ba8de5d0776da82a0f57b710f9648539555164c8,test/nn/conv/test_x_conv.py,,test_x_conv,#,5

Before Change

def test_x_conv():
    in_channels, out_channels = (16, 32)
    edge_index = torch.tensor([[0, 0, 0, 1, 2, 3], [1, 2, 3, 0, 0, 0]])
    num_nodes = edge_index.max().item() + 1
    x = torch.randn((num_nodes, in_channels))
    pos = torch.rand((num_nodes, 3))

    conv = XConv(in_channels, out_channels, dim=3, kernel_size=2, dilation=2)

After Change

    out1 = conv(x, pos)
    assert out1.size() == (8, 32)

    torch.manual_seed(12345)
    out2 = conv(x, pos, batch)
    assert out2.size() == (8, 32)

    jit = torch.jit.script(conv)

Instances