



'''simple docstring'''

def     __UpperCamelCase					(				_lowercase = 100       )			->      int:
	_lowercase       :							List[str]  	=		1
	_lowercase       :							Optional[Any]  	=		0
	for i in range(1,					num + 1       ):
		fact *= i

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

	return result


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


import torch

from accelerate import Accelerator, DistributedType







class 	A__				:






				def __enter__(		self   : Optional[Any]  ):






							'''simple docstring'''







							if self.enabled:
										lowerCAmelCase__ : Any   =						self.model.no_sync()
										self.model_sync_obj.__enter__()

							return self






				def __exit__(		self   : int       ,	a   : int       ,	a   : Optional[Any]       ,	a   : str  ):






							'''simple docstring'''







							if self.enabled:
										# Average all models on exit
										self._sync_and_avg_model_params()
										self.model_sync_obj.__exit__(a       ,	a       ,	a  )






				def __init__(		self   : List[str]       ,	a   : Accelerator       ,	a   : torch.nn.Module       ,	a   : int       ,	a   : bool = True  ):






							'''simple docstring'''







							if accelerator.distributed_type not in [
							    DistributedType.NO,
							    DistributedType.MULTI_CPU,
							    DistributedType.MULTI_GPU,
							]:
										raise NotImplementedError('LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)'  )
							lowerCAmelCase__ : Union[str, Any]   =						enabled and accelerator.distributed_type != DistributedType.NO
							lowerCAmelCase__ : str   =						0
							if self.enabled:
										lowerCAmelCase__ : Dict   =						accelerator
										lowerCAmelCase__ : Dict   =						model
										lowerCAmelCase__ : Optional[int]   =						local_sgd_steps






				def 				_lowerCamelCase						(		self   : Optional[Any]  ):






							'''simple docstring'''







							self.num_steps += 1
							if not self.enabled:
										return

							if self.num_steps % self.local_sgd_steps == 0:
										self._sync_and_avg_model_params()






				def 				_lowerCamelCase						(		self   : int  ):






							'''simple docstring'''







							self.accelerator.wait_for_everyone()
							with self.accelerator.autocast():
										for param in self.model.parameters():
													lowerCAmelCase__ : Dict   =						self.accelerator.reduce(param.data       ,	reduction='mean'  )