

"""simple docstring"""






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


__lowerCAmelCase				      =   '''Here is a text containing a lot of information: \'\'\'{text}\'\'\'.

Can you answer this question about the text: \'{question}\''''
class 	_lowerCAmelCase    (      UpperCamelCase_       ):
							__lowerCAmelCase					:    Any     =  '''google/flan-t5-base'''
							__lowerCAmelCase					:    Optional[Any]     =  (
							    '''This is a tool that answers questions related to a text. It takes two arguments named `text`, which is the '''
							    '''text where to find the answer, and `question`, which is the question, and returns the answer to the question.'''
							)
							__lowerCAmelCase					:    Union[str, Any]     =  '''text_qa'''
							__lowerCAmelCase					:    Any     =  AutoTokenizer
							__lowerCAmelCase					:    Union[str, Any]     =  AutoModelForSeqaSeqLM

							__lowerCAmelCase					:    Optional[Any]     =  ['''text''', '''text''']
							__lowerCAmelCase					:    Optional[int]     =  ['''text''']

							def 					_lowerCAmelCase  ( self       :    Optional[int] ,		a       :    Any ,		a       :    Optional[Any]    )   ->    Union[str, Any]:

									"""simple docstring"""
									lowercase										=							QA_PROMPT.format(text=__a ,		question=__a    )
									return self.pre_processor(__a ,		return_tensors='''pt'''    )

							def 					_lowerCAmelCase  ( self       :    Dict ,		a       :    Any    )   ->    Optional[Any]:

									"""simple docstring"""
									lowercase										=							self.model.generate(**__a    )

									lowercase										=							inputs['input_ids'].shape
									lowercase										=							output_ids.shape[0]

									return output_ids.reshape(__a ,		out_b // in_b ,		*output_ids.shape[1:]    )[0][0]

							def 					_lowerCAmelCase  ( self       :    Tuple ,		a       :    str    )   ->    Tuple:

									"""simple docstring"""
									return self.pre_processor.decode(__a ,		skip_special_tokens=__a ,		clean_up_tokenization_spaces=__a    )







'''simple docstring'''






def 							_SCREAMING_SNAKE_CASE	(					)     ->			int:







   """simple docstring"""

   for a in range(3_00	):
      for b in range(a + 1	,		4_00	):
         for c in range(b + 1	,		5_00	):
            if (a + b + c) == 10_00 and (a**2) + (b**2) == (c**2):
               return a * b * c

   return -1




def 							_SCREAMING_SNAKE_CASE	(					)     ->			int:







   """simple docstring"""

   for a in range(3_00	):
      for b in range(4_00	):
         __snake_case					:   Optional[Any]  				=			10_00 - a - b
         if a < b < c and (a**2) + (b**2) == (c**2):
            return a * b * c

   return -1




def 							_SCREAMING_SNAKE_CASE	(					)     ->			None:







   """simple docstring"""
   import timeit

   print(
       timeit.timeit('solution()'	,		setup='from __main__ import solution'	,		number=10_00	)	)
   print(
       timeit.timeit(
           'solution_fast()'	,		setup='from __main__ import solution_fast'	,		number=10_00	)	)


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