



"""simple docstring"""

from typing import TYPE_CHECKING

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


A_	:						List[str]				=			{'configuration_regnet': ['REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RegNetConfig']}

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

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

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_	:						int				=			[
							    '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

							A_	:						Union[str, Any]				=			_LazyModule(__name__, globals()['__file__'], _import_structure)










"""simple docstring"""

def    __snake_case       (  __A			:	int = 100    )    ->					int:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE	:       Any 							=    1
				SCREAMING_SNAKE_CASE	:       Optional[int] 							=    0
				for i in range(1       ,		num + 1    ):
								fact *= i

				for j in str(__A    ):
								result += int(__A    )

				return result


if __name__ == "__main__":
							print(solution(int(input('Enter the Number: ').strip())))





