Make spectral_mixture_kernel type stable for StaticArrays (JuliaGaussianProcesses#501)

* Cherry pick from branch

* Format and patch bump

* Remove StaticArrays from main Project.toml

Author: theogf

Project.toml

@@ -1,6 +1,6 @@
 name = "KernelFunctions"
 uuid = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
-version = "0.10.53"
+version = "0.10.54"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"

src/basekernels/sm.jl

@@ -12,6 +12,11 @@ Here, D is input dimension and A is the number of spectral components.
 
 `h` is the kernel, which defaults to [`SqExponentialKernel`](@ref) if not specified.
 
+!!! warning
+    If you want to make sure that the constructor is type-stable, you should
+    provide [`StaticArrays`](https://github.com/JuliaArrays/StaticArrays.jl) arguments:
+    `αs` as a `StaticVector`, `γs` and `ωs` as `StaticMatrix`.
+
 Generalised Spectral Mixture kernel function. This family of functions is  dense
 in the family of stationary real-valued kernels with respect to the pointwise convergence.[1]
 
@@ -42,11 +47,12 @@ function spectral_mixture_kernel(
         throw(DimensionMismatch("The dimensions of γs ans ωs do not match"))
     end
 
-    return sum(zip(αs, eachcol(γs), eachcol(ωs))) do (α, γ, ω)
+    kernels = map(zip(αs, eachcol(γs), eachcol(ωs))) do (α, γ, ω)
         a = TransformedKernel(h, LinearTransform(γ'))
         b = TransformedKernel(CosineKernel(), LinearTransform(ω'))
         return α * a * b
     end
+    return sum(kernels)
 end
 
 function spectral_mixture_kernel(

test/Project.toml

@@ -14,6 +14,7 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
+StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
@@ -32,4 +33,5 @@ PDMats = "0.9, 0.10, 0.11"
 ReverseDiff = "1.2"
 SpecialFunctions = "0.10, 1, 2"
 StableRNGs = "1"
+StaticArrays = "1"
 Zygote = "0.6.38"

test/basekernels/sm.jl

@@ -48,6 +48,14 @@
         TestUtils.test_interface(k1, x0, x1, x2)
         TestUtils.test_interface(k2, x0, x1, x2)
     end
+
+    @testset "Type stability given static arrays" begin
+        αs = @SVector rand(3)
+        γs = @SMatrix rand(D_in, 3)
+        ωs = @SMatrix rand(D_in, 3)
+        @inferred spectral_mixture_kernel(αs, γs, ωs)
+    end
+
     # test_ADs(x->spectral_mixture_kernel(exp.(x[1:3]), reshape(x[4:18], 5, 3), reshape(x[19:end], 5, 3)), vcat(log.(αs₁), γs[:], ωs[:]), dims = [5,5])
     @test_broken "No tests passing (BaseKernel)"
 end

test/runtests.jl

@@ -10,6 +10,7 @@ using PDMats
 using Random
 using SpecialFunctions
 using StableRNGs
+using StaticArrays
 using Statistics
 using Test
 using Zygote: Zygote