






"""simple docstring"""






def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__				):
				return 1 if input_a == input_a else 0



def  __lowerCamelCase					(					):
				assert xnor_gate(0       ,0				) == 1
				assert xnor_gate(0       ,1				) == 0
				assert xnor_gate(1       ,0				) == 0
				assert xnor_gate(1       ,1				) == 1


if __name__ == "__main__":
					print(xnor_gate(0, 0))
					print(xnor_gate(0, 1))
					print(xnor_gate(1, 0))
					print(xnor_gate(1, 1))










"""simple docstring"""






from ...processing_utils import ProcessorMixin





class       snake_case_       (    _lowerCamelCase       ):



	"""simple docstring"""

	SCREAMING_SNAKE_CASE_:							Union[str, Any]   			=					["""image_processor""", """feature_extractor"""]
	SCREAMING_SNAKE_CASE_:							Optional[int]   			=					"""TvltImageProcessor"""
	SCREAMING_SNAKE_CASE_:							Optional[int]   			=					"""TvltFeatureExtractor"""


	def __init__(      self  ,					__a  ,					__a						):


					"""simple docstring"""

					super().__init__(image_processor=__a  ,					feature_extractor=__a						)

					A__							 =       image_processor
					A__							 =       feature_extractor


	def __call__(      self  ,					__a=None  ,					__a=None  ,					__a=None  ,					__a=None  ,					__a=False  ,					__a=False  ,					*__a  ,					**__a  ,					):


					"""simple docstring"""

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

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

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






	@property
	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.image_processor.model_input_names
					A__							 =       self.feature_extractor.model_input_names
					return list(dict.fromkeys(image_processor_input_names + feature_extractor_input_names						)						)


