code: def _setweights(self):
          
          for name_w in self.weights:
              raw_w = getattr(self.module, name_w + '_raw')
              w = torch.nn.functional.dropout(raw_w, p=self.dropout, training=self.training)
              if hasattr(self.module, name_w):
                  delattr(self.module, name_w)
              setattr(self.module, name_w, w)
docs: Uses pytorch's built-in dropout function to apply dropout to the parameters of
          the wrapped module.
  
          Args:
              None
          Returns:
              None