As discussed in PR #369 , I adapted GINConv.
I tried different things with batching but could not get it to work in gradient computation and training.
Something like:
function (l::GINConv)(tg::TemporalSnapshotsGNNGraph, x::AbstractVector)
tg = MLUtils.batch(tg.snapshots)
x = reduce(hcat,x)
x = l(tg, x)
x = reshape(x,:, Int.(tg.num_nodes/tg.num_graphs), tg.num_graphs)
return MLUtils.unbatch(x)
end
function (l::GINConv)(tg::TemporalSnapshotsGNNGraph)
tg = MLUtils.batch(tg.snapshots)
tg = l(tg)
return MLUtils.unbatch(tg) #in this case unbatch was not working on GPU
end
If it is ok, a PR will follow to update the documentation.
As discussed in PR #369 , I adapted
GINConv
. I tried different things with batching but could not get it to work in gradient computation and training. Something like:If it is ok, a PR will follow to update the documentation.