


"""simple docstring"""





from torch import nn



class 		snake_case_(       nn.Module			):






     def __init__(	self  :					int					,				UpperCamelCase_  :					int					,				UpperCamelCase_  :					int				):
           super().__init__()
           lowerCAmelCase					:	str       =   class_size
           lowerCAmelCase					:	Dict       =   embed_size
           # self.mlp1 = nn.Linear(embed_size, embed_size)
           # self.mlp2 = (nn.Linear(embed_size, class_size))
           lowerCAmelCase					:	Any       =   nn.Linear(UpperCamelCase_					,				UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					List[Any]					,				UpperCamelCase_  :					Tuple				):
           # hidden_state = nn.functional.relu(self.mlp1(hidden_state))
           # hidden_state = self.mlp2(hidden_state)
           lowerCAmelCase					:	int       =   self.mlp(UpperCamelCase_				)
           return logits






"""simple docstring"""





def      _snake_case						(						_snake_case				:			float ,   _snake_case				:			list[float]			):
      if discount_rate < 0:
            raise ValueError('''Discount rate cannot be negative'''			)
      if not cash_flows:
            raise ValueError('''Cash flows list cannot be empty'''			)
      lowerCAmelCase					:	List[str]       =   sum(
          cash_flow / ((1 + discount_rate) ** i) for i, cash_flow in enumerate(_snake_case			)			)
      return round(_snake_case ,   ndigits=2			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()


