455a0dc9a98212089a7201a025670c33a1770f67,torch_geometric/nn/functional/spline_gcn_test.py,SplineGcnTest,test_backward,#SplineGcnTest#,92

Before Change

        vertices = [[0, 0], [1, 1], [-2, 2], [-3, -3], [4, -4]]
        edges = [[0, 0, 0, 0], [1, 2, 3, 4]]
        adj = mesh_adj(torch.FloatTensor(vertices), torch.LongTensor(edges))
        features = torch.FloatTensor([[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]])
        weight = torch.arange(0.5, 0.5 * 25, step=0.5).view(12, 2, 1)

        features_in = Variable(features, requires_grad=True)
        weight = Variable(weight, requires_grad=True)

        features_out = spline_gcn(
            adj,
            features_in,
            weight,
            kernel_size=[3, 4],
            max_radius=sqrt(16 + 16),
            degree=1)

        features_out.mean().backward()

        print(features_in.grad.size())

After Change

                max_radius=sqrt(16 + 16),
                degree=1)

        test = gradcheck(op, (features, weight), eps=1e-6, atol=1e-4)
        self.assertTrue(test)

Instances