'''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


__SCREAMING_SNAKE_CASE	:					str					=  """Here is a text containing a lot of information: '''{text}'''.

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

class      lowerCamelCase_     (snake_case__   ):
      '''simple docstring'''

      __UpperCamelCase:  Tuple      =						"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:  List[str]      =						"text_qa"
      __UpperCamelCase:  List[str]      =						AutoTokenizer
      __UpperCamelCase:  str      =						AutoModelForSeqaSeqLM

      __UpperCamelCase:  Dict      =						["text", "text"]
      __UpperCamelCase:  int      =						["text"]




      def 					_A     (	self						:    Union[str, Any]						, A						:    str						, A						:    str	):
             _UpperCAmelCase					:  int											=   QA_PROMPT.format(text=A						, question=A	)
             return self.pre_processor(A						, return_tensors="pt"	)




      def 					_A     (	self						:    Optional[Any]						, A						:    Optional[int]	):
             _UpperCAmelCase					:  Optional[Any]											=   self.model.generate(**A	)

             _UpperCAmelCase				,  _UpperCAmelCase					:  Tuple											=   inputs["input_ids"].shape
             _UpperCAmelCase					:  Optional[int]											=   output_ids.shape[0]

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





      def 					_A     (	self						:    List[Any]						, A						:    List[Any]	):
             return self.pre_processor.decode(A						, skip_special_tokens=A						, clean_up_tokenization_spaces=A	)


'''simple docstring'''




def      UpperCamelCase_							( _UpperCAmelCase  :				Optional[int]      ,     _UpperCAmelCase  :				List[Any]   )   ->   List[str]:


       """simple docstring"""







       if len(str(_UpperCAmelCase   )   ) == 1 or len(str(_UpperCAmelCase   )   ) == 1:
              return a * b

       _UpperCAmelCase					:  Any											=   max(len(str(_UpperCAmelCase   )   )      ,     len(str(_UpperCAmelCase   )   )   )
       _UpperCAmelCase					:  Any											=   ma // 2

       _UpperCAmelCase				,  _UpperCAmelCase					:  Union[str, Any]											=   divmod(_UpperCAmelCase      ,     10**ma   )
       _UpperCAmelCase				,  _UpperCAmelCase					:  int											=   divmod(_UpperCAmelCase      ,     10**ma   )

       _UpperCAmelCase					:  List[str]											=   karatsuba(_UpperCAmelCase      ,     _UpperCAmelCase   )
       _UpperCAmelCase					:  int											=   karatsuba((aa + aa)      ,     (ba + ba)   )
       _UpperCAmelCase					:  Any											=   karatsuba(_UpperCAmelCase      ,     _UpperCAmelCase   )

       return (z * 10 ** (2 * ma)) + ((y - z - x) * 10 ** (ma)) + (x)

def      UpperCamelCase_							( )   ->   List[str]:


       """simple docstring"""







       print(karatsuba(15_463      ,     23_489   )   )


if __name__ == "__main__":
  main()

