






"""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_   )







"""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""")