

def 			_lowercase    (      __UpperCamelCase     :		str ):


      if not isinstance(_A   ,       _A ):
            snake_case__					=   F'''Input value of [number={number}] must be an integer'''
            raise TypeError(_A )
      if number < 0 or number % 2 == 1:
            return False
      snake_case__					=   int(number**0.5 )
      return number == number_sqrt * (number_sqrt + 1)


if __name__ == "__main__":
       import doctest

       doctest.testmod()









# 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


lowerCAmelCase						:   List[Any]										=    '''Here is a text containing a lot of information: \'\'\'{text}\'\'\'.

Can you answer this question about the text: \'{question}\''''
class     SCREAMING_SNAKE_CASE__     (						__a		):





       '''simple docstring'''




       UpperCamelCase__ :     int				    =       '''google/flan-t5-base'''
       UpperCamelCase__ :     int				    =       (
           '''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__ :     Tuple				    =       '''text_qa'''
       UpperCamelCase__ :     Tuple				    =       AutoTokenizer
       UpperCamelCase__ :     List[Any]				    =       AutoModelForSeqaSeqLM

       UpperCamelCase__ :     Optional[Any]				    =       ['''text''', '''text''']
       UpperCamelCase__ :     Any				    =       ['''text''']

       def UpperCAmelCase_						(						self       :						Tuple    ,		lowerCAmelCase__       :						str    ,		lowerCAmelCase__       :						str							)			->    List[Any]:
             snake_case__					=   QA_PROMPT.format(text=lowerCAmelCase__    ,		question=lowerCAmelCase__							)
             return self.pre_processor(lowerCAmelCase__    ,		return_tensors="""pt"""							)

       def UpperCAmelCase_						(						self       :						Optional[Any]    ,		lowerCAmelCase__       :						Dict							)			->    List[Any]:
             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 UpperCAmelCase_						(						self       :						Union[str, Any]    ,		lowerCAmelCase__       :						Dict							)			->    List[Any]:
             return self.pre_processor.decode(lowerCAmelCase__    ,		skip_special_tokens=lowerCAmelCase__    ,		clean_up_tokenization_spaces=lowerCAmelCase__							)






