46 lines
1.1 KiB
Julia
46 lines
1.1 KiB
Julia
using Flux.Tracker, Base.Test, NNlib
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using Flux.Tracker: gradcheck
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gradtest(f, xs::AbstractArray...) = gradcheck((xs...) -> sum(f(xs...)), xs...)
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gradtest(f, dims...) = gradtest(f, rand.(dims)...)
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@testset "Tracker" begin
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@test gradtest((x, W, b) -> σ.(W*x .+ b), 5, (2,5), 2)
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@test gradtest((x, W, b) -> σ.(W*x .+ b), (5,3), (2,5), 2)
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@test gradtest((w, x) -> w'*x, randn(10, 2), randn(10))
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@test gradtest(x -> sin.(sum(x, (2, 3))), (3,4,5))
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@test gradtest(x -> softmax(x).*(1:3), 3)
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@test gradtest(x -> softmax(x).*(1:3), (3,5))
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@test gradtest(Flux.mse, rand(5,5), rand(5, 5))
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@test gradtest(Flux.crossentropy, rand(5,5), rand(5, 5))
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@test gradtest(x -> x', rand(5))
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@test gradtest(vcat, rand(5), rand(3))
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@test gradtest(vcat, rand(2,3), rand(3,3))
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@testset "mean" begin
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@test gradtest(mean, rand(2, 3))
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@test gradtest(x -> mean(x, 1), rand(2, 3))
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@test gradtest(x -> mean(x, 2), rand(2, 3))
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@test gradtest(x -> mean(x, 3), rand(2, 3, 4))
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@test gradtest(x -> mean(x, [1, 2]), rand(2, 3, 4))
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end
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@test gradtest(x -> std(x), rand(5,5))
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@test gradtest(x -> std(x, 1), rand(5,5))
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@test gradtest(rand(5)) do x
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y = x.^2
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2y + x
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end
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end #testset
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