scripts/training/train_text_generation.py:18:    entity_name: str,
scripts/training/train_text_generation.py:32:        entity_name,
scripts/training/train_text_generation.py:71:        "--entity_name", type=str, help="WANDB entity name", default=None
scripts/training/train_text_generation.py:89:        args.entity_name,
rl4lms/envs/text_generation/logging_utils.py:21:                 entity_name: str = None,
rl4lms/envs/text_generation/logging_utils.py:30:        self._entity_name = entity_name
rl4lms/envs/text_generation/logging_utils.py:61:                entity=self._entity_name,
rl4lms/envs/text_generation/evaluation_utils.py:55:        all_entities_discussed.extend([sample.entity for sample in batch])
rl4lms/envs/text_generation/observation.py:39:    entity: str = None
rl4lms/envs/text_generation/observation.py:123:                          entity=self.entity)
rl4lms/envs/text_generation/observation.py:185:                          entity=sample.entity)
rl4lms/envs/text_generation/utils_supervised.py:314:        curr_entities = [sample.entity for sample in batch]
rl4lms/envs/text_generation/hf_generation_utils.py:1019:                for constrained generation conditioned on the prefix, as described in [Autoregressive Entity
rl4lms/data_pools/text_generation_pool.py:13:    entity = None 
rl4lms/algorithms/common/maskable/policies.py:146:        #       really contain any layers (acts like an identity module).
