Need advice on training graph algorithms on a heterogenous graph.
I have created a hetero graph with 2 nodes and 1 edge in DGL, all 3 feature tensors associated with them have different shape as follows
user - feature dimension - (3,3)
movie - feature dimension - (3,2)
user-movie - feature dimension - (4,2) . This has one edge with two attributes.
I want to train a GAT on the graph to use the edge attributes along with the node attributes. It seems that the feature input to GAT(in_dim=features.size()) doesn’t allow node features of different dimensions (user has a dimension of 3 and movie has a dimension of 2). How to handle the different node feature dimensions?
The second question is how to pass edge features to GAT?