




def    A						(__A   :    str   ,				__A   :    str       )   ->      float:







     """simple docstring"""


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

          return "".join(__A       )

     # matching characters
     UpperCAmelCase_          =							get_matched_characters(__A   ,				__A       )
     UpperCAmelCase_          =							get_matched_characters(__A   ,				__A       )
     UpperCAmelCase_          =							len(__A       )

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

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

     # common prefix up to 4 characters
     UpperCAmelCase_          =							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"))












from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


snake_case_ : Union[str, Any]    		=       {"configuration_gpt_neox": ["GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXConfig"]}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_ : Dict    		=       ["GPTNeoXTokenizerFast"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_ : str    		=       [
        "GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST",
        "GPTNeoXForCausalLM",
        "GPTNeoXForQuestionAnswering",
        "GPTNeoXForSequenceClassification",
        "GPTNeoXForTokenClassification",
        "GPTNeoXLayer",
        "GPTNeoXModel",
        "GPTNeoXPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_gpt_neox import (
            GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
            GPTNeoXForCausalLM,
            GPTNeoXForQuestionAnswering,
            GPTNeoXForSequenceClassification,
            GPTNeoXForTokenClassification,
            GPTNeoXLayer,
            GPTNeoXModel,
            GPTNeoXPreTrainedModel,
        )


else:
    import sys

    snake_case_ : Optional[int]    		=       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






