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Attempt to fix the compatibility issue. #293

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Attempt to fix the compatibility issue. #293

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25 changes: 13 additions & 12 deletions examples/semisupervised_gcn.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -42,22 +42,23 @@ end
target_dim = 7 # target dimension
end

## Loss: cross entropy with first layer L2 regularization
## Loss: cross entropy with first layer L2 regularization
l2norm(x) = sum(abs2, x)
function model_loss(model, λ, batch)

function model_loss(model, λ, batch, batch_size::Int)
loss = 0.f0
for (x, y) in batch
for (x, y) in [[batch[1][i], batch[2][:,:,i]] for i = 1:batch_size]
loss += logitcrossentropy(model(x), y)
loss += λ*sum(l2norm, Flux.params(model[1]))
end
return loss
end

function accuracy(model, batch::AbstractVector)
return mean(mean(onecold(softmax(cpu(model(x)))) .== onecold(cpu(y))) for (x, y) in batch)
function accuracy(model, batch::Tuple{AbstractVector, AbstractArray}, batch_size::Int)
return mean(mean(onecold(softmax(cpu(model(x)))) .== onecold(cpu(y))) for (x,y) in [[batch[1][i], batch[2][:,:,i]] for i = 1:batch_size])
end

accuracy(model, loader::DataLoader, device) = mean(accuracy(model, batch |> device) for batch in loader)
accuracy(model, loader::DataLoader, device, batch_size::Int) = mean(accuracy(model, batch |> device, batch_size) for batch in loader)

function train(; kws...)
# load hyperparamters
Expand All @@ -75,7 +76,7 @@ function train(; kws...)

# load Cora from Planetoid dataset
train_loader, test_loader = load_data(:cora, args.batch_size)

# build model
model = Chain(
GCNConv(args.input_dim=>args.hidden_dim, relu),
Expand All @@ -86,7 +87,7 @@ function train(; kws...)

# ADAM optimizer
opt = ADAM(args.η)

# parameters
ps = Flux.params(model)

Expand All @@ -96,13 +97,12 @@ function train(; kws...)
for epoch = 1:args.epochs
@info "Epoch $(epoch)"
progress = Progress(length(train_loader))

for batch in train_loader
loss, back = Flux.pullback(ps) do
model_loss(model, args.λ, batch |> device)
model_loss(model, args.λ, batch |> device, args.batch_size)
end
train_acc = accuracy(model, train_loader, device)
test_acc = accuracy(model, test_loader, device)
train_acc = accuracy(model, train_loader, device, args.batch_size)
test_acc = accuracy(model, test_loader, device, args.batch_size)
grad = back(1f0)
Flux.Optimise.update!(opt, ps, grad)

Expand All @@ -115,6 +115,7 @@ function train(; kws...)

train_steps += 1
end

end

return model, args
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