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When training on multiple small graphs, typically one batches several graphs together into a larger graph for efficiency.
This operation is called blockdiag in SparseArrays and LightGraphs.jl.
For FeaturedGraphs, node and edge features should be vertically concatenated in the resulting graph. I'm not sure how we should handle global features, maybe we should just require them to be == nothing for all graphs as a start
The text was updated successfully, but these errors were encountered:
When training on multiple small graphs, typically one batches several graphs together into a larger graph for efficiency.
This operation is called blockdiag in SparseArrays and LightGraphs.jl.
For
FeaturedGraph
s, node and edge features should be vertically concatenated in the resulting graph. I'm not sure how we should handle global features, maybe we should just require them to be== nothing
for all graphs as a startThe text was updated successfully, but these errors were encountered: