





from __future__ import annotations

from random import choice


def       UpperCamelCase__(			UpperCamelCase__     :			Dict    )->Optional[Any]:
       return choice(UpperCamelCase__    )


def       UpperCamelCase__(			UpperCamelCase__     :			list[int]					,	UpperCamelCase__     :			int    )->int:
       A__		   =		random_pivot(UpperCamelCase__    )

       # partition based on pivot
       # linear time
       A__		   =		[e for e in lst if e < pivot]
       A__		   =		[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()












import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
    ' StableDiffusionInpaintPipeline` instead.'
)





