



"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


A    =			{
    'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
    'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/config.json',
    'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/config.json',
    'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json',
    'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/config.json',
    'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/config.json',
    'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/config.json',
    'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json',
}






class      UpperCAmelCase__		(      UpperCamelCase     ):
		lowerCAmelCase_       :	Optional[int] 							=     """albert"""



		def __init__( self  :    int      ,							snake_case  :    int=30_000      ,							snake_case  :    Optional[int]=128      ,							snake_case  :    Dict=4_096      ,							snake_case  :    str=12      ,							snake_case  :    List[Any]=1      ,							snake_case  :    List[Any]=64      ,							snake_case  :    Any=16_384      ,							snake_case  :    Any=1      ,							snake_case  :    Dict="gelu_new"      ,							snake_case  :    Optional[Any]=0      ,							snake_case  :    Optional[Any]=0      ,							snake_case  :    List[Any]=512      ,							snake_case  :    List[str]=2      ,							snake_case  :    Optional[Any]=0.02      ,							snake_case  :    List[str]=1E-1_2      ,							snake_case  :    Optional[int]=0.1      ,							snake_case  :    Dict="absolute"      ,							snake_case  :    Union[str, Any]=0      ,							snake_case  :    Tuple=2      ,							snake_case  :    int=3      ,							**snake_case  :    str      ,							)			->						int:






									'''simple docstring'''

									super().__init__(pad_token_id=snake_case      ,							bos_token_id=snake_case      ,							eos_token_id=snake_case      ,							**snake_case				)

									A         =					vocab_size
									A         =					embedding_size
									A         =					hidden_size
									A         =					num_hidden_layers
									A         =					num_hidden_groups
									A         =					num_attention_heads
									A         =					inner_group_num
									A         =					hidden_act
									A         =					intermediate_size
									A         =					hidden_dropout_prob
									A         =					attention_probs_dropout_prob
									A         =					max_position_embeddings
									A         =					type_vocab_size
									A         =					initializer_range
									A         =					layer_norm_eps
									A         =					classifier_dropout_prob
									A         =					position_embedding_type






class      UpperCAmelCase__		(      UpperCamelCase     ):



		@property
		def 					A_		( self  :    Optional[int]				)			->						Mapping[str, Mapping[int, str]]:






									'''simple docstring'''

									if self.task == "multiple-choice":
																A         =					{0: 'batch', 1: 'choice', 2: 'sequence'}
									else:
																A         =					{0: 'batch', 1: 'sequence'}
									return OrderedDict(
									    [
									        ('input_ids', dynamic_axis),
									        ('attention_mask', dynamic_axis),
									        ('token_type_ids', dynamic_axis),
									    ]				)








"""simple docstring"""







def   lowerCAmelCase__			(     lowerCamelCase__				,      lowerCamelCase__			) ->							float:

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

														return "".join(lowerCamelCase__			)

							# matching characters
							A         =					get_matched_characters(lowerCamelCase__				,      lowerCamelCase__			)
							A         =					get_matched_characters(lowerCamelCase__				,      lowerCamelCase__			)
							A         =					len(lowerCamelCase__			)

							# transposition
							A         =					(
							    len([(ca, ca) for ca, ca in zip(lowerCamelCase__				,      lowerCamelCase__			) if ca != ca]			) // 2
							)

							if not match_count:
														A         =					0.0
							else:
														A         =					(
														    1
														    / 3
														    * (
														        match_count / len(lowerCamelCase__			)
														        + match_count / len(lowerCamelCase__			)
														        + (match_count - transpositions) / match_count
														    )
														)

							# common prefix up to 4 characters
							A         =					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'))



