Can the default implementation of GCN in DGL tutorial handle heterogeneous graph

I was looking into this tutorial:

It appears this GCN implementation can only handle a homogenous graph. Is this understanding correct?

Secondly, is there a GCN implementation available with DGL that can handle heterogeneous graphs?

Hi, the GCN-for-heterograph is actually relational graph convolutional network (RGCN). We have two implementations:

Thanks @minjie.

Can you please elaborate what’s the difference between this two implementations Which one would you recommend using?

Generally, if your graph has many relations and node types (e.g., >100), I will recommend the first implementation. The second one will be more efficient if your graph has few relations and node types.

I would use this for graph classification and it would have quite large. So sounds like I should use the first implementation.

Thanks, @minjie for the feedback.