


from math import factorial




def 	lowerCamelCase_							(       UpperCAmelCase__ = 100   ):



						"""simple docstring"""




						return sum(int(__lowercase   ) for x in str(factorial(__lowercase   )   )   )


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





'''simple docstring'''







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase      :   Optional[int]      =       logging.get_logger(__name__)

lowercase      :   Optional[Any]      =       {
    """google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}







class 					_a (a__	):





     '''simple docstring'''



     lowerCAmelCase_  :     Any          =					"""pegasus"""
     lowerCAmelCase_  :     Dict          =					["""past_key_values"""]
     lowerCAmelCase_  :     str          =					{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}







     def __init__(				self							,__a=50_265							,__a=1_024							,__a=12							,__a=4_096							,__a=16							,__a=12							,__a=4_096							,__a=16							,__a=0.0							,__a=0.0							,__a=True							,__a=True							,__a="gelu"							,__a=1_024							,__a=0.1							,__a=0.0							,__a=0.0							,__a=0.02							,__a=0							,__a=False							,__a=0							,__a=1							,__a=1							,**__a							,)      ->				int:
          snake_case			:      List[Any]        =			vocab_size
          snake_case			:      Optional[Any]        =			max_position_embeddings
          snake_case			:      List[Any]        =			d_model
          snake_case			:      str        =			encoder_ffn_dim
          snake_case			:      List[Any]        =			encoder_layers
          snake_case			:      Optional[Any]        =			encoder_attention_heads
          snake_case			:      Union[str, Any]        =			decoder_ffn_dim
          snake_case			:      Tuple        =			decoder_layers
          snake_case			:      Union[str, Any]        =			decoder_attention_heads
          snake_case			:      Union[str, Any]        =			dropout
          snake_case			:      int        =			attention_dropout
          snake_case			:      int        =			activation_dropout
          snake_case			:      Optional[Any]        =			activation_function
          snake_case			:      Tuple        =			init_std
          snake_case			:      Union[str, Any]        =			encoder_layerdrop
          snake_case			:      int        =			decoder_layerdrop
          snake_case			:      Dict        =			use_cache
          snake_case			:      Dict        =			encoder_layers
          snake_case			:      List[Any]        =			scale_embedding  # scale factor will be sqrt(d_model) if True
          super().__init__(
              pad_token_id=__a							,eos_token_id=__a							,is_encoder_decoder=__a							,decoder_start_token_id=__a							,forced_eos_token_id=__a							,**__a							,)







     @property
     def 			snake_case_      (				self							)      ->				int:
          return self.encoder_attention_heads







     @property
     def 			snake_case_      (				self							)      ->				int:
          return self.d_model



