code: # 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 typing import TYPE_CHECKING
  
  from ..utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
  )
  
  
  _SCREAMING_SNAKE_CASE   						=    {
      """agents""": ["""Agent""", """AzureOpenAiAgent""", """HfAgent""", """LocalAgent""", """OpenAiAgent"""],
      """base""": ["""PipelineTool""", """RemoteTool""", """Tool""", """launch_gradio_demo""", """load_tool"""],
  }
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _SCREAMING_SNAKE_CASE   						=    ["""DocumentQuestionAnsweringTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""ImageCaptioningTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""ImageQuestionAnsweringTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""ImageSegmentationTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""SpeechToTextTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""TextClassificationTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""TextQuestionAnsweringTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""TextSummarizationTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""TextToSpeechTool"""]
       _SCREAMING_SNAKE_CASE   						=    ["""TranslationTool"""]
  
  if TYPE_CHECKING:
       from .agents import Agent, AzureOpenAiAgent, HfAgent, LocalAgent, OpenAiAgent
       from .base import PipelineTool, RemoteTool, Tool, launch_gradio_demo, load_tool
  
       try:
            if not is_torch_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .document_question_answering import DocumentQuestionAnsweringTool
            from .image_captioning import ImageCaptioningTool
            from .image_question_answering import ImageQuestionAnsweringTool
            from .image_segmentation import ImageSegmentationTool
            from .speech_to_text import SpeechToTextTool
            from .text_classification import TextClassificationTool
            from .text_question_answering import TextQuestionAnsweringTool
            from .text_summarization import TextSummarizationTool
            from .text_to_speech import TextToSpeechTool
            from .translation import TranslationTool
  else:
       import sys
  
       _SCREAMING_SNAKE_CASE   						=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
style_context: def 				__lowercase	(						lowerCamelCase__ ,				lowerCamelCase__					)				->Optional[int]:
  
    '''simple docstring'''
  
  
  
  
    sequence.append(lowerCamelCase__					)
  
    a__     		=     0
    while sequence[index] != target:
      index += 1
  
    sequence.pop()
  
    if index == len(lowerCamelCase__					):
      return None
  
    return index
  
  
  if __name__ == "__main__":
       _SCREAMING_SNAKE_CASE   						=    input("""Enter numbers separated by comma:\n""").strip()
       _SCREAMING_SNAKE_CASE   						=    [int(item) for item in user_input.split(""",""")]
  
       _SCREAMING_SNAKE_CASE   						=    input("""Enter a single number to be found in the list:\n""")
       _SCREAMING_SNAKE_CASE   						=    int(target_input)
       _SCREAMING_SNAKE_CASE   						=    sentinel_linear_search(sequence, target)
       if result is not None:
            print(F"""{target} found at positions: {result}""")
       else:
            print("""Not found""")
  
  