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))

    x = torch.randn((num_nodes, in_channels))

    conv = ARMAConv(
        in_channels, out_channels, num_stacks, num_layers, dropout=0.25)

After Change

    conv = ARMAConv(16, 32, num_stacks=8, num_layers=4)
    assert conv.__repr__() == "ARMAConv(16, 32, num_stacks=8, num_layers=4)"
    out = conv(x, edge_index)
    assert out.size() == (4, 32)
    assert conv(x, adj.t()).tolist() == out.tolist()

    t = "(Tensor, Tensor, OptTensor) -> Tensor"

Instances