




'''simple docstring'''






from typing import TYPE_CHECKING

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


_lowerCAmelCase       =   {'''configuration_regnet''': ['''REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RegNetConfig''']}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCAmelCase       =   [
				    '''REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''RegNetForImageClassification''',
				    '''RegNetModel''',
				    '''RegNetPreTrainedModel''',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCAmelCase       =   [
				    '''TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''TFRegNetForImageClassification''',
				    '''TFRegNetModel''',
				    '''TFRegNetPreTrainedModel''',
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCAmelCase       =   [
				    '''FlaxRegNetForImageClassification''',
				    '''FlaxRegNetModel''',
				    '''FlaxRegNetPreTrainedModel''',
				]


if TYPE_CHECKING:
				from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_regnet import (
								    REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
								    RegNetForImageClassification,
								    RegNetModel,
								    RegNetPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_regnet import (
								    TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFRegNetForImageClassification,
								    TFRegNetModel,
								    TFRegNetPreTrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_regnet import (
								    FlaxRegNetForImageClassification,
								    FlaxRegNetModel,
								    FlaxRegNetPreTrainedModel,
								)


else:
				import sys

				_lowerCAmelCase       =   _LazyModule(__name__, globals()['''__file__'''], _import_structure)









'''simple docstring'''






def      __lowerCAmelCase   (       snake_case__		):

			for insert_index, insert_value in enumerate(collection[1:]		):
						__UpperCamelCase :     Union[str, Any]										=  insert_index
						while insert_index >= 0 and insert_value < collection[insert_index]:
									__UpperCamelCase :     int										=  collection[insert_index]
									insert_index -= 1
						if insert_index != temp_index:
									__UpperCamelCase :     Tuple										=  insert_value
			return collection


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

				testmod()

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



