code: from __future__ import annotations
  def 	UpperCamelCase			(     snake_case__ :					int ,  snake_case__ :					List[str] ,  snake_case__ :					Dict			)			->  int | float:
  
  
  
  
  
  
     if len(UpperCAmelCase_			) == 0:
        raise ValueError('find_min() arg is an empty sequence'			)
     if (
         left >= len(UpperCAmelCase_			)
         or left < -len(UpperCAmelCase_			)
         or right >= len(UpperCAmelCase_			)
         or right < -len(UpperCAmelCase_			)
     ):
        raise IndexError('list index out of range'			)
     if left == right:
        return nums[left]
     UpperCamelCase					:						Union[str, Any]					=			(left + right) >> 1  # the middle
     UpperCamelCase					:						int					=			find_min(UpperCAmelCase_ ,  UpperCAmelCase_ ,  UpperCAmelCase_			)  # find min in range[left, mid]
     UpperCamelCase					:						Any					=			find_min(UpperCAmelCase_ ,  mid + 1 ,  UpperCAmelCase_			)  # find min in range[mid + 1, right]
  
     return left_min if left_min <= right_min else right_min
  
  
  if __name__ == "__main__":
      import doctest
  
      doctest.testmod(verbose=True)
  
  
  
  
style_context: 
  
  
  
  from typing import Optional, Tuple
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_openai import OpenAIGPTTokenizer
  
  
  __UpperCAmelCase      = logging.get_logger(__name__)
  
  __UpperCAmelCase      = {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}
  
  __UpperCAmelCase      = {
      '''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'''},
  }
  
  __UpperCAmelCase      = {
      '''openai-gpt''': 512,
  }
  
  
  
  class        lowerCAmelCase_	(						a__							):
         UpperCAmelCase__       :      Union[str, Any]       =						VOCAB_FILES_NAMES
         UpperCAmelCase__       :      int       =						PRETRAINED_VOCAB_FILES_MAP
         UpperCAmelCase__       :      Optional[int]       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
         UpperCAmelCase__       :      Optional[int]       =						["input_ids", "attention_mask"]
         UpperCAmelCase__       :      Tuple       =						OpenAIGPTTokenizer
         def __init__(    self,    SCREAMING_SNAKE_CASE_=None,    SCREAMING_SNAKE_CASE_=None,    SCREAMING_SNAKE_CASE_=None,    SCREAMING_SNAKE_CASE_="<unk>",    **SCREAMING_SNAKE_CASE_ )  ->	List[str]:
            super().__init__(SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_,    tokenizer_file=SCREAMING_SNAKE_CASE_,    unk_token=SCREAMING_SNAKE_CASE_,    **SCREAMING_SNAKE_CASE_ )
         @property
         def       snake_case_ (    self )  ->	Dict:
            return True
  
  
  
  
  
  
         def       snake_case_ (    self,    SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_ = None )  ->	Tuple[str]:
            UpperCamelCase					:						List[Any]					=			self._tokenizer.model.save(SCREAMING_SNAKE_CASE_,    name=SCREAMING_SNAKE_CASE_ )
            return tuple(SCREAMING_SNAKE_CASE_ )
  
  
  
  