45 lines
1.0 KiB
Julia
45 lines
1.0 KiB
Julia
using Flux, Flux.Tracker, CuArrays, Test
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using Flux: gpu
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# @info "Testing GPU Support"
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#
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# @testset "CuArrays" begin
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#
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# CuArrays.allowscalar(false)
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#
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# x = param(randn(5, 5))
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# cx = gpu(x)
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# @test cx isa TrackedArray && cx.data isa CuArray
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#
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# x = Flux.onehotbatch([1, 2, 3], 1:3)
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# cx = gpu(x)
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# @test cx isa Flux.OneHotMatrix && cx.data isa CuArray
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# @test (cx .+ 1) isa CuArray
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#
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# m = Chain(Dense(10, 5, tanh), Dense(5, 2), softmax)
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# cm = gpu(m)
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#
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# @test all(p isa TrackedArray && p.data isa CuArray for p in params(cm))
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# @test cm(gpu(rand(10, 10))) isa TrackedArray{Float32,2,CuArray{Float32,2}}
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#
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# x = [1,2,3]
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# cx = gpu(x)
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# @test Flux.crossentropy(x,x) ≈ Flux.crossentropy(cx,cx)
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#
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# xs = param(rand(5,5))
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# ys = Flux.onehotbatch(1:5,1:5)
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# @test collect(cu(xs) .+ cu(ys)) ≈ collect(xs .+ ys)
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#
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# c = gpu(Conv((2,2),3=>4))
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# l = c(gpu(rand(10,10,3,2)))
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# Flux.back!(sum(l))
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#
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# end
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if CuArrays.cudnn_available()
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@info "Testing Flux/CUDNN BatchNorm"
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include("cudnn.jl")
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@info "Testing Flux/CUDNN RNN"
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include("curnn.jl")
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end
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