Port Adjoint, Transpose, and triangular from Nabla

Author: ararslan

src/rules/linalg/structured.jl

@@ -16,3 +16,32 @@ rrule(::Type{<:Symmetric}, A::AbstractMatrix) = Symmetric(A), Rule(_symmetric_ba
 
 _symmetric_back(ΔΩ) = UpperTriangular(ΔΩ) + LowerTriangular(ΔΩ)' - Diagonal(ΔΩ)
 _symmetric_back(ΔΩ::Union{Diagonal,UpperTriangular}) = ΔΩ
+
+#####
+##### `Adjoint`
+#####
+
+# TODO: Deal with complex-valued arrays as well
+rrule(::Type{<:Adjoint}, A::AbstractMatrix{<:Real}) = Adjoint(A), Rule(adjoint)
+rrule(::Type{<:Adjoint}, A::AbstractVector{<:Real}) = Adjoint(A), Rule(vec∘adjoint)
+
+rrule(::typeof(adjoint), A::AbstractMatrix{<:Real}) = adjoint(A), Rule(adjoint)
+rrule(::typeof(adjoint), A::AbstractVector{<:Real}) = adjoint(A), Rule(vec∘adjoint)
+
+#####
+##### `Transpose`
+#####
+
+rrule(::Type{<:Transpose}, A::AbstractMatrix) = Transpose(A), Rule(transpose)
+rrule(::Type{<:Transpose}, A::AbstractVector) = Transpose(A), Rule(vec∘transpose)
+
+rrule(::typeof(transpose), A::AbstractMatrix) = transpose(A), Rule(transpose)
+rrule(::typeof(transpose), A::AbstractVector) = transpose(A), Rule(vec∘transpose)
+
+#####
+##### Triangular matrices
+#####
+
+rrule(::Type{<:UpperTriangular}, A::AbstractMatrix) = UpperTriangular(A), Rule(Matrix)
+
+rrule(::Type{<:LowerTriangular}, A::AbstractMatrix) = LowerTriangular(A), Rule(Matrix)

test/rules/linalg/structured.jl

@@ -18,4 +18,16 @@
         rng, N = MersenneTwister(123456), 3
         rrule_test(Symmetric, randn(rng, N, N), (randn(rng, N, N), randn(rng, N, N)))
     end
+    @testset "$f" for f in (Adjoint, adjoint, Transpose, transpose)
+        rng = MersenneTwister(32)
+        n = 5
+        m = 3
+        rrule_test(f, randn(rng, m, n), (randn(rng, n, m), randn(rng, n, m)))
+        rrule_test(f, randn(rng, 1, n), (randn(rng, n), randn(rng, n)))
+    end
+    @testset "$T" for T in (UpperTriangular, LowerTriangular)
+        rng = MersenneTwister(33)
+        n = 5
+        rrule_test(T, T(randn(rng, n, n)), (randn(rng, n, n), randn(rng, n, n)))
+    end
 end