


def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase     ):

							def get_matched_characters(__lowerCamelCase							,     __lowerCamelCase     ) -> str:
														__snake_case		:      Union[str, Any]										=       []
														__snake_case		:      Optional[int]										=       min(len(_stra     )							,     len(_stra     )     ) // 2
														for i, l in enumerate(_stra     ):
																					__snake_case		:      Tuple										=       int(max(0							,     i - limit     )     )
																					__snake_case		:      Optional[Any]										=       int(min(i + limit + 1							,     len(_stra     )     )     )
																					if l in _stra[left:right]:
																												matched.append(__lowerCamelCase     )
																												__snake_case		:      Dict										=       F'{_stra[0:_stra.index(__lowerCamelCase     )]} {_stra[_stra.index(__lowerCamelCase     ) + 1:]}'

														return "".join(__lowerCamelCase     )

							# matching characters
							__snake_case		:      str										=       get_matched_characters(__lowerCamelCase							,     __lowerCamelCase     )
							__snake_case		:      List[str]										=       get_matched_characters(__lowerCamelCase							,     __lowerCamelCase     )
							__snake_case		:      List[str]										=       len(__lowerCamelCase     )

							# transposition
							__snake_case		:      Tuple										=       (
							    len([(ca, ca) for ca, ca in zip(__lowerCamelCase							,     __lowerCamelCase     ) if ca != ca]     ) // 2
							)

							if not match_count:
														__snake_case		:      List[str]										=       0.0
							else:
														__snake_case		:      str										=       (
														    1
														    / 3
														    * (
														        match_count / len(__lowerCamelCase     )
														        + match_count / len(__lowerCamelCase     )
														        + (match_count - transpositions) / match_count
														    )
														)

							# common prefix up to 4 characters
							__snake_case		:      int										=       0
							for ca, ca in zip(stra[:4]							,     stra[:4]     ):
														if ca == ca:
																					prefix_len += 1
														else:
																					break

							return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			print(jaro_winkler("hello", "world"))





import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


_snake_case					:		Union[str, Any]      =    ["small", "medium", "large"]

_snake_case					:		List[Any]      =    "lm_head.decoder.weight"
_snake_case					:		Optional[Any]      =    "lm_head.weight"







def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase     ):
							__snake_case		:      Tuple										=       torch.load(__lowerCamelCase     )
							__snake_case		:      Dict										=       d.pop(__lowerCamelCase     )
							os.makedirs(__lowerCamelCase							,     exist_ok=__lowerCamelCase     )
							torch.save(__lowerCamelCase							,     os.path.join(__lowerCamelCase							,     __lowerCamelCase     )     )


if __name__ == "__main__":
			_snake_case					:		Dict      =    argparse.ArgumentParser()
			parser.add_argument("--dialogpt_path", default=".", type=str)
			_snake_case					:		Any      =    parser.parse_args()
			for MODEL in DIALOGPT_MODELS:
						_snake_case					:		Dict      =    os.path.join(args.dialogpt_path, f'''{MODEL}_ft.pkl''')
						_snake_case					:		List[str]      =    f'''./DialoGPT-{MODEL}'''
						convert_dialogpt_checkpoint(
						    checkpoint_path,
						    pytorch_dump_folder_path,
						)

