`GNNExplainer` for link prediction

❓ Questions & Help

Hi @rusty1s,

I wrote a GNN model by pytorch geometric to do the link prediction which refers to this example. The forward part of the model is showed below. I tried to use GNNExplainer to explain my model but got an error forward() got an unexpected keyword argument 'edge_index'. Since my forward doesn’t directly use edge_index, this might cause the issue. Is it possible that I can have an example to use GNNExplainer for link prediction? Or some instructions to modify the GNNExplainer for my model? Thank you!

    def forward(self, x, adjs, link, n_id):
        for i, (edge_index, _, size) in enumerate(adjs):
            x_target = x[:size[1]]  # Target nodes are always placed first.
            x = self.convs[i]((x, x_target), edge_index)
            if i != self.num_layers - 1:
                x = F.relu(x)
                x = F.dropout(x, p=self.dropout_p, training=self.training)

        x = x[[list(np.where(n_id.numpy()==i.numpy())[0])[0] for i in link[:,0]]] * x[[list(np.where(n_id.numpy()==i.numpy())[0])[0] for i in link[:,1]]]
        x = torch.sigmoid(self.lin(x)).squeeze(1)

        return x

[Alec-Stashevsky]

I would also like to put in a vote for adding link-prediction functionality to the GNNExplainer class!

[rusty1s]

Noted 😃 Let’s see what we can do!