


# 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 			SCREAMING_SNAKE_CASE__  (    lowercase__      ):
      snake_case__    :					List[Any]					       =						'''philschmid/bart-large-cnn-samsum'''
      snake_case__    :					Tuple					       =						(
          '''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.'''
      )
      snake_case__    :					Optional[int]					       =						'''summarizer'''
      snake_case__    :					int					       =						AutoTokenizer
      snake_case__    :					Dict					       =						AutoModelForSeqaSeqLM

      snake_case__    :					Optional[Any]					       =						['''text''']
      snake_case__    :					int					       =						['''text''']
      def 	SCREAMING_SNAKE_CASE							(	self    :	List[str]					,							SCREAMING_SNAKE_CASE__    :	Optional[int]					)		->      Tuple:
             return self.pre_processor(SCREAMING_SNAKE_CASE__					,							return_tensors='pt'					,							truncation=SCREAMING_SNAKE_CASE__					)
      def 	SCREAMING_SNAKE_CASE							(	self    :	List[Any]					,							SCREAMING_SNAKE_CASE__    :	Union[str, Any]					)		->      Tuple:
             return self.model.generate(**SCREAMING_SNAKE_CASE__					)[0]

      def 	SCREAMING_SNAKE_CASE							(	self    :	Union[str, Any]					,							SCREAMING_SNAKE_CASE__    :	str					)		->      int:
             return self.pre_processor.decode(SCREAMING_SNAKE_CASE__					,							skip_special_tokens=SCREAMING_SNAKE_CASE__					,							clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__					)






def 	SCREAMING_SNAKE_CASE_						(      __A			:      list    )     ->		list:

       """simple docstring"""

       a_ :		int							=  len(__A    )
       for _ in range(__A    ):
              for i in range(_ % 2  ,   arr_size - 1  ,   2    ):
                     if arr[i + 1] < arr[i]:
                            a_							,		a_ :		int							=  arr[i + 1], arr[i]

       return arr


if __name__ == "__main__":
   UpperCAmelCase_				:			int   =	list(range(10, 0, -1))
   print(F'Original: {arr}. Sorted: {odd_even_transposition(arr)}')


