

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

class 				a  (	UpperCAmelCase				):
						_lowercase    						=			["image_processor", "tokenizer"]
						_lowercase    						=			"AutoImageProcessor"
						_lowercase    						=			"AutoTokenizer"


						def __init__(       self						,					A_						,					A_	):







										'''simple docstring'''


										super().__init__(A_						,					A_	)
										_UpperCAmelCase       :		int 		=    self.image_processor


						def __call__(       self						,					A_=None						,					A_=None						,					A_=None						,					**A_	):







										'''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:
														_UpperCAmelCase       :		Optional[int] 		=    self.tokenizer(A_						,					return_tensors=A_						,					**A_	)

										if images is not None:
														_UpperCAmelCase       :		List[Any] 		=    self.image_processor(A_						,					return_tensors=A_						,					**A_	)

										if text is not None and images is not None:
														_UpperCAmelCase       :		List[Any] 		=    image_features.pixel_values
														return encoding
										elif text is not None:
														return encoding
										else:
														return BatchEncoding(data=dict(**A_	)						,					tensor_type=A_	)


						def        _UpperCAmelCase				(       self						,					*A_						,					**A_	):







										'''simple docstring'''


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


						def        _UpperCAmelCase				(       self						,					*A_						,					**A_	):







										'''simple docstring'''


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





						@property
						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


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





def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  str  ,      lowerCAmelCase:  str )   ->       int:
				if len(lowerCAmelCase ) != len(lowerCAmelCase ):
								raise ValueError("String lengths must match!" )

				_UpperCAmelCase       :		List[Any] 		=    0

				for chara, chara in zip(lowerCAmelCase  ,      lowerCAmelCase ):
								if chara != chara:
												count += 1

				return count


if __name__ == "__main__":
					import doctest

					doctest.testmod()


