

from torch import nn




class   UpperCamelCase			(  nn.Module ):

    def __init__(      self			:   Any				,     snake_case__			:   List[Any]				,     snake_case__			:   Tuple     ):

     """simple docstring"""






     super().__init__()
     SCREAMING_SNAKE_CASE		    =      class_size
     SCREAMING_SNAKE_CASE		    =      embed_size
     # self.mlp1 = nn.Linear(embed_size, embed_size)
     # self.mlp2 = (nn.Linear(embed_size, class_size))
     SCREAMING_SNAKE_CASE		    =      nn.Linear(snake_case__				,     snake_case__     )




    def UpperCamelCase      (      self			:   Union[str, Any]				,     snake_case__			:   Optional[int]     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      self.mlp(snake_case__     )
     return logits




def 							__lowerCAmelCase     (							_UpperCamelCase		:	List[str]=2_81_23						)		->				str:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      [1] * (limit + 1)

 for i in range(2		,				int(limit**0.5						) + 1						):
  sum_divs[i * i] += i
  for k in range(i + 1		,				limit // i + 1						):
   sum_divs[k * i] += k + i

 SCREAMING_SNAKE_CASE		    =      set()
 SCREAMING_SNAKE_CASE		    =      0

 for n in range(1		,				limit + 1						):
  if sum_divs[n] > n:
   abundants.add(_UpperCamelCase						)

  if not any((n - a in abundants) for a in abundants						):
   res += n

 return res


if __name__ == "__main__":
      print(solution())

