Tests cosmetics

Author: theogf

test/testAD.jl

@@ -7,29 +7,32 @@ dims = [10,5]
 A = rand(dims...)
 B = rand(dims...)
 K = [zeros(dims[1],dims[1]),zeros(dims[2],dims[2])]
-kernels = [SquaredExponentialKernel]
+kernels = [SquaredExponentialKernel,MaternKernel]
 l = 2.0
 vl = l*ones(dims[1])
 testfunction(k,A,B) = sum(kernelmatrix(k,A,B))
 testfunction(k,A) = sum(kernelmatrix(k,A))
 
-testfunction(SquaredExponentialKernel(vl),A)
 ##Eventually store real results in file
 @testset "Zygote Automatic Differentiation test" begin
     @testset "ARD" begin
         for k in kernels
-            @test all(isapprox.(Zygote.gradient(x->testfunction(k(x),A,B),vl)[1], ForwardDiff.gradient(x->testfunction(k(x),A,B),vl)))
-            @test  all(isapprox.(Zygote.gradient(x->testfunction(k(vl),x,B),A)[1],ForwardDiff.gradient(x->testfunction(k(vl),x,B),A)))
-            @test all(isapprox.(Zygote.gradient(x->testfunction(k(x),A),vl)[1],ForwardDiff.gradient(x->testfunction(k(x),A),vl)))
-            @test all(isapprox.(Zygote.gradient(x->testfunction(k(vl),x),A)[1],ForwardDiff.gradient(x->testfunction(k(vl),x),A)))
+            @testset "$k" begin
+                @test all(isapprox.(Zygote.gradient(x->testfunction(k(x),A,B),vl)[1], ForwardDiff.gradient(x->testfunction(k(x),A,B),vl)))
+                @test  all(isapprox.(Zygote.gradient(x->testfunction(k(vl),x,B),A)[1],ForwardDiff.gradient(x->testfunction(k(vl),x,B),A)))
+                @test all(isapprox.(Zygote.gradient(x->testfunction(k(x),A),vl)[1],ForwardDiff.gradient(x->testfunction(k(x),A),vl)))
+                @test all(isapprox.(Zygote.gradient(x->testfunction(k(vl),x),A)[1],ForwardDiff.gradient(x->testfunction(k(vl),x),A)))
+            end
         end
     end
     @testset "ISO" begin
         for k in kernels
-            @test all(isapprox.(Zygote.gradient(x->testfunction(k(x),A,B),l)[1],ForwardDiff.gradient(x->testfunction(k(x[1]),A,B),[l])[1]))
-            @test all(isapprox.(Zygote.gradient(x->testfunction(k(l),x,B),A)[1],ForwardDiff.gradient(x->testfunction(k(l),x,B),A)))
-            @test all(isapprox.(Zygote.gradient(x->testfunction(k(x),A),l)[1],ForwardDiff.gradient(x->testfunction(k(x[1]),A),[l])))
-            @test all(isapprox.(Zygote.gradient(x->testfunction(k(l),x),A)[1],ForwardDiff.gradient(x->testfunction(k(l[1]),x),A)))
+            @testset "$k" begin
+                @test all(isapprox.(Zygote.gradient(x->testfunction(k(x),A,B),l)[1],ForwardDiff.gradient(x->testfunction(k(x[1]),A,B),[l])[1]))
+                @test all(isapprox.(Zygote.gradient(x->testfunction(k(l),x,B),A)[1],ForwardDiff.gradient(x->testfunction(k(l),x,B),A)))
+                @test all(isapprox.(Zygote.gradient(x->testfunction(k(x),A),l)[1],ForwardDiff.gradient(x->testfunction(k(x[1]),A),[l])))
+                @test all(isapprox.(Zygote.gradient(x->testfunction(k(l),x),A)[1],ForwardDiff.gradient(x->testfunction(k(l[1]),x),A)))
+            end
         end
     end
 end