b48c943b9f6248dbdd42d0fce44658b937098372,torch_geometric/nn/functional/spline_gcn.py,,spline_gcn,#Any#Any#Any#Any#Any#Any#Any#,9

Before Change

    // Convolution via sparse row sum. Converts [|E| x M_out] feature matrix to
    // [n x M_out] feature matrix.
    size = torch.Size([adj.size(0), adj.size(1), output.size(1)])
    adj = torch.sparse.FloatTensor(indices, output, size)
    output = sum(adj, dim=1)

    // TODO: root node and weight mean
    // root_weight = weight[torch.arange(kernel_size[-1])]
    // root_weight.mean(0)

After Change

    zero = torch.zeros(adj.size(1), output.size(1))
    zero = zero.cuda() if output.is_cuda else zero
    zero = Variable(zero) if not torch.is_tensor(output) else zero
    row = row.view(-1, 1).expand(row.size(0), output.size(1))
    output = zero.scatter_add_(0, row, output)

    // Weighten root node features by multiplying with the meaned weights at the
    // origin.
    index = torch.arange(0, kernel_size[-1]).long()

Instances