


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

class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							Optional[int]					  =  ["image_processor", "tokenizer"]
							__UpperCAmelCase   :							Optional[int]					  =  "AutoImageProcessor"
							__UpperCAmelCase   :							int					  =  "AutoTokenizer"

							def __init__(							self	:  List[Any]   ,     lowerCamelCase	:  List[Any]   ,     lowerCamelCase	:  str    )     ->   List[str]:
														super().__init__(lowerCamelCase   ,     lowerCamelCase    )
														__snake_case		:      Union[str, Any]										=       self.image_processor

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

														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		:      Any										=       self.tokenizer(lowerCamelCase   ,     return_tensors=lowerCamelCase   ,     **lowerCamelCase    )

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

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

							def    __snake_case (							self	:  int   ,     *lowerCamelCase	:  int   ,     **lowerCamelCase	:  Any    )     ->   List[Any]:
														return self.tokenizer.batch_decode(*lowerCamelCase   ,     **lowerCamelCase    )

							def    __snake_case (							self	:  Union[str, Any]   ,     *lowerCamelCase	:  Dict   ,     **lowerCamelCase	:  List[str]    )     ->   Tuple:
														return self.tokenizer.decode(*lowerCamelCase   ,     **lowerCamelCase    )






							@property
							def    __snake_case (							self	:  List[str]    )     ->   Tuple:
														return ["input_ids", "attention_mask", "pixel_values"]





def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase     ):
							return x if y == 0 else greatest_common_divisor(__lowerCamelCase							,     x % y     )







def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase     ):
							return (x * y) // greatest_common_divisor(__lowerCamelCase							,     __lowerCamelCase     )







def     lowerCAmelCase_					( __lowerCamelCase = 2_0     ):
							__snake_case		:      Optional[Any]										=       1
							for i in range(1							,     n + 1     ):
														__snake_case		:      Any										=       lcm(__lowerCamelCase							,     __lowerCamelCase     )
							return g


if __name__ == "__main__":
			print(f'''{solution() = }''')

