def  snake_case						(__lowercase						)	->	int:

      '''simple docstring'''



      return 1 if digit in (0, 1) else (digit * factorial(digit - 1						))
def  snake_case						(__lowercase						)	->	bool:

      '''simple docstring'''



      _snake_case						:					Any    =   0
      _snake_case						:					int    =   number
      while duplicate > 0:
            _snake_case    ,_snake_case						:					List[Any]    =   divmod(_UpperCamelCase ,      10						)
            fact_sum += factorial(_UpperCamelCase						)
      return fact_sum == number


if __name__ == "__main__":
    print('Program to check whether a number is a Krisnamurthy Number or not.')
    __SCREAMING_SNAKE_CASE						:   Optional[int]         =			int(input('Enter number: ').strip())
    print(
        F'''{number} is {'' if krishnamurthy(number) else 'not '}a Krishnamurthy Number.'''
    )
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__SCREAMING_SNAKE_CASE						:   Optional[Any]         =			{
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE						:   Union[str, Any]         =			[
				    'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'AutoformerForPrediction',
				    'AutoformerModel',
				    'AutoformerPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_autoformer import (
				    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    AutoformerConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_autoformer import (
								    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    AutoformerForPrediction,
								    AutoformerModel,
								    AutoformerPreTrainedModel,
								)

else:
				import sys

				__SCREAMING_SNAKE_CASE						:   str         =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)