


from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class      UpperCamelCase(	_a ):
					snake_case_		:					Union[str, Any]    					=						["""image_processor""", """tokenizer"""]
					snake_case_		:					List[Any]    					=						"""AutoImageProcessor"""
					snake_case_		:					int    					=						"""AutoTokenizer"""


					def __init__(    self						:		str  ,     SCREAMING_SNAKE_CASE						:		Union[str, Any]  ,     SCREAMING_SNAKE_CASE						:		str    )      ->						Tuple:




											'''simple docstring'''

											super().__init__(SCREAMING_SNAKE_CASE  ,     SCREAMING_SNAKE_CASE    )
											__snake_case				=		self.image_processor


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




											'''simple docstring'''

											if text is None and images is None:
																	raise ValueError("You have to specify either text or images. Both cannot be none."    )

											if text is not None:
																	__snake_case				=		self.tokenizer(SCREAMING_SNAKE_CASE  ,     return_tensors=SCREAMING_SNAKE_CASE  ,     **SCREAMING_SNAKE_CASE    )

											if images is not None:
																	__snake_case				=		self.image_processor(SCREAMING_SNAKE_CASE  ,     return_tensors=SCREAMING_SNAKE_CASE  ,     **SCREAMING_SNAKE_CASE    )

											if text is not None and images is not None:
																	__snake_case				=		image_features.pixel_values
																	return encoding
											elif text is not None:
																	return encoding
											else:
																	return BatchEncoding(data=dict(**SCREAMING_SNAKE_CASE    )  ,     tensor_type=SCREAMING_SNAKE_CASE    )


					def 				SCREAMING_SNAKE_CASE_	(    self						:		Tuple  ,     *SCREAMING_SNAKE_CASE						:		Optional[int]  ,     **SCREAMING_SNAKE_CASE						:		Optional[Any]    )      ->						Optional[int]:




											'''simple docstring'''

											return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE  ,     **SCREAMING_SNAKE_CASE    )


					def 				SCREAMING_SNAKE_CASE_	(    self						:		Dict  ,     *SCREAMING_SNAKE_CASE						:		Any  ,     **SCREAMING_SNAKE_CASE						:		Optional[int]    )      ->						str:




											'''simple docstring'''

											return self.tokenizer.decode(*SCREAMING_SNAKE_CASE  ,     **SCREAMING_SNAKE_CASE    )






					@property
					def 				SCREAMING_SNAKE_CASE_	(    self						:		Optional[int]    )      ->						Optional[int]:




											'''simple docstring'''

											return ["input_ids", "attention_mask", "pixel_values"]









import baseaa





def 						_lowerCAmelCase							(     _lowerCAmelCase			)    ->						bytes:


						'''simple docstring'''






						return baseaa.baaencode(string.encode("utf-8"			)			)





def 						_lowerCAmelCase							(     _lowerCAmelCase			)    ->						str:


						'''simple docstring'''






						return baseaa.baadecode(_lowerCAmelCase			).decode("utf-8"			)


if __name__ == "__main__":
	A				:       Dict      =  'Hello World!'
	A				:       Any      =  baseaa_encode(test)
	print(encoded)

	A				:       Optional[int]      =  baseaa_decode(encoded)
	print(decoded)





