




from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments


def 		_lowerCamelCase				(					)			->		Optional[Any]:





  """simple docstring"""





  _lowercase: Optional[int]						     =    HfArgumentParser(UpperCamelCase							)
  try:
    _lowercase: Optional[Any]						     =    parser.parse_args_into_dataclasses()[0]
  except ValueError as e:
    _lowercase: Optional[Any]						     =    'Arg --no_{0} is no longer used, please use --no-{0} instead.'
    _lowercase: Tuple						     =    ' '.join(str(UpperCamelCase							).split(' '							)[:-1]							)
    _lowercase: Any						     =    ''
    _lowercase: List[str]						     =    eval(str(UpperCamelCase							).split(' '							)[-1]							)
    _lowercase: Optional[Any]						     =    []
    for arg in depreciated_args:
      # arg[2:] removes '--'
      if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
        # arg[5:] removes '--no_'
        full_error_msg += arg_error_msg.format(arg[5:]							)
      else:
        wrong_args.append(UpperCamelCase							)
    if len(UpperCamelCase							) > 0:
      _lowercase: int						     =    full_error_msg + begin_error_msg + str(UpperCamelCase							)
    raise ValueError(UpperCamelCase							)

  _lowercase: Optional[int]						     =    PyTorchBenchmark(args=UpperCamelCase							)
  benchmark.run()


if __name__ == "__main__":
   main()






from cva import destroyAllWindows, imread, imshow, waitKey


def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		List[str]:





  """simple docstring"""





  _lowercase     ,					_lowercase: Tuple						     =    img.shape[0], img.shape[1]

  def to_grayscale(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							):
    return 0.2_126 * red + 0.587 * green + 0.114 * blue

  def normalize(UpperCamelCase							):
    return min(UpperCamelCase					,     255							)

  for i in range(UpperCamelCase							):
    for j in range(UpperCamelCase							):
      _lowercase: Any						     =    int(to_grayscale(*img[i][j]							)							)
      _lowercase: str						     =    [
          normalize(UpperCamelCase							),
          normalize(greyscale + factor							),
          normalize(greyscale + 2 * factor							),
      ]

  return img


if __name__ == "__main__":
   # read original image
   UpperCAmelCase__						:       Optional[Any]							=    {
       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()
