
"""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


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

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



class  lowercase				(   lowercase__		):
			lowercase			     =    '''google/flan-t5-base'''
			lowercase			     =    (
			    '''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.'''
			)
			lowercase			     =    '''text_qa'''
			lowercase			     =    AutoTokenizer
			lowercase			     =    AutoModelForSeqaSeqLM

			lowercase			     =    ['''text''', '''text''']
			lowercase			     =    ['''text''']






			def 				UpperCAmelCase       (self     :  Optional[int]			,SCREAMING_SNAKE_CASE_     :  str			,SCREAMING_SNAKE_CASE_     :  str )					->  Optional[int]:





				"""simple docstring"""


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






			def 				UpperCAmelCase       (self     :  Any			,SCREAMING_SNAKE_CASE_     :  Optional[int] )					->  Union[str, Any]:





				"""simple docstring"""


				lowerCAmelCase				       =     self.model.generate(**SCREAMING_SNAKE_CASE_ )

				lowerCAmelCase       ,					lowerCAmelCase				       =     inputs['''input_ids'''].shape
				lowerCAmelCase				       =     output_ids.shape[0]

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






			def 				UpperCAmelCase       (self     :  List[Any]			,SCREAMING_SNAKE_CASE_     :  str )					->  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"""






def __magic_name__  (							_lowerCamelCase:		int,				_lowerCamelCase:		int )				->	int:

	'''simple docstring'''




	lowerCAmelCase				       =     1.0
	for i in range(1,				r + 1 ):
		ret *= (n + 1 - i) / i
	return round(_lowerCamelCase )




def __magic_name__  (							_lowerCamelCase:		int )				->	int:

	'''simple docstring'''




	return choose(8 + n,				_lowerCamelCase ) + choose(9 + n,				_lowerCamelCase ) - 10




def __magic_name__  (							_lowerCamelCase:		int )				->	int:

	'''simple docstring'''




	return sum(non_bouncy_exact(_lowerCamelCase ) for i in range(1,				n + 1 ) )




def __magic_name__  (							_lowerCamelCase:		int = 100 )				->	int:

	'''simple docstring'''




	return non_bouncy_upto(_lowerCamelCase )


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


