code: 
  
  from typing import Optional, Tuple
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_openai import OpenAIGPTTokenizer
  
  
  snake_case_    						=				logging.get_logger(__name__)
  
  snake_case_    						=				{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}
  
  snake_case_    						=				{
      '''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_    						=				{
      '''openai-gpt''': 512,
  }
  
  
  class    SCREAMING_SNAKE_CASE__      (__snake_case  ):
  
      '''simple docstring'''
  
  
  
  
  
      __lowerCamelCase		: int														=  VOCAB_FILES_NAMES
      __lowerCamelCase		: List[str]														=  PRETRAINED_VOCAB_FILES_MAP
      __lowerCamelCase		: Union[str, Any]														=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __lowerCamelCase		: Any														=  ["""input_ids""", """attention_mask"""]
      __lowerCamelCase		: List[str]														=  OpenAIGPTTokenizer
  
  
  
  
  
      def __init__(   self		,     a=None		,     a=None		,     a=None		,     a="<unk>"		,     **a):
           super().__init__(a		,     a		,     tokenizer_file=a		,     unk_token=a		,     **a)
  
  
  
  
  
      @property
      def    snake_case_       (   self):
           return True
  
  
  
  
  
      def    snake_case_       (   self		,     a		,     a = None):
           lowercase__					:     Optional[int]   = self._tokenizer.model.save(a		,     name=a)
           return tuple(a)
  
  
style_context: 
  
  from cva import destroyAllWindows, imread, imshow, waitKey
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					int			,  SCREAMING_SNAKE_CASE_	:					int    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       lowercase__   ,				lowercase__					:     Optional[int]   = img.shape[0], img.shape[1]
  
       def to_grayscale(SCREAMING_SNAKE_CASE_	:					Union[str, Any]			,  SCREAMING_SNAKE_CASE_	:					List[Any]			,  SCREAMING_SNAKE_CASE_	:					Union[str, Any]    ):
            return 0.2126 * red + 0.587 * green + 0.114 * blue
  
       def normalize(SCREAMING_SNAKE_CASE_	:					int    ):
            return min(SCREAMING_SNAKE_CASE_			,  255    )
  
       for i in range(SCREAMING_SNAKE_CASE_    ):
            for j in range(SCREAMING_SNAKE_CASE_    ):
                 lowercase__					:     str   = int(to_grayscale(*img[i][j]    )    )
                 lowercase__					:     Dict   = [
                     normalize(SCREAMING_SNAKE_CASE_    ),
                     normalize(greyscale + factor    ),
                     normalize(greyscale + 2 * factor    ),
                 ]
  
       return img
  
  
  if __name__ == "__main__":
         # read original image
         snake_case_    						=				{
             percentage: imread('''image_data/lena.jpg''', 1) for percentage in (10, 20, 30, 40)
         }
  
         for percentage, img in images.items():
                make_sepia(img, percentage)
  
         for percentage, img in images.items():
                imshow(F'''Original image with sepia (factor: {percentage})''', img)
  
         waitKey(0)
         destroyAllWindows()
  
  