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Resolve gradient bug for GatedGraphConv #250

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Merged
merged 1 commit into from
Nov 18, 2021
Merged

Resolve gradient bug for GatedGraphConv #250

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8 changes: 5 additions & 3 deletions src/layers/conv.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -324,13 +324,15 @@ function (ggc::GatedGraphConv)(fg::FeaturedGraph, H::AbstractMatrix{S}) where {T
@assert (m <= ggc.out_ch) "number of input features must less or equals to output features."
adj = adjacency_list(fg)
if m < ggc.out_ch
Hpad = similar(H, S, ggc.out_ch - m, n)
H = vcat(H, fill!(Hpad, 0))
Hpad = Zygote.ignore() do
fill!(similar(H, S, ggc.out_ch - m, n), 0)
end
H = vcat(H, Hpad)
end
for i = 1:ggc.num_layers
M = view(ggc.weight, :, :, i) * H
_, M = propagate(ggc, adj, Fill(0.f0, 0, ne(fg)), M, +)
H, _ = ggc.gru(H, M) # BUG: FluxML/Flux.jl#1381
H, _ = ggc.gru(H, M)
end
H
end
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14 changes: 7 additions & 7 deletions test/layers/conv.jl
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Expand Up @@ -60,7 +60,7 @@ fg_single_vertex = FeaturedGraph(adj_single_vertex)
@test size(node_feature(fgt_)) == (out_channel, N)

g = Zygote.gradient(x -> sum(node_feature(gc(x))), fg)[1]
@test size(g[].nf) == size(X)
@test size(g.nf) == size(X)

g = Zygote.gradient(model -> sum(node_feature(model(fg))), gc)[1]
@test size(g.weight) == size(gc.weight)
Expand Down Expand Up @@ -118,7 +118,7 @@ fg_single_vertex = FeaturedGraph(adj_single_vertex)
@test size(node_feature(fgt_)) == (out_channel, N)

g = Zygote.gradient(x -> sum(node_feature(cc(x))), fg)[1]
@test size(g[].nf) == size(X)
@test size(g.nf) == size(X)

g = Zygote.gradient(model -> sum(node_feature(model(fg))), cc)[1]
@test size(g.weight) == size(cc.weight)
Expand Down Expand Up @@ -174,7 +174,7 @@ fg_single_vertex = FeaturedGraph(adj_single_vertex)
@test size(node_feature(fgt_)) == (out_channel, N)

g = Zygote.gradient(x -> sum(node_feature(gc(x))), fg)[1]
@test size(g[].nf) == size(X)
@test size(g.nf) == size(X)

g = Zygote.gradient(model -> sum(node_feature(model(fg))), gc)[1]
@test size(g.weight1) == size(gc.weight1)
Expand Down Expand Up @@ -245,7 +245,7 @@ fg_single_vertex = FeaturedGraph(adj_single_vertex)
@test size(node_feature(fgt_)) == (concat ? (out_channel*heads, N) : (out_channel, N))

g = Zygote.gradient(x -> sum(node_feature(gat(x))), fg_gat)[1]
@test size(g[].nf) == size(X)
@test size(g.nf) == size(X)

g = Zygote.gradient(model -> sum(node_feature(model(fg_gat))), gat)[1]
@test size(g.weight) == size(gat.weight)
Expand Down Expand Up @@ -299,7 +299,7 @@ fg_single_vertex = FeaturedGraph(adj_single_vertex)
@test size(node_feature(fgt_)) == (out_channel, N)

g = Zygote.gradient(x -> sum(node_feature(ggc(x))), fg)[1]
@test size(g[].nf) == size(X)
@test size(g.nf) == size(X)

g = Zygote.gradient(model -> sum(node_feature(model(fg))), ggc)[1]
@test size(g.weight) == size(ggc.weight)
Expand Down Expand Up @@ -342,7 +342,7 @@ fg_single_vertex = FeaturedGraph(adj_single_vertex)
@test size(node_feature(fgt_)) == (out_channel, N)

g = Zygote.gradient(x -> sum(node_feature(ec(x))), fg)[1]
@test size(g[].nf) == size(X)
@test size(g.nf) == size(X)

g = Zygote.gradient(model -> sum(node_feature(model(fg))), ec)[1]
@test size(g.nn.weight) == size(ec.nn.weight)
Expand Down Expand Up @@ -371,7 +371,7 @@ fg_single_vertex = FeaturedGraph(adj_single_vertex)

g = Zygote.gradient(x -> sum(node_feature(gc(x))),
FeaturedGraph(adj, nf=X))[1]
@test size(g.x.nf) == size(X)
@test size(g.nf) == size(X)

g = Zygote.gradient(model -> sum(node_feature(model(FeaturedGraph(adj, nf=X)))),
gc)[1]
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8 changes: 3 additions & 5 deletions test/runtests.jl
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@@ -1,12 +1,13 @@
using GeometricFlux
using GeometricFlux.Datasets
using CUDA
using Flux
using Flux: @functor
using FillArrays
using GraphSignals
using LightGraphs: SimpleGraph, SimpleDiGraph, add_edge!, nv, ne
using LinearAlgebra
using NNlib
using NNlib, NNlibCUDA
using SparseArrays: SparseMatrixCSC
using Statistics: mean
using Zygote
Expand All @@ -26,10 +27,7 @@ tests = [
"models",
]

if Flux.use_cuda[]
using CUDA
using Flux: gpu
using NNlibCUDA
if CUDA.functional()
append!(tests, cuda_tests)
else
@warn "CUDA unavailable, not testing GPU support"
Expand Down