Reworked dim and added tests for it

Author: theogf

src/utils.jl

@@ -92,9 +92,9 @@ For a transform return its parameters, for a `ChainTransform` return a vector of
 #params
 
 dim(x) = 0 # This is the passes-by-default choice. For a proper check, implement `KernelFunctions.dim` for your datatype.
+dim(x::AbstractVector) = dim(first(x))
 dim(x::AbstractVector{<:AbstractVector{<:Real}}) = length(first(x))
 dim(x::AbstractVector{<:Real}) = 1
-dim(x::AbstractVector{Tuple{Any,Int}}) = 1
 
 
 function validate_inputs(x, y)

test/utils.jl

@@ -84,6 +84,12 @@
         xx = [rand(rng, D, D) for _ in 1:N1]
         xx⁻ = [rand(rng, D, D⁻) for _ in 1:N1]
         yy = [rand(rng, D, D) for _ in 1:N2]
+
+        @test KernelFunctions.dim("string") == 0
+        @test KernelFunctions.dim(["string", "string2"]) == 0
+        @test KernelFunctions.dim(rand(rng, 4)) == 1
+        @test KernelFunctions.dim(x) == D
+
         @test_nowarn KernelFunctions.validate_inplace_dims(zeros(N1, N2), x, y)
         @test_throws DimensionMismatch KernelFunctions.validate_inplace_dims(zeros(N1, N1), x, y)
         @test_throws DimensionMismatch KernelFunctions.validate_inplace_dims(zeros(N1, N2), x⁻, y)