



from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin



class     _UpperCAmelCase			(       A__			,      A__     ):




     @register_to_config
     def __init__(				self ,						a__ = 7_6_8 ,						):
         super().__init__()

         A__		 =					nn.Parameter(torch.zeros(1 ,						UpperCamelCase_))
         A__		 =					nn.Parameter(torch.ones(1 ,						UpperCamelCase_))




     def 		snake_case_		(				self ,						a__ = None ,						a__ = None ,						):
         A__		 =					nn.Parameter(self.mean.to(UpperCamelCase_).to(UpperCamelCase_))
         A__		 =					nn.Parameter(self.std.to(UpperCamelCase_).to(UpperCamelCase_))
         return self




     def 		snake_case_		(				self ,						a__):
         A__		 =					(embeds - self.mean) * 1.0 / self.std
         return embeds




     def 		snake_case_		(				self ,						a__):
         A__		 =					(embeds * self.std) + self.mean
         return embeds





def 		lowerCAmelCase__    (					UpperCamelCase_				:       str ,       UpperCamelCase_				:       str	)->  float:

    def get_matched_characters(UpperCamelCase_				:       str ,       UpperCamelCase_				:       str	) -> 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(UpperCamelCase_	)
                A__		 =					f"{_stra[0:_stra.index(UpperCamelCase_	)]} {_stra[_stra.index(UpperCamelCase_	) + 1:]}"

        return "".join(UpperCamelCase_	)

    # matching characters
    A__		 =					get_matched_characters(UpperCamelCase_ ,       UpperCamelCase_	)
    A__		 =					get_matched_characters(UpperCamelCase_ ,       UpperCamelCase_	)
    A__		 =					len(UpperCamelCase_	)

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

    if not match_count:
        A__		 =					0.0
    else:
        A__		 =					(
            1
            / 3
            * (
                match_count / len(UpperCamelCase_	)
                + match_count / len(UpperCamelCase_	)
                + (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"))
