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:
     __A  							=			None
  
  
  __A  							=			logging.get_logger(__name__)
  
  
  __A  							=			"""▁"""
  
  __A  							=			{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}
  
  __A  							=			{
      """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"""
          )
      },
  }
  
  __A  							=			{
      """google/reformer-crime-and-punishment""": 52_42_88,
  }
  
  
  
  class 							_A (    UpperCAmelCase__							):
      """simple docstring"""
  
      lowerCamelCase  :       Dict   =   VOCAB_FILES_NAMES
      lowerCamelCase  :       Optional[Any]   =   PRETRAINED_VOCAB_FILES_MAP
      lowerCamelCase  :       List[Any]   =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCamelCase  :       str   =   ['input_ids', 'attention_mask']
      lowerCamelCase  :       List[Any]   =   ReformerTokenizer
  
  
  
      def __init__(							self			:    int   ,    __SCREAMING_SNAKE_CASE			:    Any=None   ,    __SCREAMING_SNAKE_CASE			:    Union[str, Any]=None   ,    __SCREAMING_SNAKE_CASE			:    int="</s>"   ,    __SCREAMING_SNAKE_CASE			:    List[Any]="<unk>"   ,    __SCREAMING_SNAKE_CASE			:    int=[]   ,    **__SCREAMING_SNAKE_CASE			:    Optional[Any]   ,    )			->       Dict:
             super().__init__(
                 lowerCamelCase__   ,    tokenizer_file=lowerCamelCase__   ,    eos_token=lowerCamelCase__   ,    unk_token=lowerCamelCase__   ,    additional_special_tokens=lowerCamelCase__   ,    **lowerCamelCase__   ,    )
  
             __UpperCAmelCase    							=vocab_file
             __UpperCAmelCase    							=False if not self.vocab_file else True
  
  
  
      def _a       (							self			:    int   ,    __SCREAMING_SNAKE_CASE			:    Any   ,    __SCREAMING_SNAKE_CASE			:    Dict = None			)			->       Dict:
             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(lowerCamelCase__			):
                    logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''			)
                    return
             __UpperCAmelCase    							=os.path.join(
                 lowerCamelCase__   ,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]			)
  
             if os.path.abspath(self.vocab_file			) != os.path.abspath(lowerCamelCase__			):
                    copyfile(self.vocab_file   ,    lowerCamelCase__			)
  
             return (out_vocab_file,)
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  __A  							=  [0.485, 0.456, 0.406]
  __A  							=  [0.229, 0.224, 0.225]
  __A  							=  [0.5, 0.5, 0.5]
  __A  							=  [0.5, 0.5, 0.5]
  __A  							=  [0.4814_5466, 0.457_8275, 0.4082_1073]
  __A  							=  [0.2686_2954, 0.2613_0258, 0.2757_7711]
  
  
  
  
  