=Make rand_tangent on adjoint an transpose return natural

Author: oxinabox

src/rand_tangent.jl

@@ -13,11 +13,13 @@ rand_tangent(rng::AbstractRNG, x::Integer) = NoTangent()
 
 rand_tangent(rng::AbstractRNG, x::T) where {T<:Number} = randn(rng, T)
 
-# TODO: right now Julia don't allow `randn(rng, BigFloat)` 
+# TODO: right now Julia don't allow `randn(rng, BigFloat)`
 # see: https://github.com/JuliaLang/julia/issues/17629
 rand_tangent(rng::AbstractRNG, ::BigFloat) = big(randn(rng))
 
 rand_tangent(rng::AbstractRNG, x::StridedArray) = rand_tangent.(Ref(rng), x)
+rand_tangent(rng::AbstractRNG, x::Adjoint) = adjoint(rand_tangent(rng, parent(x)))
+rand_tangent(rng::AbstractRNG, x::Tangent) = tangent(rand_tangent(rng, parent(x)))
 
 function rand_tangent(rng::AbstractRNG, x::T) where {T<:Tuple}
     return Tangent{T}(rand_tangent.(Ref(rng), x)...)

test/rand_tangent.jl

@@ -24,6 +24,11 @@ using FiniteDifferences: rand_tangent
         (randn(Complex{Float32}, 5, 4), Matrix{Complex{Float32}}),
         ([randn(5, 4), 4.0], Vector{Any}),
 
+        # Wrapper Arrays
+        (randn(5, 4)', Adjoint{Float64, Matrix{Float64}},
+        (transpose(randn(5, 4)), Transpose{Float64, Matrix{Float64}},
+
+
         # Tuples.
         ((4.0, ), Tangent{Tuple{Float64}}),
         ((5.0, randn(3)), Tangent{Tuple{Float64, Vector{Float64}}}),