

from __future__ import annotations

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  Optional[int] )   ->       Optional[Any]:
				if len(_lowerCAmelCase ) == 0:
								return []
				_UpperCAmelCase		,							_UpperCAmelCase       :		List[Any] 		=    min(_lowerCAmelCase ), max(_lowerCAmelCase )
				_UpperCAmelCase       :		List[Any] 		=    int(max_value - min_value ) + 1
				_UpperCAmelCase       :		Union[str, Any] 		=    [[] for _ in range(_lowerCAmelCase )]

				for i in my_list:
								buckets[int(i - min_value )].append(_lowerCAmelCase )

				return [v for bucket in buckets for v in sorted(_lowerCAmelCase )]


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

					testmod()
					assert bucket_sort([4, 5, 3, 2, 1]) == [1, 2, 3, 4, 5]
					assert bucket_sort([0, 1, -10, 15, 2, -2]) == [-10, -2, 0, 1, 2, 15]





import warnings

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


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

class 				a  (	UpperCAmelCase				):


						def __init__(       self						,					*A_						,					**A_	):







										'''simple docstring'''


										warnings.warn(
										    "The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
										    " Please use DeformableDetrImageProcessor instead."						,					A_						,					)
										super().__init__(*A_						,					**A_	)


