



"""simple docstring"""




import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_reformer import ReformerTokenizer
else:
      __UpperCAmelCase	=			None


__UpperCAmelCase	=			logging.get_logger(__name__)


__UpperCAmelCase	=			'▁'

__UpperCAmelCase	=			{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__UpperCAmelCase	=			{
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    },
    'tokenizer_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
        )
    },
}

__UpperCAmelCase	=			{
    'google/reformer-crime-and-punishment': 52_4288,
}







class        __lowercase     (      __lowerCamelCase   ):
  snake_case_			    =    VOCAB_FILES_NAMES
  snake_case_			    =    PRETRAINED_VOCAB_FILES_MAP
  snake_case_			    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  snake_case_			    =    ["""input_ids""", """attention_mask"""]
  snake_case_			    =    ReformerTokenizer

  def __init__(					self						:     List[Any]   ,A						:     Dict=None   ,A						:     List[str]=None   ,A						:     Union[str, Any]="</s>"   ,A						:     List[str]="<unk>"   ,A						:     Tuple=[]   ,**A						:     Optional[int]   ,):






   '''simple docstring'''
   super().__init__(
       A   ,tokenizer_file=A   ,eos_token=A   ,unk_token=A   ,additional_special_tokens=A   ,**A   ,)

   UpperCAmelCase__   :					Tuple   				=   vocab_file
   UpperCAmelCase__   :					Optional[Any]   				=   False if not self.vocab_file else True




  def 				__lowercase    (					self						:     Any   ,A						:     str   ,A						:     Optional[str] = None      ):






   '''simple docstring'''
   if not self.can_save_slow_tokenizer:
    raise ValueError(
        """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
        """tokenizer."""      )

   if not os.path.isdir(A      ):
    logger.error(f"Vocabulary path ({save_directory}) should be a directory"      )
    return
   UpperCAmelCase__   :					Tuple   				=   os.path.join(
       A   ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )

   if os.path.abspath(self.vocab_file      ) != os.path.abspath(A      ):
    copyfile(self.vocab_file   ,A      )

   return (out_vocab_file,)








"""simple docstring"""




from __future__ import annotations
def 					lowerCAmelCase  (   __UpperCamelCase							,      __UpperCamelCase							,      __UpperCamelCase							,      __UpperCamelCase ):
 '''simple docstring'''





 UpperCAmelCase__				, UpperCAmelCase__   :					Optional[Any]   				=   m - 1, 0
 while i >= 0 and j < n:
  if key == mat[i][j]:
   print(F"Key {key} found at row- {i + 1} column- {j + 1}" )
   return
  if key < mat[i][j]:
   i -= 1
  else:
   j += 1
 print(F"Key {key} not found" )
def 					lowerCAmelCase  (   ):
 '''simple docstring'''





 UpperCAmelCase__   :					Union[str, Any]   				=   [[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
 UpperCAmelCase__   :					int   				=   int(input("""Enter the element to be searched:""" ) )
 print(__UpperCamelCase )
 search_in_a_sorted_matrix(__UpperCamelCase							,      len(__UpperCamelCase )							,      len(mat[0] )							,      __UpperCamelCase )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()





