




'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_SCREAMING_SNAKE_CASE			=						{
    '''configuration_mobilenet_v2''': [
        '''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileNetV2Config''',
        '''MobileNetV2OnnxConfig''',
    ],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_SCREAMING_SNAKE_CASE			=						['''MobileNetV2FeatureExtractor''']
							_SCREAMING_SNAKE_CASE			=						['''MobileNetV2ImageProcessor''']


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_SCREAMING_SNAKE_CASE			=						[
							    '''MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''MobileNetV2ForImageClassification''',
							    '''MobileNetV2ForSemanticSegmentation''',
							    '''MobileNetV2Model''',
							    '''MobileNetV2PreTrainedModel''',
							    '''load_tf_weights_in_mobilenet_v2''',
							]


if TYPE_CHECKING:
							from .configuration_mobilenet_va import (
							    MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    MobileNetVaConfig,
							    MobileNetVaOnnxConfig,
							)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
														from .image_processing_mobilenet_va import MobileNetVaImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mobilenet_va import (
														    MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MobileNetVaForImageClassification,
														    MobileNetVaForSemanticSegmentation,
														    MobileNetVaModel,
														    MobileNetVaPreTrainedModel,
														    load_tf_weights_in_mobilenet_va,
														)


else:
							import sys

							_SCREAMING_SNAKE_CASE			=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)








def 			lowerCAmelCase__					(     a__:						list			)    ->						list:


							'''simple docstring'''





							if len(a__			) < 2:
														return collection

							def circle_sort_util(a__:						list     ,    a__:						int     ,    a__:						int			) -> bool:
														_UpperCAmelCase											=     False

														if low == high:
																					return swapped

														_UpperCAmelCase											=     low
														_UpperCAmelCase											=     high

														while left < right:
																					if collection[left] > collection[right]:
																												_UpperCAmelCase						,			_UpperCAmelCase											=     (
																												    collection[right],
																												    collection[left],
																												)
																												_UpperCAmelCase											=     True

																					left += 1
																					right -= 1

														if left == right and collection[left] > collection[right + 1]:
																					_UpperCAmelCase						,			_UpperCAmelCase											=     (
																					    collection[right + 1],
																					    collection[left],
																					)

																					_UpperCAmelCase											=     True

														_UpperCAmelCase											=     low + int((high - low) / 2			)
														_UpperCAmelCase											=     circle_sort_util(a__     ,    a__     ,    a__			)
														_UpperCAmelCase											=     circle_sort_util(a__     ,    mid + 1     ,    a__			)

														return swapped or left_swap or right_swap

							_UpperCAmelCase											=     True

							while is_not_sorted is True:
														_UpperCAmelCase											=     circle_sort_util(a__     ,    0     ,    len(a__			) - 1			)

							return collection


if __name__ == "__main__":
		lowerCAmelCase__    :Tuple       =				input('''Enter numbers separated by a comma:\n''').strip()
		lowerCAmelCase__    :List[str]       =				[int(item) for item in user_input.split(''',''')]
		print(circle_sort(unsorted))
