



import math

def      A_ (		__a       :			Optional[Any]						):

				"""simple docstring"""
				if number == 0:
								a__			 =						"""Zero"""
								return words
				else:
								a__			 =						math.logaa(SCREAMING_SNAKE_CASE_						)
								a__			 =						digits + 1
								a__			 =						{}
								a__			 =						""""""
								a__			 =						"""One"""
								a__			 =						"""Two"""
								a__			 =						"""Three"""
								a__			 =						"""Four"""
								a__			 =						"""Five"""
								a__			 =						"""Six"""
								a__			 =						"""Seven"""
								a__			 =						"""Eight"""
								a__			 =						"""Nine"""

								a__			 =						{}
								a__			 =						""""""
								a__			 =						"""Twenty"""
								a__			 =						"""Thirty"""
								a__			 =						"""Forty"""
								a__			 =						"""Fifty"""
								a__			 =						"""Sixty"""
								a__			 =						"""Seventy"""
								a__			 =						"""Eighty"""
								a__			 =						"""Ninety"""

								a__			 =						{}
								a__			 =						"""Ten"""
								a__			 =						"""Eleven"""
								a__			 =						"""Twelve"""
								a__			 =						"""Thirteen"""
								a__			 =						"""Fourteen"""
								a__			 =						"""Fifteen"""
								a__			 =						"""Sixteen"""
								a__			 =						"""Seventeen"""
								a__			 =						"""Eighteen"""
								a__			 =						"""Nineteen"""

								a__			 =						{}
								a__			 =						"""Hundred,"""
								a__			 =						"""Thousand,"""
								a__			 =						"""Lakh,"""
								a__			 =						"""Crore,"""

								a__			 =						number
								a__			 =						""""""
								a__			 =						0
								a__			 =						int(SCREAMING_SNAKE_CASE_						)
								while counter < digits:
												a__			 =						temp_num % 10
												if counter % 2 == 0:
																a__			 =						""""""
																if counter in placevalue and current != 0:
																				a__			 =						placevalue[counter]
																if counter == 2:
																				a__			 =						singles[current] + addition + words
																elif counter == 0:
																				if ((temp_num % 100) // 10) == 1:
																								a__			 =						teens[current] + addition + words
																								a__			 =						temp_num // 10
																								counter += 1
																				else:
																								a__			 =						singles[current] + addition + words

																else:
																				a__			 =						doubles[current] + addition + words

												else:
																if counter == 1:
																				if current == 1:
																								a__			 =						teens[number % 10] + words
																				else:
																								a__			 =						""""""
																								if counter in placevalue:
																												a__			 =						placevalue[counter]
																								a__			 =						doubles[current] + addition + words
																else:
																				a__			 =						""""""
																				if counter in placevalue:
																								if current == 0 and ((temp_num % 100) // 10) == 0:
																												a__			 =						""""""
																								else:
																												a__			 =						placevalue[counter]
																				if ((temp_num % 100) // 10) == 1:
																								a__			 =						teens[current] + addition + words
																								a__			 =						temp_num // 10
																								counter += 1
																				else:
																								a__			 =						singles[current] + addition + words
												counter += 1
												a__			 =						temp_num // 10
				return words


if __name__ == "__main__":
				import doctest

				doctest.testmod()






import torch
import trajectory.utils as utils

from transformers import TrajectoryTransformerModel

class 	__snake_case (				utils.Parser):







							'''simple docstring'''






							UpperCamelCase__			: str             =   "halfcheetah-medium-expert-v2"
							UpperCamelCase__			: str             =   "config.offline"




def      A_ (		__a       :			List[Any]	,						__a       :			Union[str, Any]	,						__a       :			Optional[Any]	,						__a       :			Dict	,						__a       :			Union[str, Any]						):

				"""simple docstring"""
				a__ ,     a__			 =						utils.load_model(__a	,						__a	,						__a	,						epoch=__a	,						device=__a						)
				a__			 =						TrajectoryTransformerModel(gpt.config						)

				trajectory_transformer.tok_emb.load_state_dict(gpt.tok_emb.state_dict()						)
				a__			 =						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__":
	UpperCAmelCase								=   Parser().parse_args("""plan""")
	convert_trajectory_transformer_original_pytorch_checkpoint_to_pytorch(
	    args.logbase, args.dataset, args.gpt_loadpath, args.gpt_epoch, args.device
	)

