test.py

     # add this to TestAutograd in test/test_autograd.py
     def test_convbackwardbackward(self):
         v_in = Variable(torch.Tensor([0.1, 0.1]).view(1, 2, 1, 1), requires_grad=True)

         def forward(v_in):
             f1 = lambda x: x * 0.0001
             f2 = torch.nn.Conv2d(2, 1, 1, 1)
             grad_out = Variable(torch.ones(1, 1, 1, 1))
             gradient = torch.autograd.grad(outputs=f2(f1(v_in)), inputs=v_in,
                                      grad_outputs=grad_out,
                                      create_graph=True, retain_graph=True,
                                      only_inputs=True)[0]
             out = gradient.sum()
             return out

         self.assertTrue(gradcheck(forward, [v_in]))