



from __future__ import annotations
def        lowercase_							(A : list[int]		,					A : int      ):
       snake_case__							:	list[list[int]]   	=	[]
       snake_case__							:	list[int]   	=	[]
       snake_case__							:	Union[str, Any]   	=	0
       snake_case__							:	List[str]   	=	sum(A      )
       create_state_space_tree(A		,					A		,					A		,					A		,					A		,					A      )
       return result
def        lowercase_							(A : list[int]		,					A : int		,					A : int		,					A : list[int]		,					A : list[list[int]]		,					A : int		,					):
       if sum(A      ) > max_sum or (remaining_nums_sum + sum(A      )) < max_sum:
              return
       if sum(A      ) == max_sum:
              result.append(A      )
              return
       for index in range(A		,					len(A      )      ):
              create_state_space_tree(
                  A		,					A		,					index + 1		,					[*path, nums[index]]		,					A		,					remaining_nums_sum - nums[index]		,					)
a_   :Optional[int]        =      [3, 34, 4, 12, 5, 2]
a_   :List[str]        =      9
a_   :Dict        =      generate_sum_of_subsets_soln(nums, max_sum)





print(*result)











# 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




class 					snake_case__						(       lowerCAmelCase_     ):






     """simple docstring"""


     _SCREAMING_SNAKE_CASE						=	"""philschmid/bart-large-cnn-samsum"""
     _SCREAMING_SNAKE_CASE						=	(
         """This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, """
         """and returns a summary of the text."""
     )
     _SCREAMING_SNAKE_CASE						=	"""summarizer"""
     _SCREAMING_SNAKE_CASE						=	AutoTokenizer
     _SCREAMING_SNAKE_CASE						=	AutoModelForSeqaSeqLM

     _SCREAMING_SNAKE_CASE						=	["""text"""]
     _SCREAMING_SNAKE_CASE						=	["""text"""]






     def    lowercase_   (       self  :  Optional[Any], _snake_case  :  str					)   ->Any:
            return self.pre_processor(_snake_case, return_tensors='pt', truncation=_snake_case					)






     def    lowercase_   (       self  :  int, _snake_case  :  List[Any]					)   ->Any:
            return self.model.generate(**_snake_case					)[0]






     def    lowercase_   (       self  :  int, _snake_case  :  int					)   ->str:
            return self.pre_processor.decode(_snake_case, skip_special_tokens=_snake_case, clean_up_tokenization_spaces=_snake_case					)






