Removed zygote rules

Author: theogf

dev/debugAD.jl

@@ -9,12 +9,12 @@ K = [zeros(dims[1],dims[1]),zeros(dims[2],dims[2])]
 l = 0.1
 vl = l*ones(dims[1])
 testfunction(k,A,B) = det(kernelmatrix(k,A,B))
-testfunction(k,A) = sum(kernelmatrix(k,A))
+testfunction(k,A) = sum(kernelmatrix(k,A,obsdim=2))
 k = MaternKernel(vl)
 KernelFunctions.kappa(k,3)
 testfunction(SqExponentialKernel(vl),A)
 testfunction(MaternKernel(vl),A)
-@which kernelmatrix(MaternKernel(vl),A,B)
+kernelmatrix(MaternKernel(vl),A)
 #For debugging
 @info "Running Zygote gradients"
 Zygote.refresh()
@@ -40,10 +40,10 @@ Zygote.gradient(x->kernelmatrix(MaternKernel(x,1.0),A)[1],l)
 
 @info "Running ForwardDiff gradients"
 ## ForwardDiff
-ForwardDiff.gradient(x->testfunction(SqExponentialKernel(x),A,B),vl) #✓
-ForwardDiff.gradient(x->testfunction(MaternKernel(x),A,B),vl) #✓
 ForwardDiff.gradient(x->testfunction(SqExponentialKernel(x),A),vl) #✓
 ForwardDiff.gradient(x->testfunction(MaternKernel(x),A),vl) #✓
+ForwardDiff.gradient(x->testfunction(SqExponentialKernel(x),A,B),vl) #✓
+ForwardDiff.gradient(x->testfunction(MaternKernel(x),A,B),vl) #✓
 ForwardDiff.gradient(x->testfunction(SqExponentialKernel(x[1]),A,B),[l])
 ForwardDiff.gradient(x->testfunction(MaternKernel(x[1]),A,B),[l])
 ForwardDiff.gradient(x->testfunction(SqExponentialKernel(x[1]),A),[l])

src/zygote_rules.jl

@@ -9,7 +9,6 @@ using Zygote
 include("test_util.jl")
 
 @testset "KernelFunctions" begin
-# include("zygote_rules.jl")
 include("test_kernelmatrix.jl")
 include("test_constructors.jl")
 # include("test_AD.jl")