


from __future__ import annotations






def 							__lowercase       (			__lowerCAmelCase							:    list[int]       ):
							if len(__lowerCAmelCase       ) == 0:
														return array

							a__				, a__					=					min(__lowerCAmelCase       ), max(__lowerCAmelCase       )

							# Compute the variables
							a__					=					_max - _min + 1
							a__				, a__					=					[0] * holes_range, [0] * holes_range

							# Make the sorting.
							for i in array:
														a__					=					i - _min
														a__					=					i
														holes_repeat[index] += 1

							# Makes the array back by replacing the numbers.
							a__					=					0
							for i in range(__lowerCAmelCase       ):
														while holes_repeat[i] > 0:
																					a__					=					holes[i]
																					index += 1
																					holes_repeat[i] -= 1

    # Returns the sorted array.
							return array


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			snake_case							:	List[str]					      =				input('''Enter numbers separated by comma:\n''')
			snake_case							:	Optional[Any]					      =				[int(x) for x in user_input.split(''',''')]
			print(pigeon_sort(unsorted))








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case							:	Optional[int]					      =				{
    '''configuration_clipseg''': [
        '''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPSegConfig''',
        '''CLIPSegTextConfig''',
        '''CLIPSegVisionConfig''',
    ],
    '''processing_clipseg''': ['''CLIPSegProcessor'''],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							:	List[str]					      =				[
						    '''CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''CLIPSegModel''',
						    '''CLIPSegPreTrainedModel''',
						    '''CLIPSegTextModel''',
						    '''CLIPSegVisionModel''',
						    '''CLIPSegForImageSegmentation''',
						]

if TYPE_CHECKING:
						from .configuration_clipseg import (
						    CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    CLIPSegConfig,
						    CLIPSegTextConfig,
						    CLIPSegVisionConfig,
						)
						from .processing_clipseg import CLIPSegProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_clipseg import (
												    CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
												    CLIPSegForImageSegmentation,
												    CLIPSegModel,
												    CLIPSegPreTrainedModel,
												    CLIPSegTextModel,
												    CLIPSegVisionModel,
												)

else:
						import sys

						snake_case							:	Optional[int]					      =				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




