49 lines
1.1 KiB
Julia
49 lines
1.1 KiB
Julia
using Flux, Flux.Tracker, CuArrays, Test
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using Flux.Tracker: TrackedArray, data
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@testset "CUDNN BatchNorm" begin
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@testset "4D Input" begin
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x = TrackedArray(Float64.(collect(reshape(1:12, 2, 2, 3, 1))))
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m = BatchNorm(3)
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cx = gpu(x)
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cm = gpu(m)
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y = m(x)
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cy = cm(cx)
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@test cy isa TrackedArray{Float32,4,CuArray{Float32,4}}
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@test cpu(data(cy)) ≈ data(y)
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g = rand(size(y)...)
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Flux.back!(y, g)
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Flux.back!(cy, gpu(g))
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@test m.γ.grad ≈ cpu(cm.γ.grad)
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@test m.β.grad ≈ cpu(cm.β.grad)
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@test x.grad ≈ cpu(x.grad)
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end
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@testset "2D Input" begin
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x = TrackedArray(Float64.(collect(reshape(1:12, 3, 4))))
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m = BatchNorm(3)
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cx = gpu(x)
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cm = gpu(m)
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y = m(x)
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cy = cm(cx)
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@test cy isa TrackedArray{Float32,2,CuArray{Float32,2}}
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@test cpu(data(cy)) ≈ data(y)
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g = rand(size(y)...)
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Flux.back!(y, g)
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Flux.back!(cy, gpu(g))
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@test m.γ.grad ≈ cpu(cm.γ.grad)
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@test m.β.grad ≈ cpu(cm.β.grad)
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@test x.grad ≈ cpu(x.grad)
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end
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end
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