code: def forward(self, x):
          
          self.noise.normal_()
          return self.layers(th.cat([x, self.noise], 1))
docs: Pass data through the net structure.
  
          :param x: input data: shape (:,1)
          :type x: torch.Variable
          :return: output of the shallow net
          :rtype: torch.Variable