Factor out _to_colvecs

Author: Will Tebbutt

src/basekernels/nn.jl

@@ -40,21 +40,21 @@ end
 function kernelmatrix(
     k::NeuralNetworkKernel, x::AbstractVector{<:Real}, y::AbstractVector{<:Real}
 )
-    return kernelmatrix(k, ColVecs(reshape(x, 1, :)), ColVecs(reshape(y, 1, :)))
+    return kernelmatrix(k, _to_colvecs(x), _to_colvecs(y))
 end
 
 function kernelmatrix(k::NeuralNetworkKernel, x::AbstractVector{<:Real})
-    return kernelmatrix(k, ColVecs(reshape(x, 1, :)))
+    return kernelmatrix(k, _to_colvecs(x))
 end
 
 function kernelmatrix_diag(
     k::NeuralNetworkKernel, x::AbstractVector{<:Real}, y::AbstractVector{<:Real}
 )
-    return kernelmatrix_diag(k, ColVecs(reshape(x, 1, :)), ColVecs(reshape(y, 1, :)))
+    return kernelmatrix_diag(k, _to_colvecs(x), _to_colvecs(y))
 end
 
 function kernelmatrix_diag(k::NeuralNetworkKernel, x::AbstractVector{<:Real})
-    return kernelmatrix_diag(k, ColVecs(reshape(x, 1, :)))
+    return kernelmatrix_diag(k, _to_colvecs(x))
 end
 
 function kernelmatrix(::NeuralNetworkKernel, x::ColVecs, y::ColVecs)

src/utils.jl

@@ -97,6 +97,8 @@ Base.zero(x::ColVecs) = ColVecs(zero(x.X))
 
 dim(x::ColVecs) = size(x.X, 1)
 
+_to_colvecs(x::AbstractVector{<:Real}) = ColVecs(reshape(x, 1, :))
+
 pairwise(d::PreMetric, x::ColVecs) = Distances_pairwise(d, x.X; dims=2)
 pairwise(d::PreMetric, x::ColVecs, y::ColVecs) = Distances_pairwise(d, x.X, y.X; dims=2)
 function pairwise(d::PreMetric, x::AbstractVector, y::ColVecs)