Method gcn

python/dgl/transforms/module.py:1844–1863

(self, g)

        return feat_list

    def gcn(self, g):
        feat_list = []
        with g.local_scope():
            if self.eweight_name is None:
                eweight_name = "w"
                if eweight_name in g.edata:
                    g.edata.pop(eweight_name)
            else:
                eweight_name = self.eweight_name

            transform = GCNNorm(eweight_name=eweight_name)
            transform(g)

            for _ in range(self.k):
                g.update_all(
                    fn.u_mul_e(self.in_feat_name, eweight_name, "m"),
                    fn.sum("m", self.in_feat_name),
                )
                feat_list.append(g.ndata[self.in_feat_name])
        return feat_list

    def ppr(self, g):
        feat_list = []