cf1cc19bb79ae4128ef5437279de475835374a46,benchmark/runtime/dgl/rgcn.py,BaseRGCN,forward,#BaseRGCN#Any#,182

Before Change

    def forward(self, g):
        if self.features is not None:
            g.ndata["id"] = self.features
        for layer in self.layers:
            layer(g)
        return g.ndata.pop("h")


class EntityClassify(BaseRGCN):

After Change

        self.conv2 = RGCNConv(g, 16, out_channels, num_relations, num_bases=30)

    def forward(self, x):
        x = F.relu(self.conv1(None))
        x = self.conv2(x)
        return F.log_softmax(x, dim=1)


class RGCNSPMVConv(torch.nn.Module):

Instances