Flux.jl/test/cuda/cuda.jl

using Flux, Flux.Tracker, CuArrays, Test
using Flux: gpu

@info "Testing GPU Support"

@testset "CuArrays" begin

CuArrays.allowscalar(false)

x = param(randn(5, 5))
cx = gpu(x)
@test cx isa TrackedArray && cx.data isa CuArray

x = Flux.onehotbatch([1, 2, 3], 1:3)
cx = gpu(x)
@test cx isa Flux.OneHotMatrix && cx.data isa CuArray
@test (cx .+ 1) isa CuArray

m = Chain(Dense(10, 5, tanh), Dense(5, 2), softmax)
cm = gpu(m)

@test all(p isa TrackedArray && p.data isa CuArray for p in params(cm))
@test cm(gpu(rand(10, 10))) isa TrackedArray{Float32,2,CuArray{Float32,2}}

x = [1,2,3]
cx = gpu(x)
@test Flux.crossentropy(x,x) ≈ Flux.crossentropy(cx,cx)

xs = param(rand(5,5))
ys = Flux.onehotbatch(1:5,1:5)
@test collect(cu(xs) .+ cu(ys)) ≈ collect(xs .+ ys)

c = gpu(Conv((2,2),3=>4))
l = c(gpu(rand(10,10,3,2)))
Flux.back!(sum(l))

end

if CuArrays.cudnn_available()
    info("Testing Flux/CUDNN BatchNorm")
    include("cudnn.jl")
    info("Testing Flux/CUDNN RNN")
    include("curnn.jl")
end