



'''simple docstring'''







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


SCREAMING_SNAKE_CASE__     : Optional[int]				=   '''Here is a text containing a lot of information: \'\'\'{text}\'\'\'.

Can you answer this question about the text: \'{question}\''''




class 				__lowerCAmelCase(							__a      ):
			__snake_case  :		Tuple		=      'google/flan-t5-base'
			__snake_case  :		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.'
			)
			__snake_case  :		List[Any]		=      'text_qa'
			__snake_case  :		List[str]		=      AutoTokenizer
			__snake_case  :		Optional[int]		=      AutoModelForSeqaSeqLM

			__snake_case  :		List[str]		=      ['text', 'text']
			__snake_case  :		Dict		=      ['text']






			def 				_lowercase	(   self  :							List[str]      ,       SCREAMING_SNAKE_CASE  :							str      ,       SCREAMING_SNAKE_CASE  :							List[Any]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Dict										=      QA_PROMPT.format(text=SCREAMING_SNAKE_CASE__      ,       question=SCREAMING_SNAKE_CASE__	)
					return self.pre_processor(SCREAMING_SNAKE_CASE__      ,       return_tensors='pt'	)






			def 				_lowercase	(   self  :							Optional[Any]      ,       SCREAMING_SNAKE_CASE  :							List[str]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      self.model.generate(**SCREAMING_SNAKE_CASE__	)

					SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:Tuple										=      inputs['input_ids'].shape
					SCREAMING_SNAKE_CASE_						:Tuple										=      output_ids.shape[0]

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






			def 				_lowercase	(   self  :							Optional[Any]      ,       SCREAMING_SNAKE_CASE  :							Optional[Any]	):




					"""simple docstring"""







					return self.pre_processor.decode(SCREAMING_SNAKE_CASE__      ,       skip_special_tokens=SCREAMING_SNAKE_CASE__      ,       clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__	)



"""simple docstring"""




from __future__ import annotations



def 						UpperCAmelCase__ (					A__						,     A__						,     A__						,     A__ )   ->   None:




   """simple docstring"""
   lowerCamelCase__       ,							lowerCamelCase__						       =      m - 1, 0
   while i >= 0 and j < n:
      if key == mat[i][j]:
         print(f'Key {key} found at row- {i + 1} column- {j + 1}' )
         return
      if key < mat[i][j]:
         i -= 1
      else:
         j += 1
   print(f'Key {key} not found' )



def 						UpperCAmelCase__ (					)   ->   None:




   """simple docstring"""
   lowerCamelCase__						       =      [[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
   lowerCamelCase__						       =      int(input("Enter the element to be searched:" ) )
   print(A__ )
   search_in_a_sorted_matrix(A__						,     len(A__ )						,     len(mat[0] )						,     A__ )


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()




