




import warnings

from ...utils import logging
from .image_processing_conditional_detr import ConditionalDetrImageProcessor


_lowerCAmelCase    : str		= logging.get_logger(__name__)
class       _UpperCamelCase   (					lowerCAmelCase		):
      def __init__(      self :Union[str, Any]			,   *lowerCamelCase :Dict			,   **lowerCamelCase :Optional[Any]   )  ->      None:
       warnings.warn(
           "The class ConditionalDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
           " Please use ConditionalDetrImageProcessor instead."			,   lowerCamelCase			,   )
       super().__init__(*lowerCamelCase			,   **lowerCamelCase   )











def     lowerCAmelCase		(		_lowerCAmelCase				: Tuple    ,				_lowerCAmelCase				: Tuple						):




 """simple docstring"""







 sequence.append(_lowerCAmelCase						)

 UpperCAmelCase__							=    0
 while sequence[index] != target:
  index += 1

 sequence.pop()

 if index == len(_lowerCAmelCase						):
  return None

 return index


if __name__ == "__main__":
  _lowerCAmelCase    : List[Any]		= input("Enter numbers separated by comma:\n").strip()
  _lowerCAmelCase    : Dict		= [int(item) for item in user_input.split(",")]

  _lowerCAmelCase    : Optional[Any]		= input("Enter a single number to be found in the list:\n")
  _lowerCAmelCase    : Tuple		= int(target_input)
  _lowerCAmelCase    : int		= sentinel_linear_search(sequence, target)
  if result is not None:
    print(F'''{target} found at positions: {result}''')
  else:
    print("Not found")





