7b4892781e2198ad99a8655da03133505619040a,test/nn/conv/test_arma_conv.py,,test_arma_conv,#,5

Before Change

def test_arma_conv():
    in_channels, out_channels = (16, 32)
    num_stacks, num_layers = 8, 4
    edge_index = torch.tensor([[0, 0, 0, 1, 2, 3], [1, 2, 3, 0, 0, 0]])
    num_nodes = edge_index.max().item() + 1
    edge_weight = torch.rand(edge_index.size(1))

After Change

    jit = torch.jit.script(conv.jittable(t))
    assert jit(x, edge_index).tolist() == out.tolist()

    t = "(Tensor, SparseTensor, OptTensor) -> Tensor"
    jit = torch.jit.script(conv.jittable(t))
    assert torch.allclose(conv(x, adj.t()), out, atol=1e-6)

Instances