hugegraph-ml/src/hugegraph_ml/models/seal.py [144:171]:
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    def forward(self, g, z, node_id=None, edge_id=None):
        """
        Args:
            g(DGLGraph): the graph
            z(Tensor): node labeling tensor, shape [N, 1]
            node_id(Tensor, optional): node id tensor, shape [N, 1]
            edge_id(Tensor, optional): edge id tensor, shape [E, 1]
        Returns:
            x(Tensor): output tensor

        """

        z_emb = self.z_embedding(z)

        if self.use_attribute:
            x = self.node_attributes_lookup(node_id)
            x = torch.cat([z_emb, x], 1)
        else:
            x = z_emb

        if self.use_edge_weight:
            edge_weight = self.edge_weights_lookup(edge_id)
        else:
            edge_weight = None

        if self.use_embedding:
            n_emb = self.node_embedding(node_id)
            x = torch.cat([x, n_emb], 1)
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hugegraph-ml/src/hugegraph_ml/models/seal.py [284:307]:
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    def forward(self, g, z, node_id=None, edge_id=None):
        """
        Args:
            g(DGLGraph): the graph
            z(Tensor): node labeling tensor, shape [N, 1]
            node_id(Tensor, optional): node id tensor, shape [N, 1]
            edge_id(Tensor, optional): edge id tensor, shape [E, 1]
        Returns:
            x(Tensor): output tensor
        """
        z_emb = self.z_embedding(z)
        if self.use_attribute:
            x = self.node_attributes_lookup(node_id)
            x = torch.cat([z_emb, x], 1)
        else:
            x = z_emb
        if self.use_edge_weight:
            edge_weight = self.edge_weights_lookup(edge_id)
        else:
            edge_weight = None

        if self.use_embedding:
            n_emb = self.node_embedding(node_id)
            x = torch.cat([x, n_emb], 1)
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