b2002a8ef80ecbecee09fd61b910c987648455c7,torch_geometric/datasets/karate.py,KarateClub,__init__,#KarateClub#Any#,20

Before Change

        data.num_nodes = edge_index.max().item() + 1
        data.x = torch.eye(data.num_nodes, dtype=torch.float)
        y = [0 if G.nodes[i]["club"] == "Mr. Hi" else 1 for i in G.nodes]
        data.y = torch.tensor(y)
        self.data, self.slices = self.collate([data])

    def _download(self):
        return

After Change

        // Compute communities.
        partition = community_louvain.best_partition(G)
        y = torch.tensor([partition[i] for i in range(G.number_of_nodes())])

        // Select a single training node for each community
        // (we just use the first one).
        train_mask = torch.zeros(y.size(0), dtype=torch.bool)
        for i in range(int(y.max()) + 1):
            train_mask[(y == i).nonzero(as_tuple=False)[0]] = True

        data = Data(x=x, edge_index=edge_index, y=y, train_mask=train_mask)

        self.data, self.slices = self.collate([data])

Instances