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