How to create a sparse autoencoder neural network with pytorch

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This code doesnt run in Pytorch 1.1.0! I keep getting the backward() needs to return two values not 1!
Edit :
You need to return None for any arguments that you do not need the gradients. so the L1Penalty would be :

import torch
from torch.autograd import Function

class L1Penalty(Function):

    @staticmethod
    def forward(ctx, input, l1weight):
        ctx.save_for_backward(input)
        ctx.l1weight = l1weight
        return input

    @staticmethod
    def backward(ctx, grad_output):
        input, = ctx.saved_variables
        grad_input = input.clone().sign().mul(self.l1weight)
        grad_input += grad_output
        return grad_input, None