



"""simple docstring"""


import torch
import trajectory.utils as utils

from transformers import TrajectoryTransformerModel







class    A_    (  utils.Parser       ):



						"""simple docstring"""
						__UpperCamelCase	       =							"halfcheetah-medium-expert-v2"
						__UpperCamelCase	       =							"config.offline"


def 				_lowerCAmelCase   (     lowercase_	,			lowercase_	,			lowercase_	,			lowercase_	,			lowercase_		):
						UpperCAmelCase   ,					UpperCAmelCase    =				utils.load_model(lowercase_	,			lowercase_	,			lowercase_	,			epoch=lowercase_	,			device=lowercase_		)
						UpperCAmelCase    =				TrajectoryTransformerModel(gpt.config		)

						trajectory_transformer.tok_emb.load_state_dict(gpt.tok_emb.state_dict()		)
						UpperCAmelCase    =				gpt.pos_emb
						trajectory_transformer.drop.load_state_dict(gpt.drop.state_dict()		)
						trajectory_transformer.ln_f.load_state_dict(gpt.ln_f.state_dict()		)
						trajectory_transformer.head.load_state_dict(gpt.head.state_dict()		)

						for i, block in enumerate(gpt.blocks		):
												trajectory_transformer.blocks[i].lna.load_state_dict(gpt.blocks[i].lna.state_dict()		)
												trajectory_transformer.blocks[i].lna.load_state_dict(gpt.blocks[i].lna.state_dict()		)
												trajectory_transformer.blocks[i].attn.load_state_dict(gpt.blocks[i].attn.state_dict()		)

												trajectory_transformer.blocks[i].la.load_state_dict(gpt.blocks[i].mlp[0].state_dict()		)
												trajectory_transformer.blocks[i].act.load_state_dict(gpt.blocks[i].mlp[1].state_dict()		)
												trajectory_transformer.blocks[i].la.load_state_dict(gpt.blocks[i].mlp[2].state_dict()		)
												trajectory_transformer.blocks[i].drop.load_state_dict(gpt.blocks[i].mlp[3].state_dict()		)

						torch.save(trajectory_transformer.state_dict()	,			'pytorch_model.bin'		)


if __name__ == "__main__":
				snake_case_         = Parser().parse_args("""plan""")
				convert_trajectory_transformer_original_pytorch_checkpoint_to_pytorch(
				    args.logbase, args.dataset, args.gpt_loadpath, args.gpt_epoch, args.device
				)










"""simple docstring"""


import warnings

from .generation import FlaxGenerationMixin







class    A_    (  SCREAMING_SNAKE_CASE_       ):



						"""simple docstring"""
						# warning at import time
						warnings.warn(
						    """Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will """
						    """be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead."""			,     SCREAMING_SNAKE_CASE_			,     )





