
def 				a						(							snake_case__:					list					):


				'''simple docstring'''

				def merge(snake_case__:					list						,   snake_case__:					list					) -> list:

								def _merge():
												while left and right:
																yield (left if left[0] <= right[0] else right).pop(0					)
												yield from left
												yield from right

								return list(_merge()					)

				if len(snake_case__					) <= 1:
								return collection
				lowercase_       =					len(snake_case__					) // 2
				return merge(merge_sort(collection[:mid]					)						,   merge_sort(collection[mid:]					)					)


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(*merge_sort(unsorted), sep=',')






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


__a  			=					{'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DeiTConfig', 'DeiTOnnxConfig']}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a  			=					['DeiTFeatureExtractor']
						__a  			=					['DeiTImageProcessor']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a  			=					[
						    'DEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'DeiTForImageClassification',
						    'DeiTForImageClassificationWithTeacher',
						    'DeiTForMaskedImageModeling',
						    'DeiTModel',
						    'DeiTPreTrainedModel',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a  			=					[
						    'TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TFDeiTForImageClassification',
						    'TFDeiTForImageClassificationWithTeacher',
						    'TFDeiTForMaskedImageModeling',
						    'TFDeiTModel',
						    'TFDeiTPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_deit import DeiTFeatureExtractor
												from .image_processing_deit import DeiTImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_deit import (
												    DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DeiTForImageClassification,
												    DeiTForImageClassificationWithTeacher,
												    DeiTForMaskedImageModeling,
												    DeiTModel,
												    DeiTPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_deit import (
												    TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFDeiTForImageClassification,
												    TFDeiTForImageClassificationWithTeacher,
												    TFDeiTForMaskedImageModeling,
												    TFDeiTModel,
												    TFDeiTPreTrainedModel,
												)


else:
						import sys

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




