






"""simple docstring"""

from ...processing_utils import ProcessorMixin

class 						A_							(      snake_case_  ):
				UpperCAmelCase__        =				['''image_processor''', '''feature_extractor''']
				UpperCAmelCase__        =				'''TvltImageProcessor'''
				UpperCAmelCase__        =				'''TvltFeatureExtractor'''







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

										__magic_name__            =     image_processor
										__magic_name__            =     feature_extractor







				def __call__(							self							:						str						,    __lowerCamelCase							:						Optional[int]=None						,    __lowerCamelCase							:						Optional[int]=None						,    __lowerCamelCase							:						Any=None						,    __lowerCamelCase							:						Optional[int]=None						,    __lowerCamelCase							:						Tuple=False						,    __lowerCamelCase							:						str=False						,    *__lowerCamelCase							:						int						,    **__lowerCamelCase							:						str						,    )				->					Tuple:

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

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

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







				@property
				def     _snake_case					(							self							:						Any	)				->					Dict:
										__magic_name__            =     self.image_processor.model_input_names
										__magic_name__            =     self.feature_extractor.model_input_names
										return list(dict.fromkeys(image_processor_input_names + feature_extractor_input_names	)	)











"""simple docstring"""

def _lowerCAmelCase	(  __lowerCamelCase:list   ):

						'''simple docstring'''






						__magic_name__            =     len(__lowerCamelCase   )
						for i in range(1 ,						__lowerCamelCase   ):
												__magic_name__            =     collection[i]
												__magic_name__            =     0
												__magic_name__            =     i - 1

												while low <= high:
																		__magic_name__            =     (low + high) // 2
																		if val < collection[mid]:
																								__magic_name__            =     mid - 1
																		else:
																								__magic_name__            =     mid + 1
												for j in range(__lowerCamelCase ,						__lowerCamelCase ,						-1   ):
																		__magic_name__            =     collection[j - 1]
												__magic_name__            =     val
						return collection


if __name__ == "__main__":
			lowercase    			=       input('''Enter numbers separated by a comma:\n''').strip()
			lowercase    			=       [int(item) for item in user_input.split(''',''')]
			print(binary_insertion_sort(unsorted))



