Refactor test

Author: foldfelis

test/deeponet.jl renamed to test/DeepONet/DeepONet.jl

@@ -33,3 +33,9 @@
     @test_throws AssertionError DeepONet((32, 64, 70), (24, 48, 72), σ, tanh)
     @test_throws DimensionMismatch m(a, sensors)
 end
+
+if CUDA.functional()
+    include("cuda.jl")
+else
+    @warn "CUDA unavailable, not testing GPU support"
+end

test/cuda.jl renamed to test/DeepONet/cuda.jl

@@ -1,4 +1,4 @@
-@testset "CUDA" begin @testset "DeepONet" begin
+@testset "DeepONet CUDA" begin
     batch_size = 2
     a = [0.83541104, 0.83479851, 0.83404712, 0.83315711, 0.83212979, 0.83096755,
         0.82967374, 0.82825263, 0.82670928, 0.82504949, 0.82327962, 0.82140651,
@@ -13,4 +13,4 @@
 
     mgrad = Flux.Zygote.gradient(() -> sum(model(a, sensors)), Flux.params(model))
     @test length(mgrad.grads) == 9
-end end
+end

test/model.jl renamed to test/FNO/FNO.jl

@@ -0,0 +1,16 @@
+@testset "GraphKernel" begin
+    batch_size = 5
+    channel = 32
+    N = 10 * 10
+
+    κ = Dense(2 * channel, channel, relu)
+
+    graph = grid([10, 10])
+    𝐱 = rand(Float32, channel, N, batch_size)
+    l = WithGraph(FeaturedGraph(graph), GraphKernel(κ, channel))
+    @test repr(l.layer) == "GraphKernel(Dense(64 => 32, relu), channel=32)"
+    @test size(l(𝐱)) == (channel, N, batch_size)
+
+    g = Zygote.gradient(() -> sum(l(𝐱)), Flux.params(l))
+    @test length(g.grads) == 3
+end

test/nomad.jl renamed to test/NOMAD/NOMAD.jl

@@ -142,20 +142,3 @@ end
     @test SpectralConv(ch, modes) isa OperatorConv
     @test SpectralConv(ch, modes).transform isa FourierTransform
 end
-
-@testset "GraphKernel" begin
-    batch_size = 5
-    channel = 32
-    N = 10 * 10
-
-    κ = Dense(2 * channel, channel, relu)
-
-    graph = grid([10, 10])
-    𝐱 = rand(Float32, channel, N, batch_size)
-    l = WithGraph(FeaturedGraph(graph), GraphKernel(κ, channel))
-    @test repr(l.layer) == "GraphKernel(Dense(64 => 32, relu), channel=32)"
-    @test size(l(𝐱)) == (channel, N, batch_size)
-
-    g = Zygote.gradient(() -> sum(l(𝐱)), Flux.params(l))
-    @test length(g.grads) == 3
-end

test/graph_kernel.jl

@@ -8,29 +8,19 @@ using Test
 
 CUDA.allowscalar(false)
 
-cuda_tests = [
-    "cuda.jl",
-]
+@testset "NeuralOperators.jl" begin
+    # kernels
+    include("Transform/Transform.jl")
+    include("operator_kernel.jl")
+    include("graph_kernel.jl")
+    include("loss.jl")
 
-tests = [
-    "Transform/Transform.jl",
-    "operator_kernel.jl",
-    "loss.jl",
-    "model.jl",
-    "deeponet.jl",
-    "nomad.jl",
-]
-
-if CUDA.functional()
-    append!(tests, cuda_tests)
-else
-    @warn "CUDA unavailable, not testing GPU support"
+    # models
+    include("FNO/FNO.jl")
+    include("DeepONet/DeepONet.jl")
+    include("NOMAD/NOMAD.jl")
 end
 
-@testset "NeuralOperators.jl" begin for t in tests
-    include(t)
-end end
-
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