
'''simple docstring'''





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


A							     = "Here is a text containing a lot of information: '''{text}'''.\n\nCan you answer this question about the text: '{question}'"



class 			lowerCAmelCase__ (							UpperCamelCase							):



  '''simple docstring'''






  _UpperCamelCase							=			'google/flan-t5-base'
  _UpperCamelCase							=			(
      '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.'
  )
  _UpperCamelCase							=			'text_qa'
  _UpperCamelCase							=			AutoTokenizer
  _UpperCamelCase							=			AutoModelForSeqaSeqLM

  _UpperCamelCase							=			['text', 'text']
  _UpperCamelCase							=			['text']

  def 		_lowerCamelCase						(self	:			Union[str, Any]						,			lowerCAmelCase_	:			str						,			lowerCAmelCase_	:			str     ) ->							int:
        snake_case_    							=				QA_PROMPT.format(text=lowerCAmelCase_						,			question=lowerCAmelCase_     )
        return self.pre_processor(lowerCAmelCase_						,			return_tensors="pt"     )

  def 		_lowerCamelCase						(self	:			Any						,			lowerCAmelCase_	:			Any     ) ->							Tuple:
        snake_case_    							=				self.model.generate(**lowerCAmelCase_     )

        snake_case_							,						snake_case_    							=				inputs["input_ids"].shape
        snake_case_    							=				output_ids.shape[0]

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


  def 		_lowerCamelCase						(self	:			List[str]						,			lowerCAmelCase_	:			Tuple     ) ->							Tuple:
        return self.pre_processor.decode(lowerCAmelCase_						,			skip_special_tokens=lowerCAmelCase_						,			clean_up_tokenization_spaces=lowerCAmelCase_     )




def      UpperCAmelCase__							(     _A :					Optional[int]      , _A :					Optional[int]				):





  '''simple docstring'''







  sequence.append(_A				)

  a__    =0
  while sequence[index] != target:
    index += 1

  sequence.pop()

  if index == len(_A				):
    return None

  return index


if __name__ == "__main__":
       lowerCamelCase 	=   input('''Enter numbers separated by comma:\n''').strip()
       lowerCamelCase 	=   [int(item) for item in user_input.split(''',''')]

       lowerCamelCase 	=   input('''Enter a single number to be found in the list:\n''')
       lowerCamelCase 	=   int(target_input)
       lowerCamelCase 	=   sentinel_linear_search(sequence, target)
       if result is not None:
              print(f"""{target} found at positions: {result}""")
       else:
              print('''Not found''')
