


"""simple docstring"""





from __future__ import annotations

snake_case__		:     Optional[Any]    				=				[-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
snake_case__		:     str    				=				[-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]


def      _snake_case						(						_snake_case				:			list[float]			):
      lowerCAmelCase					:	Union[str, Any]       =   []
      lowerCAmelCase					:	int       =   len(_snake_case			)

      for i in range(_snake_case			):
            lowerCAmelCase					:	float       =   -1
            for j in range(i + 1 ,   _snake_case			):
                  if arr[i] < arr[j]:
                        lowerCAmelCase					:	Union[str, Any]       =   arr[j]
                        break
            result.append(_snake_case			)
      return result


def      _snake_case						(						_snake_case				:			list[float]			):
      lowerCAmelCase					:	Tuple       =   []
      for i, outer in enumerate(_snake_case			):
            lowerCAmelCase					:	float       =   -1
            for inner in arr[i + 1 :]:
                  if outer < inner:
                        lowerCAmelCase					:	Optional[Any]       =   inner
                        break
            result.append(_snake_case			)
      return result


def      _snake_case						(						_snake_case				:			list[float]			):
      lowerCAmelCase					:	Dict       =   len(_snake_case			)
      lowerCAmelCase					:	list[float]       =   []
      lowerCAmelCase					:	list[float]       =   [-1] * arr_size

      for index in reversed(range(_snake_case			)			):
            if stack:
                  while stack[-1] <= arr[index]:
                        stack.pop()
                        if not stack:
                              break
            if stack:
                  lowerCAmelCase					:	Optional[int]       =   stack[-1]
            stack.append(arr[index]			)
      return result


if __name__ == "__main__":
 from doctest import testmod
 from timeit import timeit

 testmod()
 print(next_greatest_element_slow(arr))
 print(next_greatest_element_fast(arr))
 print(next_greatest_element(arr))

 snake_case__		:     Optional[Any]    				=				(
     '''from __main__ import arr, next_greatest_element_slow, '''
     '''next_greatest_element_fast, next_greatest_element'''
 )
 print(
     '''next_greatest_element_slow():''',
     timeit('''next_greatest_element_slow(arr)''', setup=setup),
 )
 print(
     '''next_greatest_element_fast():''',
     timeit('''next_greatest_element_fast(arr)''', setup=setup),
 )
 print(
     '''     next_greatest_element():''',
     timeit('''next_greatest_element(arr)''', setup=setup),
 )







"""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



class 		snake_case_(       a__			):
     __UpperCamelCase  =					'''philschmid/bart-large-cnn-samsum'''
     __UpperCamelCase  =					(
         '''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.'''
     )
     __UpperCamelCase  =					'''summarizer'''
     __UpperCamelCase  =					AutoTokenizer
     __UpperCamelCase  =					AutoModelForSeqaSeqLM

     __UpperCamelCase  =					['''text''']
     __UpperCamelCase  =					['''text''']






     def      lowerCamelCase__     (	self  :					Dict					,				UpperCamelCase_  :					int				):
           return self.pre_processor(UpperCamelCase_					,				return_tensors='''pt'''					,				truncation=UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					Optional[int]					,				UpperCamelCase_  :					str				):
           return self.model.generate(**UpperCamelCase_				)[0]






     def      lowerCamelCase__     (	self  :					Any					,				UpperCamelCase_  :					Tuple				):
           return self.pre_processor.decode(UpperCamelCase_					,				skip_special_tokens=UpperCamelCase_					,				clean_up_tokenization_spaces=UpperCamelCase_				)


