code: 
  
  
  
  
  
  '''simple docstring'''
  
  from typing import Optional, Tuple
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_openai import OpenAIGPTTokenizer
  
  
  lowercase_			       =				logging.get_logger(__name__)
  
  lowercase_			       =				{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}
  
  lowercase_			       =				{
      """vocab_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/vocab.json"""},
      """merges_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/merges.txt"""},
      """tokenizer_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/tokenizer.json"""},
  }
  
  lowercase_			       =				{
      """openai-gpt""": 512,
  }
  
  
  class       a_  (       snake_case_ ):
  
      '''simple docstring'''
      UpperCamelCase									=				VOCAB_FILES_NAMES
      UpperCamelCase									=				PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase									=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCamelCase									=				['''input_ids''', '''attention_mask''']
      UpperCamelCase									=				OpenAIGPTTokenizer
  
  
      def __init__(	self				,	A=None				,	A=None				,	A=None				,	A="<unk>"				,	**A )	->     Union[str, Any]:
          super().__init__(A				,	A				,	tokenizer_file=A				,	unk_token=A				,	**A )
  
  
      @property
      def     snake_case_(	self )	->     List[Any]:
          return True
  
  
  
  
  
      def     snake_case_(	self				,	A				,	A = None )	->     Tuple[str]:
          _SCREAMING_SNAKE_CASE             =    self._tokenizer.model.save(A				,	name=A )
          return tuple(A )
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  import safs
  
  
  class       a_  (       safs.SaFileSystem ):
  
      '''simple docstring'''
  
  
  
  