



from __future__ import annotations
def        lowercase_							(A : int		,					A : int      ):
       snake_case__							:	list[list[int]]   	=	[]
       create_all_state(1		,					A		,					A		,					[]		,					A      )
       return result
def        lowercase_							(A : int		,					A : int		,					A : int		,					A : list[int]		,					A : list[list[int]]		,					):
       if level == 0:
              total_list.append(current_list[:]      )
              return

       for i in range(A		,					total_number - level + 2      ):
              current_list.append(A      )
              create_all_state(i + 1		,					A		,					level - 1		,					A		,					A      )
              current_list.pop()
def        lowercase_							(A : list[list[int]]      ):
       for i in total_list:
              print(*A      )


if __name__ == "__main__":
 a_   :Optional[Any]        =      4
 a_   :str        =      2
 a_   :int        =      generate_all_combinations(n, k)
 print_all_state(total_list)











# 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					)






