Testing (and fixing) handling of AbstractVector{AbstractVector{T}} inputs

Project.toml

@@ -1,6 +1,6 @@
 name = "KernelFunctions"
 uuid = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
-version = "0.10.22"
+version = "0.10.23"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"

src/basekernels/fbm.jl

@@ -43,6 +43,8 @@ end
 _fbm(modX, modY, modXY, h) = (modX^h + modY^h - modXY^h) / 2
 
 _mod(x::AbstractVector{<:Real}) = abs2.(x)
+_mod(x::AbstractVector{<:AbstractVector{<:Real}}) = sum.(abs2, x)
+# two lines above could be combined into the second (dispatching on general AbstractVectors), but this (somewhat) more performant
 _mod(x::ColVecs) = vec(sum(abs2, x.X; dims=1))
 _mod(x::RowVecs) = vec(sum(abs2, x.X; dims=2))
 

src/distances/delta.jl

@@ -1,19 +1,10 @@
 # Delta is not following the PreMetric rules since d(x, x) == 1
 struct Delta <: Distances.UnionPreMetric end
 
-@inline function Distances._evaluate(::Delta, a::AbstractVector, b::AbstractVector)
-    @boundscheck if length(a) != length(b)
-        throw(
-            DimensionMismatch(
-                "first array has length $(length(a)) which does not match the length of the " *
-                "second, $(length(b)).",
-            ),
-        )
-    end
-    return a == b
-end
-
-Distances.result_type(::Delta, Ta::Type, Tb::Type) = Bool
-
+@inline Distances.eval_op(::Delta, a::Real, b::Real) = a == b
+@inline Distances.eval_reduce(::Delta, a, b) = a && b
+@inline Distances.eval_start(::Delta, a, b) = true
 @inline (dist::Delta)(a::AbstractArray, b::AbstractArray) = Distances._evaluate(dist, a, b)
 @inline (dist::Delta)(a::Number, b::Number) = a == b
+
+Distances.result_type(::Delta, Ta::Type, Tb::Type) = Bool

src/test_utils.jl

@@ -133,6 +133,18 @@ function test_interface(
     )
 end
 
+function test_interface(
+    rng::AbstractRNG, k::Kernel, ::Type{<:Vector{Vector{T}}}; dim_in=2, kwargs...
+) where {T<:Real}
+    return test_interface(
+        k,
+        [randn(rng, T, dim_in) for _ in 1:1001],
+        [randn(rng, T, dim_in) for _ in 1:1001],
+        [randn(rng, T, dim_in) for _ in 1:1000];
+        kwargs...,
+    )
+end
+
 function test_interface(k::Kernel, T::Type{<:AbstractVector}; kwargs...)
     return test_interface(Random.GLOBAL_RNG, k, T; kwargs...)
 end
@@ -147,6 +159,9 @@ function test_interface(rng::AbstractRNG, k::Kernel, T::Type{<:Real}; kwargs...)
     @testset "RowVecs{$T}" begin
         test_interface(rng, k, RowVecs{T}; kwargs...)
     end
+    @testset "Vector{Vector{T}}" begin
+        test_interface(rng, k, Vector{Vector{T}}; kwargs...)
+    end
 end
 
 function test_interface(k::Kernel, T::Type{<:Real}=Float64; kwargs...)