


'''simple docstring'''



def       _UpperCamelCase (						UpperCamelCase__   ):
			for i in range(len(UpperCamelCase__   ) - 1	, 0	, -1   ):
						UpperCAmelCase__					:   Dict       				=       False

						for j in range(UpperCamelCase__	, 0	, -1   ):
									if unsorted[j] < unsorted[j - 1]:
												UpperCAmelCase__				,    UpperCAmelCase__					:   str       				=       unsorted[j - 1], unsorted[j]
												UpperCAmelCase__					:   List[str]       				=       True

						for j in range(UpperCamelCase__   ):
									if unsorted[j] > unsorted[j + 1]:
												UpperCAmelCase__				,    UpperCAmelCase__					:   List[str]       				=       unsorted[j + 1], unsorted[j]
												UpperCAmelCase__					:   Optional[int]       				=       True

						if not swapped:
									break
			return unsorted


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		__A		=input('Enter numbers separated by a comma:\n').strip()
		__A		=[int(item) for item in user_input.split(',')]
		print(f"""{cocktail_shaker_sort(unsorted) = }""")



'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A		={
    'configuration_table_transformer': [
        'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TableTransformerConfig',
        'TableTransformerOnnxConfig',
    ]
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__A		=[
		    'TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TableTransformerForObjectDetection',
		    'TableTransformerModel',
		    'TableTransformerPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_table_transformer import (
		    TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    TableTransformerConfig,
		    TableTransformerOnnxConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_table_transformer import (
				    TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TableTransformerForObjectDetection,
				    TableTransformerModel,
				    TableTransformerPreTrainedModel,
				)

else:
		import sys

		__A		=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)