Firstly, I wanted to thank all of you for creating this wonderful library for Graph computations. I am working on link prediction task with RGCNs involving a heterogeneous network with 3 kinds of nodes and several kinds of relationships between the nodes. I am closely following two examples to achieve my goal:
My first question is whether in the rgcn-hetero example if it is possible for node attributes for each node type to have different dimensions? (are there any tutorials for this?)
Secondly, I am trying to write my own model class LinkPredict with heterographs similar to example 1 but by modifying example 2 which has a EntityClassify task. If I understand this correctly, I would need to modify the Input 2 Hidden (i2h) layer to take into account different input node attribute sizes for my 3 different node types. Currently it seems to me that in_feat is common for ALL node types?
Sorry if my questions are a little naive. I’m just starting out with DGL. Many thanks!