






'''simple docstring'''







from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase       		=      logging.get_logger(__name__)

__lowerCAmelCase       		=      {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}





class 	SCREAMING_SNAKE_CASE					(					SCREAMING_SNAKE_CASE_       ):
			snake_case__  =				"openai-gpt"
			snake_case__  =				{
			    "max_position_embeddings": "n_positions",
			    "hidden_size": "n_embd",
			    "num_attention_heads": "n_head",
			    "num_hidden_layers": "n_layer",
			}






			def __init__( self      :			List[Any]  ,						__SCREAMING_SNAKE_CASE      :			Optional[int]=4_0478  ,						__SCREAMING_SNAKE_CASE      :			List[str]=512  ,						__SCREAMING_SNAKE_CASE      :			Any=768  ,						__SCREAMING_SNAKE_CASE      :			Optional[int]=12  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any]=12  ,						__SCREAMING_SNAKE_CASE      :			Any="gelu"  ,						__SCREAMING_SNAKE_CASE      :			int=0.1  ,						__SCREAMING_SNAKE_CASE      :			List[Any]=0.1  ,						__SCREAMING_SNAKE_CASE      :			List[str]=0.1  ,						__SCREAMING_SNAKE_CASE      :			List[Any]=1e-5  ,						__SCREAMING_SNAKE_CASE      :			str=0.02  ,						__SCREAMING_SNAKE_CASE      :			int="cls_index"  ,						__SCREAMING_SNAKE_CASE      :			str=True  ,						__SCREAMING_SNAKE_CASE      :			Optional[int]=None  ,						__SCREAMING_SNAKE_CASE      :			List[Any]=True  ,						__SCREAMING_SNAKE_CASE      :			List[str]=0.1  ,						**__SCREAMING_SNAKE_CASE      :			List[str]  ,						)			->			int:
							a_		:  Optional[int]											=      vocab_size
							a_		:  str											=      n_positions
							a_		:  Tuple											=      n_embd
							a_		:  Dict											=      n_layer
							a_		:  Optional[Any]											=      n_head
							a_		:  List[str]											=      afn
							a_		:  str											=      resid_pdrop
							a_		:  Tuple											=      embd_pdrop
							a_		:  List[Any]											=      attn_pdrop
							a_		:  List[Any]											=      layer_norm_epsilon
							a_		:  Tuple											=      initializer_range
							a_		:  Optional[Any]											=      summary_type
							a_		:  List[str]											=      summary_use_proj
							a_		:  List[str]											=      summary_activation
							a_		:  List[str]											=      summary_first_dropout
							a_		:  Optional[Any]											=      summary_proj_to_labels
							super().__init__(**__SCREAMING_SNAKE_CASE					)












'''simple docstring'''







def 		_UpperCAmelCase   (							__A							:   str						,		__A							:   str      ):

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

								return "".join(__A      )

				# matching characters
				a_		:  Optional[Any]											=      get_matched_characters(__A						,		__A      )
				a_		:  int											=      get_matched_characters(__A						,		__A      )
				a_		:  Any											=      len(__A      )

				# transposition
				a_		:  List[Any]											=      (
				    len([(ca, ca) for ca, ca in zip(__A						,		__A      ) if ca != ca]      ) // 2
				)

				if not match_count:
								a_		:  Dict											=      0.0
				else:
								a_		:  Optional[int]											=      (
								    1
								    / 3
								    * (
								        match_count / len(__A      )
								        + match_count / len(__A      )
								        + (match_count - transpositions) / match_count
								    )
								)

				# common prefix up to 4 characters
				a_		:  List[str]											=      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'))




