






'''simple docstring'''
from typing import Callable, Optional, Union

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


a_					=	logging.get_logger(__name__)

a_					=	{
    'microsoft/xprophetnet-large-wiki100-cased': (
        'https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'
    ),
}






class        __SCREAMING_SNAKE_CASE (     lowerCamelCase			):
 snake_case_												=							"""xlm-prophetnet"""
 snake_case_												=							["""past_key_values"""]
 snake_case_												=							{
     """num_attention_heads""": """num_encoder_attention_heads""",
 }




 def __init__( self		:							List[Any]   , __lowercase		:							Optional[float] = 0.1   , __lowercase		:							Optional[Union[str, Callable]] = "gelu"   , __lowercase		:							Optional[int] = 3_05_22   , __lowercase		:							Optional[int] = 10_24   , __lowercase		:							Optional[int] = 40_96   , __lowercase		:							Optional[int] = 12   , __lowercase		:							Optional[int] = 16   , __lowercase		:							Optional[int] = 40_96   , __lowercase		:							Optional[int] = 12   , __lowercase		:							Optional[int] = 16   , __lowercase		:							Optional[float] = 0.1   , __lowercase		:							Optional[float] = 0.1   , __lowercase		:							Optional[int] = 5_12   , __lowercase		:							Optional[float] = 0.02   , __lowercase		:							Optional[bool] = True   , __lowercase		:							Optional[bool] = True   , __lowercase		:							Optional[int] = 0   , __lowercase		:							Optional[int] = 2   , __lowercase		:							Optional[int] = 32   , __lowercase		:							Optional[int] = 1_28   , __lowercase		:							Optional[bool] = False   , __lowercase		:							Optional[float] = 0.0   , __lowercase		:							Optional[bool] = True   , __lowercase		:							Optional[int] = 0   , __lowercase		:							Optional[int] = 1   , __lowercase		:							Optional[int] = 2   , **__lowercase		:							Dict   , )		->  Any:
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=vocab_size
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=hidden_size
       SCREAMING_SNAKE_CASE__       :			Tuple													=encoder_ffn_dim
       SCREAMING_SNAKE_CASE__       :			str													=num_encoder_layers
       SCREAMING_SNAKE_CASE__       :			List[str]													=num_encoder_attention_heads
       SCREAMING_SNAKE_CASE__       :			str													=decoder_ffn_dim
       SCREAMING_SNAKE_CASE__       :			Tuple													=num_decoder_layers
       SCREAMING_SNAKE_CASE__       :			Tuple													=num_decoder_attention_heads
       SCREAMING_SNAKE_CASE__       :			Dict													=max_position_embeddings
       SCREAMING_SNAKE_CASE__       :			Any													=init_std  # Normal(0, this parameter)
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=activation_function

       # parameters for xlmprophetnet
       SCREAMING_SNAKE_CASE__       :			Dict													=ngram
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=num_buckets
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=relative_max_distance
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=disable_ngram_loss
       SCREAMING_SNAKE_CASE__       :			str													=eps

       # 3 Types of Dropout
       SCREAMING_SNAKE_CASE__       :			Any													=attention_dropout
       SCREAMING_SNAKE_CASE__       :			Any													=activation_dropout
       SCREAMING_SNAKE_CASE__       :			List[str]													=dropout

       SCREAMING_SNAKE_CASE__       :			Dict													=use_cache

       super().__init__(
           pad_token_id=__lowercase   , bos_token_id=__lowercase   , eos_token_id=__lowercase   , is_encoder_decoder=__lowercase   , add_cross_attention=__lowercase   , decoder_start_token_id=__lowercase   , **__lowercase   , )




 @property
 def        __magic_name__		( self		:							str )		->  int:
       return self.num_encoder_layers + self.num_decoder_layers




 @num_hidden_layers.setter
 def        __magic_name__		( self		:							int   , __lowercase		:							List[Any] )		->  List[str]:
       raise NotImplementedError(
           '''This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'''
           ''' `num_decoder_layers`.''' )







'''simple docstring'''
from math import factorial





def 	_a(					UpperCamelCase__			:  int = 1_0_0							):




      '''simple docstring'''






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


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