99 lines
2.3 KiB
Julia
99 lines
2.3 KiB
Julia
using Flux: testmode!
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@testset "Dropout" begin
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x = [1.,2.,3.]
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@test x == testmode!(Dropout(0.1))(x)
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@test x == Dropout(0)(x)
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@test zeros(x) == Dropout(1)(x)
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x = rand(100)
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m = Dropout(0.9)
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y = m(x)
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@test count(a->a==0, y) > 50
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testmode!(m)
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y = m(x)
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@test count(a->a==0, y) == 0
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testmode!(m, false)
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y = m(x)
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@test count(a->a==0, y) > 50
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x = rand(100)
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m = Chain(Dense(100,100),
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Dropout(0.9))
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y = m(x)
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@test count(a->a == 0, y) > 50
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testmode!(m)
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y = m(x)
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@test count(a->a == 0, y) == 0
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end
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@testset "BatchNorm" begin
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let m = BatchNorm(2), x = param([1 2; 3 4; 5 6]')
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@test m.β.data == [0, 0] # initβ(2)
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@test m.γ.data == [1, 1] # initγ(2)
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# initial m.σ is 1
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# initial m.μ is 0
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@test m.active
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# @test m(x).data ≈ [-1 -1; 0 0; 1 1]'
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m(x)
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# julia> x
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# 2×3 Array{Float64,2}:
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# 1.0 3.0 5.0
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# 2.0 4.0 6.0
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#
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# μ of batch will be
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# (1. + 3. + 5.) / 3 = 3
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# (2. + 4. + 6.) / 3 = 4
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#
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# ∴ update rule with momentum:
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# .1 * 3 + 0 = .3
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# .1 * 4 + 0 = .4
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@test m.μ ≈ reshape([0.3, 0.4], 2, 1)
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# julia> .1 .* std(x, 2, corrected=false) .* (3 / 2).+ .9 .* [1., 1.]
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# 2×1 Array{Float64,2}:
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# 1.14495
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# 1.14495
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@test isapprox(m.σ, .1 .* std(x.data, 2, corrected=false) .* (3 / 2).+ .9 .* [1., 1.], atol = 1.0e-6)
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testmode!(m)
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@test !m.active
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x′ = m(x).data
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@test isapprox(x′[1], (1 - 0.3) / 1.1449489742783179, atol = 1.0e-6)
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end
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# with activation function
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let m = BatchNorm(2, σ), x = param([1 2; 3 4; 5 6]')
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@test m.active
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m(x)
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testmode!(m)
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@test !m.active
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x′ = m(x).data
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@test isapprox(x′[1], σ((1 - 0.3) / 1.1449489742783179), atol = 1.0e-7)
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end
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let m = BatchNorm(2), x = param(reshape(1:6, 3, 2, 1))
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y = reshape(permutedims(x, [2, 1, 3]), 2, :)
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y = permutedims(reshape(m(y), 2, 3, 1), [2, 1, 3])
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@test m(x) == y
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end
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let m = BatchNorm(2), x = param(reshape(1:12, 2, 3, 2, 1))
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y = reshape(permutedims(x, [3, 1, 2, 4]), 2, :)
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y = permutedims(reshape(m(y), 2, 2, 3, 1), [2, 3, 1, 4])
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@test m(x) == y
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end
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let m = BatchNorm(2), x = param(reshape(1:24, 2, 2, 3, 2, 1))
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y = reshape(permutedims(x, [4, 1, 2, 3, 5]), 2, :)
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y = permutedims(reshape(m(y), 2, 2, 2, 3, 1), [2, 3, 4, 1, 5])
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@test m(x) == y
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end
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end
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