

"""simple docstring"""






import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


__lowerCamelCase										=		logging.get_logger(__name__)
class        _lowercase					(     __UpperCAmelCase     ):







     def __init__(      self ,						*UpperCamelCase_ ,						**UpperCamelCase_       ):
      warnings.warn(
          '''The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
          ''' Please use DeformableDetrImageProcessor instead.''' ,						UpperCamelCase_ ,						)
      super().__init__(*UpperCamelCase_ ,						**UpperCamelCase_       )




"""simple docstring"""






from __future__ import annotations

from random import choice





def 	lowercase      (   __UpperCamelCase						) ->      Any:
 return choice(__UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      int:
 __magic_name__     =      random_pivot(__UpperCamelCase						)

 # partition based on pivot
 # linear time
 __magic_name__     =      [e for e in lst if e < pivot]
 __magic_name__     =      [e for e in lst if e > pivot]

 # if we get lucky, pivot might be the element we want.
 # we can easily see this:
 # small (elements smaller than k)
 # + pivot (kth element)
 # + big (elements larger than k)
 if len(__UpperCamelCase						) == k - 1:
  return pivot
 # pivot is in elements bigger than k
 elif len(__UpperCamelCase						) < k - 1:
  return kth_number(__UpperCamelCase      ,   k - len(__UpperCamelCase						) - 1						)
 # pivot is in elements smaller than k
 else:
  return kth_number(__UpperCamelCase      ,   __UpperCamelCase						)


if __name__ == "__main__":
 import doctest

 doctest.testmod()

