Refactor test

Author: foldfelis

test/loss.jl

@@ -3,7 +3,8 @@
     𝐲̂ = rand(1, 3, 3, 5)
 
     feature_dims = 2:3
-    loss = mean(.√(sum(abs2, 𝐲̂-𝐲, dims=feature_dims)))
+    loss = sum(.√(sum(abs2, 𝐲̂-𝐲, dims=feature_dims)))
+    y_norm = sum(.√(sum(abs2, 𝐲, dims=feature_dims)))
 
-    @test l₂loss(𝐲̂, 𝐲) ≈ loss/prod(feature_dims)
+    @test l₂loss(𝐲̂, 𝐲) ≈ loss/y_norm
 end

test/model.jl

@@ -1,7 +1,7 @@
 @testset "FourierNeuralOperator" begin
     m = FourierNeuralOperator()
 
-    𝐱, 𝐲 = rand(Float32, 2, 1024, 5), rand(Float32, 1024, 5)
+    𝐱, 𝐲 = rand(Float32, 2, 1024, 5), rand(Float32, 1, 1024, 5)
     @test size(m(𝐱)) == size(𝐲)
 
     loss(𝐱, 𝐲) = sum(abs2, 𝐲 .- m(𝐱)) / size(𝐱)[end]

test/runtests.jl

@@ -4,7 +4,6 @@ using Flux
 using GeometricFlux
 using Graphs
 using Zygote
-using Statistics
 using Test
 
 CUDA.allowscalar(false)