Using GCN as encoder alone for multiple small graph data. about pygcn HOT 2 OPEN

There are many ways to batch operations for multiple graphs. If all graphs are of the same size and not very large (and you don't care about sparsity), then stacking the adjacency matrices along a third axis might result in a simpler implementation (using batched matrix multiplications or tensor products). If you'd like to use sparse matrix multiplications, then you are confined to 2D matrices (as currently there are no sparse tensor ops for higher order tensors in PyTorch, or any other framework), and the blog-diagonal construction scheme is the most straightforward in this case. Lastly, you can represent graphs as edge lists and construct your own scatter/gather operations (using PyTorch's scatter function). This gives you the highest flexibility in constructing GCNs/GNNs, but is a bit more tricky to implement.

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Thanks for your suggestion for helping me understand these implementation details!

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