code: 
  
  
  
  
  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:
      SCREAMING_SNAKE_CASE__    :    Any								=					None
  
  
  SCREAMING_SNAKE_CASE__    :    Union[str, Any]								=					logging.get_logger(__name__)
  
  
  SCREAMING_SNAKE_CASE__    :    int								=					"▁"
  
  SCREAMING_SNAKE_CASE__    :    List[str]								=					{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}
  
  SCREAMING_SNAKE_CASE__    :    str								=					{
      "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"
          )
      },
  }
  
  SCREAMING_SNAKE_CASE__    :    str								=					{
      "google/reformer-crime-and-punishment": 52_42_88,
  }
  
  
  
  class 			a_					(    a__    ):
   A						       =   VOCAB_FILES_NAMES
   A						       =   PRETRAINED_VOCAB_FILES_MAP
   A						       =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A						       =   ["input_ids", "attention_mask"]
   A						       =   ReformerTokenizer
  
  
  
  
  
   def __init__(       self			,    SCREAMING_SNAKE_CASE=None			,    SCREAMING_SNAKE_CASE=None			,    SCREAMING_SNAKE_CASE="</s>"			,    SCREAMING_SNAKE_CASE="<unk>"			,    SCREAMING_SNAKE_CASE=[]			,    **SCREAMING_SNAKE_CASE			,    )     ->				int:
  
  
  
  
      """simple docstring"""
  
  
  
      super().__init__(
          SCREAMING_SNAKE_CASE_			,    tokenizer_file=SCREAMING_SNAKE_CASE_			,    eos_token=SCREAMING_SNAKE_CASE_			,    unk_token=SCREAMING_SNAKE_CASE_			,    additional_special_tokens=SCREAMING_SNAKE_CASE_			,    **SCREAMING_SNAKE_CASE_			,    )
  
      SCREAMING_SNAKE_CASE_			=	vocab_file
      SCREAMING_SNAKE_CASE_			=	False if not self.vocab_file else True
  
  
  
  
  
   def 	A_(       self			,    SCREAMING_SNAKE_CASE			,    SCREAMING_SNAKE_CASE = None			)     ->				Tuple[str]:
  
  
  
  
      """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(SCREAMING_SNAKE_CASE_			):
         logger.error(f'Vocabulary path ({save_directory}) should be a directory'			)
         return
      SCREAMING_SNAKE_CASE_			=	os.path.join(
          SCREAMING_SNAKE_CASE_			,    (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)
  
      if os.path.abspath(self.vocab_file			) != os.path.abspath(SCREAMING_SNAKE_CASE_			):
         copyfile(self.vocab_file			,    SCREAMING_SNAKE_CASE_			)
  
      return (out_vocab_file,)
  
style_context: 
  
  
  
  
  from __future__ import annotations
  
  def lowercase						(     SCREAMING_SNAKE_CASE					,						SCREAMING_SNAKE_CASE					,						SCREAMING_SNAKE_CASE					,						SCREAMING_SNAKE_CASE   ) ->       None:
  
  
  			'''simple docstring'''
  
  
  
  
  
  
  
  			SCREAMING_SNAKE_CASE_	,		SCREAMING_SNAKE_CASE_			=	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 lowercase						(     ) ->       None:
  
  
  			'''simple docstring'''
  
  
  
  
  
  
  
  			SCREAMING_SNAKE_CASE_			=	[[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
  			SCREAMING_SNAKE_CASE_			=	int(input('Enter the element to be searched:'   )   )
  			print(SCREAMING_SNAKE_CASE   )
  			search_in_a_sorted_matrix(SCREAMING_SNAKE_CASE					,						len(SCREAMING_SNAKE_CASE   )					,						len(mat[0]   )					,						SCREAMING_SNAKE_CASE   )
  
  
  if __name__ == "__main__":
  				import doctest
  
  				doctest.testmod()
  				main()
  