

'''simple docstring'''



from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool



class lowerCamelCase			(  lowercase_						):



			'''simple docstring'''






			__snake_case        =	'philschmid/bart-large-cnn-samsum'
			__snake_case        =	(
			    'This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, '
			    'and returns a summary of the text.'
			)
			__snake_case        =	'summarizer'
			__snake_case        =	AutoTokenizer
			__snake_case        =	AutoModelForSeqaSeqLM

			__snake_case        =	['text']
			__snake_case        =	['text']


			def lowercase__						(				self	:						Tuple		,      lowerCAmelCase_	:						List[str]			)      ->		Optional[int]:





									'''simple docstring'''
									return self.pre_processor(lowerCAmelCase_		,      return_tensors="""pt"""		,      truncation=lowerCAmelCase_			)


			def lowercase__						(				self	:						Tuple		,      lowerCAmelCase_	:						Optional[int]			)      ->		Optional[Any]:





									'''simple docstring'''
									return self.model.generate(**lowerCAmelCase_			)[0]



			def lowercase__						(				self	:						Union[str, Any]		,      lowerCAmelCase_	:						List[str]			)      ->		List[Any]:





									'''simple docstring'''
									return self.pre_processor.decode(lowerCAmelCase_		,      skip_special_tokens=lowerCAmelCase_		,      clean_up_tokenization_spaces=lowerCAmelCase_			)




'''simple docstring'''



def 						__lowerCamelCase	(       __snake_case					:		int	)	->							bool:






						"""simple docstring"""





						if p < 2:
												raise ValueError("""p should not be less than 2!"""	)
						elif p == 2:
												return True

						A__					:       Any     =4
						A__					:       int     =(1 << p) - 1
						for _ in range(p - 2	):
												A__					:       Dict     =((s * s) - 2) % m
						return s == 0


if __name__ == "__main__":
		print(lucas_lehmer_test(7))
		print(lucas_lehmer_test(11))

