"""simple docstring"""




import warnings

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

class       a_      (     __UpperCamelCase			):
					UpperCamelCase_ :	Union[str, Any]			=    ["image_processor", "tokenizer"]
					UpperCamelCase_ :	List[Any]			=    "CLIPImageProcessor"
					UpperCamelCase_ :	Union[str, Any]			=    ("XLMRobertaTokenizer", "XLMRobertaTokenizerFast")




					def __init__(	self						:     List[str]  ,						snake_case__						:     str=None  ,						snake_case__						:     Any=None  ,						**snake_case__						:     List[Any]     ):
							lowerCAmelCase__        =   None
							if "feature_extractor" in kwargs:
									warnings.warn(
									    """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
									    """ instead."""  ,						snake_case__  ,						)
									lowerCAmelCase__        =   kwargs.pop("""feature_extractor"""     )

							lowerCAmelCase__        =   image_processor if image_processor is not None else feature_extractor
							if image_processor is None:
									raise ValueError("""You need to specify an `image_processor`."""     )
							if tokenizer is None:
									raise ValueError("""You need to specify a `tokenizer`."""     )

							super().__init__(snake_case__  ,						snake_case__     )




					def __call__(	self						:     List[str]  ,						snake_case__						:     List[str]=None  ,						snake_case__						:     Optional[Any]=None  ,						snake_case__						:     int=None  ,						**snake_case__						:     Optional[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:
									lowerCAmelCase__        =   self.tokenizer(snake_case__  ,						return_tensors=snake_case__  ,						**snake_case__     )

							if images is not None:
									lowerCAmelCase__        =   self.image_processor(snake_case__  ,						return_tensors=snake_case__  ,						**snake_case__     )

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




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Dict  ,						*snake_case__						:     int  ,						**snake_case__						:     Optional[Any]     ):
							return self.tokenizer.batch_decode(*snake_case__  ,						**snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[int]  ,						*snake_case__						:     Dict  ,						**snake_case__						:     List[str]     ):
							return self.tokenizer.decode(*snake_case__  ,						**snake_case__     )




					@property
					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[int]     ):
							lowerCAmelCase__        =   self.tokenizer.model_input_names
							lowerCAmelCase__        =   self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names     )     )





"""simple docstring"""




from math import pi, sqrt







def 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




		if num <= 0:
				raise ValueError("""math domain error"""     )
		if num > 1_71.5:
				raise OverflowError("""math range error"""     )
		elif num - int(lowerCamelCase__     ) not in (0, 0.5):
				raise NotImplementedError("""num must be an integer or a half-integer"""     )
		elif num == 0.5:
				return sqrt(lowerCamelCase__     )
		else:
				return 1.0 if num == 1 else (num - 1) * gamma(num - 1     )







def 							_UpperCAmelCase		(       ):





		"""simple docstring"""




		assert gamma(0.5     ) == sqrt(lowerCamelCase__     )
		assert gamma(1     ) == 1.0
		assert gamma(2     ) == 1.0


if __name__ == "__main__":
			from doctest import testmod

			testmod()
			__lowerCAmelCase    :							Dict													=						1.0
			while num:
						__lowerCAmelCase    :							Any													=						float(input("Gamma of: "))
						print(F"gamma({num}) = {gamma(num)}")
						print("\nEnter 0 to exit...")




