





'''simple docstring'''




from ...processing_utils import ProcessorMixin
class 			_lowerCAmelCase		(			A__	):






     """simple docstring"""






     snake_case_						      =   ["image_processor", "feature_extractor"]
     snake_case_						      =   "TvltImageProcessor"
     snake_case_						      =   "TvltFeatureExtractor"



     def __init__(   self							:			Union[str, Any]   ,       __snake_case							:			Optional[int]   ,       __snake_case							:			int						)->	Union[str, Any]:
        super().__init__(image_processor=__snake_case   ,       feature_extractor=__snake_case						)

        snake_case 						=   image_processor
        snake_case 						=   feature_extractor



     def __call__(   self							:			Dict   ,       __snake_case							:			Union[str, Any]=None   ,       __snake_case							:			List[str]=None   ,       __snake_case							:			Any=None   ,       __snake_case							:			Any=None   ,       __snake_case							:			int=False   ,       __snake_case							:			int=False   ,       *__snake_case							:			Dict   ,       **__snake_case							:			Dict   ,       )->	Any:

        if images is None and audio is None:
           raise ValueError("""You need to specify either an `images` or `audio` input to process."""						)

        snake_case 						=   None
        if images is not None:
           snake_case 						=   self.image_processor(__snake_case   ,       mask_pixel=__snake_case   ,       *__snake_case   ,       **__snake_case						)
        if images_mixed is not None:
           snake_case 						=   self.image_processor(__snake_case   ,       is_mixed=__snake_case   ,       *__snake_case   ,       **__snake_case						)
        if audio is not None:
           snake_case 						=   self.feature_extractor(
               __snake_case   ,       *__snake_case   ,       sampling_rate=__snake_case   ,       mask_audio=__snake_case   ,       **__snake_case						)

        snake_case 						=   {}
        if audio is not None:
           output_dict.update(__snake_case						)
        if images is not None:
           output_dict.update(__snake_case						)
        if images_mixed_dict is not None:
           output_dict.update(__snake_case						)
        return output_dict



     @property
     def      lowerCAmelCase			(   self							:			str						)->	List[Any]:
        snake_case 						=   self.image_processor.model_input_names
        snake_case 						=   self.feature_extractor.model_input_names
        return list(dict.fromkeys(image_processor_input_names + feature_extractor_input_names						)						)








'''simple docstring'''




from __future__ import annotations





def 	__lowerCamelCase			(      __lowerCAmelCase       :							Any      ,    __lowerCAmelCase       :							str      ,    __lowerCAmelCase       :							Any      ,    __lowerCAmelCase       :							int		)		->  Tuple:  # noqa: E741
   while r - l > 1:
      snake_case 						=   (l + r) // 2
      if v[m] >= key:
         snake_case 						=   m
      else:
         snake_case 						=   m  # noqa: E741
   return r





def 	__lowerCamelCase			(      __lowerCAmelCase       :							list[int]		)		->  int:
   if len(__lowerCAmelCase		) == 0:
      return 0

   snake_case 						=   [0] * len(__lowerCAmelCase		)
   snake_case 						=   1

   snake_case 						=   v[0]

   for i in range(1      ,    len(__lowerCAmelCase		)		):
      if v[i] < tail[0]:
         snake_case 						=   v[i]
      elif v[i] > tail[length - 1]:
         snake_case 						=   v[i]
         length += 1
      else:
         snake_case 						=   v[i]

   return length


if __name__ == "__main__":
 import doctest

 doctest.testmod()

