534a10d60d3c5a356c8121f9b3c53f49cf873f96,torch_geometric/transforms/gdc.py,GDC,diffusion_matrix_approx,#GDC#Any#Any#Any#Any#Any#,257

Before Change

                // (except for errors due to approximation).
                diag_idx = torch.arange(0, num_nodes, dtype=torch.long,
                                        device=edge_index.device)
                diag_idx = diag_idx.unsqueeze(0).repeat(2, 1)

                D_vec_sqrt = torch.sqrt(D_vec_orig)
                edge_index, edge_weight = spspmm(diag_idx, D_vec_sqrt,
                                                 edge_index, edge_weight,
                                                 num_nodes, num_nodes,
                                                 num_nodes)
                D_vec_invsqrt = 1 / D_vec_sqrt
                edge_index, edge_weight = spspmm(edge_index, edge_weight,
                                                 diag_idx, D_vec_invsqrt,
                                                 num_nodes, num_nodes,
                                                 num_nodes)
            elif normalization in ["col", "row"]:
                pass
            else:
                raise ValueError(

After Change

                // Since we use the original degrees for this it will be like
                // we had used symmetric normalization from the beginning
                // (except for errors due to approximation).
                row, col = edge_index
                deg_inv = deg.sqrt()
                deg_inv_sqrt = deg.pow(-0.5)
                deg_inv_sqrt[deg_inv_sqrt == float("inf")] = 0

Instances