106 lines
2.6 KiB
Julia
106 lines
2.6 KiB
Julia
using Flux, Test
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using Flux: maxpool, meanpool
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@testset "Pooling" begin
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x = randn(Float32, 10, 10, 3, 2)
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mp = MaxPool((2, 2))
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@test mp(x) == maxpool(x, PoolDims(x, 2))
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mp = MeanPool((2, 2))
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@test mp(x) == meanpool(x, PoolDims(x, 2))
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end
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@testset "CNN" begin
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r = zeros(Float32, 28, 28, 1, 5)
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m = Chain(
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Conv((2, 2), 1=>16, relu),
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MaxPool((2,2)),
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Conv((2, 2), 16=>8, relu),
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MaxPool((2,2)),
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x -> reshape(x, :, size(x, 4)),
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Dense(288, 10), softmax)
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@test size(m(r)) == (10, 5)
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end
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@testset "asymmetric padding" begin
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r = ones(Float32, 28, 28, 1, 1)
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m = Conv((3, 3), 1=>1, relu; pad=(0,1,1,2))
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m.weight.data[:] .= 1.0
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m.bias.data[:] .= 0.0
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y_hat = Flux.data(m(r))[:,:,1,1]
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@test size(y_hat) == (27, 29)
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@test y_hat[1, 1] ≈ 6.0
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@test y_hat[2, 2] ≈ 9.0
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@test y_hat[end, 1] ≈ 4.0
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@test y_hat[1, end] ≈ 3.0
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@test y_hat[1, end-1] ≈ 6.0
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@test y_hat[end, end] ≈ 2.0
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end
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@testset "Depthwise Conv" begin
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r = zeros(Float32, 28, 28, 3, 5)
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m1 = DepthwiseConv((2, 2), 3=>15)
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@test size(m1(r), 3) == 15
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m3 = DepthwiseConv((2, 3), 3=>9)
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@test size(m3(r), 3) == 9
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# Test that we cannot ask for non-integer multiplication factors
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@test_throws AssertionError DepthwiseConv((2,2), 3=>10)
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end
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@testset "ConvTranspose" begin
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x = zeros(Float32, 28, 28, 1, 1)
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y = Conv((3,3), 1 => 1)(x)
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x_hat = ConvTranspose((3, 3), 1 => 1)(y)
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@test size(x_hat) == size(x)
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end
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@testset "CrossCor" begin
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x = rand(Float32, 28, 28, 1, 1)
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w = rand(2,2,1,1)
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y = CrossCor(w, [0.0])
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@test sum(w .* x[1:2, 1:2, :, :]) == y(x)[1, 1, 1, 1]
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r = zeros(Float32, 28, 28, 1, 5)
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m = Chain(
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CrossCor((2, 2), 1=>16, relu),
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MaxPool((2,2)),
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CrossCor((2, 2), 16=>8, relu),
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MaxPool((2,2)),
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x -> reshape(x, :, size(x, 4)),
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Dense(288, 10), softmax)
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@test size(m(r)) == (10, 5)
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@test y(x) != Conv(w, [0.0])(x)
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@test CrossCor(w[end:-1:1, end:-1:1, :, :], [0.0])(x) == Conv(w, [0.0])(x)
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end
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@testset "Conv with non quadratic window #700" begin
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data = zeros(Float32, 7,7,1,1)
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data[4,4,1,1] = 1
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l = Conv((3,3), 1=>1)
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expected = zeros(eltype(l.weight),5,5,1,1)
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expected[2:end-1,2:end-1,1,1] = l.weight
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@test expected == l(data)
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l = Conv((3,1), 1=>1)
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expected = zeros(eltype(l.weight),5,7,1,1)
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expected[2:end-1,4,1,1] = l.weight
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@test expected == l(data)
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l = Conv((1,3), 1=>1)
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expected = zeros(eltype(l.weight),7,5,1,1)
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expected[4,2:end-1,1,1] = l.weight
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@test expected == l(data)
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@test begin
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# we test that the next expression does not throw
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randn(Float32, 10,10,1,1) |> Conv((6,1), 1=>1, Flux.σ)
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true
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end
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end
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