


"""simple docstring"""

import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
     from transformers.pipelines.conversational import Conversation


UpperCAmelCase__  							=logging.get_logger(__name__)

UpperCAmelCase__  							={"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

UpperCAmelCase__  							={
    "tokenizer_file": {
        "EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json",
    },
}

UpperCAmelCase__  							={
    "gpt-neox-20b": 2048,
}





class    lowerCamelCase__						(		__lowercase    ):
      a :     List[str]											=		VOCAB_FILES_NAMES
      a :     Optional[Any]											=		PRETRAINED_VOCAB_FILES_MAP
      a :     Tuple											=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a :     Tuple											=		['input_ids', 'attention_mask']
      def __init__(		self	:	List[Any]      ,       A_	:	Tuple=None      ,       A_	:	Optional[Any]=None      ,       A_	:	str=None      ,       A_	:	Optional[int]="<|endoftext|>"      ,       A_	:	Dict="<|endoftext|>"      ,       A_	:	List[Any]="<|endoftext|>"      ,       A_	:	Any=False      ,       **A_	:	List[str]      ,       ):






       '''simple docstring'''


       super().__init__(
           __A      ,       __A      ,       tokenizer_file=__A      ,       unk_token=__A      ,       bos_token=__A      ,       eos_token=__A      ,       add_prefix_space=__A      ,       **__A      ,       )

       __lowercase									=	json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
       if pre_tok_state.get("""add_prefix_space"""      ,       __A							) != add_prefix_space:
        __lowercase									=	getattr(__A      ,       pre_tok_state.pop("""type"""							)							)
        __lowercase									=	add_prefix_space
        __lowercase									=	pre_tok_class(**__A							)

       __lowercase									=	add_prefix_space
      def SCREAMING_SNAKE_CASE_	(		self	:	Tuple      ,       A_	:	Union[str, Any]      ,       A_	:	int = None							):






       '''simple docstring'''


       __lowercase									=	self._tokenizer.model.save(__A      ,       name=__A							)
       return tuple(__A							)






      def SCREAMING_SNAKE_CASE_	(		self	:	str      ,       A_	:	Any							):






       '''simple docstring'''


       __lowercase									=	[]
       for is_user, text in conversation.iter_texts():
        input_ids.extend(self.encode(__A      ,       add_special_tokens=__A							) + [self.eos_token_id]							)

       if len(__A							) > self.model_max_length:
        __lowercase									=	input_ids[-self.model_max_length :]
       return input_ids




"""simple docstring"""

def lowerCAmelCase_      (				UpperCamelCase__	: str				,   UpperCamelCase__	: str ):






 """simple docstring"""







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

  return "".join(UpperCamelCase__ )

 # matching characters
 __lowercase									=	get_matched_characters(UpperCamelCase__				,   UpperCamelCase__ )
 __lowercase									=	get_matched_characters(UpperCamelCase__				,   UpperCamelCase__ )
 __lowercase									=	len(UpperCamelCase__ )

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

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

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