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Flux.jl
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Added tests for dice and Tversky loss

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Adarsh Kumar 2020-02-27 02:29:39 +05:30 committed by GitHub
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commit 3d8965230f
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1 changed files with 14 additions and 1 deletions
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test/layers/stateless.jl
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@ -90,11 +90,24 @@ const ϵ = 1e-7
@test Flux.poisson(y, y) ≈ 0.5044459776946685
end
y = [1.0 0.5 0.3 2.4]
y1 = [0 1.4 0.5 1.2]
@testset "dice_coeff_loss" begin
@test Flux.dice_coeff_loss(y, y1) ≈ 0.2799999999999999
@test Flux.dice_coeff_loss(y,y) ≈ 0.0
end
@testset "tversky_loss" begin
@test Flux.tversky_loss(y,y1) ≈ 0.028747433264887046
@test Flux.tversky_loss(y,y1,0.8) ≈ 0.050200803212851364
@test Flux.tversky_loss(y,y) ≈ -0.5576923076923075
end
@testset "no spurious promotions" begin
for T in (Float32, Float64)
y = rand(T, 2)
ŷ = rand(T, 2)
for f in (mse, crossentropy, logitcrossentropy, Flux.kldivergence, Flux.hinge, Flux.poisson,Flux.mae,Flux.huber_loss,Flux.msle,Flux.squared_hinge)
for f in (mse, crossentropy, logitcrossentropy, Flux.kldivergence, Flux.hinge, Flux.poisson,Flux.mae,Flux.huber_loss,Flux.msle,Flux.squared_hinge,Flux.dice_coeff_loss,Flux.tversky_loss)
fwd, back = Flux.pullback(f, ŷ, y)
@test fwd isa T
@test eltype(back(one(T))[1]) == T