code: 
  
  
  
  
  
  
  """simple docstring"""
  from typing import Optional, Tuple
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_openai import OpenAIGPTTokenizer
  
  
  snake_case   :   Optional[Any]    		=		logging.get_logger(__name__)
  
  snake_case   :   Optional[Any]    		=		{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}
  
  snake_case   :   Optional[int]    		=		{
      """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"""},
  }
  
  snake_case   :   int    		=		{
      """openai-gpt""": 5_1_2,
  }
  
  
  
  class 					UpperCamelCase__   (							a_):
  
  
  
  
  
  
  
  				"""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   :  Any							,						UpperCamelCase_   :  Any=None							,						UpperCamelCase_   :  Optional[int]=None							,						UpperCamelCase_   :  Dict=None							,						UpperCamelCase_   :  Any="<unk>"							,						**UpperCamelCase_   :  List[Any]   ):
  
  
  
  
  
  											'''simple docstring'''
  
  											super().__init__(UpperCamelCase_							,						UpperCamelCase_							,						tokenizer_file=UpperCamelCase_							,						unk_token=UpperCamelCase_							,						**UpperCamelCase_   )
  
  
  
  
  
  
  
  				@property
  				def 							a__ (		self   :  Optional[int]   ):
  
  
  
  
  
  											'''simple docstring'''
  
  											return True
  
  
  
  
  
  
  
  				def 							a__ (		self   :  Optional[Any]							,						UpperCamelCase_   :  str							,						UpperCamelCase_   :  Optional[str] = None   ):
  
  
  
  
  
  											'''simple docstring'''
  
  											__magic_name__										=						self._tokenizer.model.save(UpperCamelCase_							,						name=UpperCamelCase_   )
  											return tuple(UpperCamelCase_   )
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  def        A	(							__snake_case:   Dict   ,    __snake_case:   Tuple     )						->		int:
  
         """simple docstring"""
  
  
  
  
  
         sequence.append(__snake_case     )
  
         __magic_name__										=						0
         while sequence[index] != target:
                index += 1
  
         sequence.pop()
  
         if index == len(__snake_case     ):
                return None
  
         return index
  
  
  if __name__ == "__main__":
   snake_case   :   Dict    		=		input("""Enter numbers separated by comma:\n""").strip()
   snake_case   :   List[str]    		=		[int(item) for item in user_input.split(""",""")]
  
   snake_case   :   Union[str, Any]    		=		input("""Enter a single number to be found in the list:\n""")
   snake_case   :   str    		=		int(target_input)
   snake_case   :   Any    		=		sentinel_linear_search(sequence, target)
   if result is not None:
    print(f"""{target} found at positions: {result}""")
   else:
    print("""Not found""")