Add support for using non-AbstractArrays with OrdinaryDiffEq and Zygote

src/concrete_solve.jl

@@ -946,6 +946,8 @@ function DiffEqBase._concrete_solve_adjoint(
                         if !(Δ isa NoTangent || v isa ZeroTangent)
                             if u0 isa Number
                                 ForwardDiff.value.(J'v)
+                            elseif v isa Tangent
+                                ForwardDiff.value.(J'vec(v.x))
                             else
                                 ForwardDiff.value.(J'vec(v))
                             end
@@ -1110,6 +1112,8 @@ function DiffEqBase._concrete_solve_adjoint(
                     if !(Δ isa NoTangent || v isa ZeroTangent)
                         if u0 isa Number
                             ForwardDiff.value.(J'v)
+                        elseif v isa Tangent
+                            ForwardDiff.value.(J'vec(v.x))
                         else
                             ForwardDiff.value.(J'vec(v))
                         end

test/noindex_tests.jl

@@ -0,0 +1,97 @@
+using OrdinaryDiffEq, RecursiveArrayTools, LinearAlgebra
+using Zygote, SciMLSensitivity, Random, Test
+
+struct CustomArray{T, N}
+    x::Array{T, N}
+end
+Base.size(x::CustomArray) = size(x.x)
+Base.axes(x::CustomArray) = axes(x.x)
+Base.ndims(x::CustomArray) = ndims(x.x)
+Base.ndims(::Type{<:CustomArray{T,N}}) where {T,N} = N
+Base.zero(x::CustomArray) = CustomArray(zero(x.x))
+Base.zero(::Type{<:CustomArray{T,N}}) where {T,N} = CustomArray(zero(Array{T,N}))
+Base.similar(x::CustomArray, dims::Union{Integer, AbstractUnitRange}...) = CustomArray(similar(x.x, dims...))
+Base.copyto!(x::CustomArray, y::CustomArray) = CustomArray(copyto!(x.x, y.x))
+Base.copy(x::CustomArray) = CustomArray(copy(x.x))
+Base.length(x::CustomArray) = length(x.x)
+Base.isempty(x::CustomArray) = isempty(x.x)
+Base.eltype(x::CustomArray) = eltype(x.x)
+Base.zero(x::CustomArray) = CustomArray(zero(x.x))
+Base.fill!(x::CustomArray, y) = CustomArray(fill!(x.x, y))
+Base.getindex(x::CustomArray, i) = getindex(x.x, i)
+Base.setindex!(x::CustomArray, v, idx) = setindex!(x.x, v, idx)
+Base.firstindex(x::CustomArray) = firstindex(x.x)
+Base.lastindex(x::CustomArray) = lastindex(x.x)
+Base.eachindex(x::CustomArray) = eachindex(x.x)
+Base.mapreduce(f, op, x::CustomArray; kwargs...) = mapreduce(f, op, x.x; kwargs...)
+Base.any(f::Function, x::CustomArray; kwargs...) = any(f, x.x; kwargs...)
+Base.all(f::Function, x::CustomArray; kwargs...) = all(f, x.x; kwargs...)
+Base.similar(x::CustomArray, t) = CustomArray(similar(x.x, t))
+Base.:(+)(x::CustomArray, y::CustomArray) = CustomArray(x.x + y.x)
+Base.:(==)(x::CustomArray, y::CustomArray) = x.x == y.x
+Base.:(*)(x::Number, y::CustomArray) = CustomArray(x*y.x)
+Base.:(/)(x::CustomArray, y::Number) = CustomArray(x.x/y)
+LinearAlgebra.norm(x::CustomArray) = norm(x.x)
+LinearAlgebra.vec(x::CustomArray) = CustomArray(vec(x.x))
+
+struct CustomStyle{N} <: Broadcast.BroadcastStyle where {N} end
+CustomStyle(::Val{N}) where N = CustomStyle{N}()
+CustomStyle{M}(::Val{N}) where {N,M} = NoIndexStyle{N}()
+Base.BroadcastStyle(::Type{<:CustomArray{T,N}}) where {T,N} = CustomStyle{N}()
+Broadcast.BroadcastStyle(::CustomStyle{N}, ::Broadcast.DefaultArrayStyle{0}) where {N} = CustomStyle{N}()
+Base.similar(bc::Base.Broadcast.Broadcasted{CustomStyle{N}}, ::Type{ElType}) where {N, ElType} = CustomArray(similar(Array{ElType, N}, axes(bc)))
+Base.@propagate_inbounds Base.Broadcast._broadcast_getindex(x::CustomArray, i) = x.x[i]
+Base.Broadcast.extrude(x::CustomArray) = x
+Base.Broadcast.broadcastable(x::CustomArray) = x
+
+@inline function Base.copyto!(dest::CustomArray, bc::Base.Broadcast.Broadcasted{<:Union{Base.Broadcast.AbstractArrayStyle,CustomStyle}})
+    axes(dest) == axes(bc) || throwdm(axes(dest), axes(bc))
+    bc′ = Base.Broadcast.preprocess(dest, bc)
+    dest′ = dest.x
+    @simd for I in 1:length(dest′)
+        @inbounds dest′[I] = bc′[I]
+    end
+    return dest
+end
+@inline function Base.copy(bc::Base.Broadcast.Broadcasted{<:CustomStyle})
+    bcf = Broadcast.flatten(bc)
+    x = find_x(bcf)
+    data = similar(x, eltype(bcf[1]))
+    @inbounds @simd for I in 1:length(x)
+        data[I] = bcf[I]
+    end
+    return CustomArray(data)
+end
+find_x(bc::Broadcast.Broadcasted) = find_x(bc.args)
+find_x(args::Tuple) = find_x(find_x(args[1]), Base.tail(args))
+find_x(x) = x
+find_x(::Any, rest) = find_x(rest)
+find_x(x::CustomArray, rest) = x.x
+
+RecursiveArrayTools.recursive_unitless_bottom_eltype(x::CustomArray) = eltype(x)
+RecursiveArrayTools.recursivecopy!(dest::CustomArray, src::CustomArray) = copyto!(dest, src)
+RecursiveArrayTools.recursivecopy(x::CustomArray) = copy(x)
+RecursiveArrayTools.recursivefill!(x::CustomArray, a) = fill!(x, a)
+
+Base.show_vector(io::IO, x::CustomArray) = Base.show_vector(io, x.x)
+
+Base.show(io::IO, x::CustomArray) = (print(io, "CustomArray");show(io, x.x))
+function Base.show(io::IO, ::MIME"text/plain", x::CustomArray)
+    println(io, Base.summary(x), ":")
+    Base.print_array(io, x.x)
+end
+
+ca0 = CustomArray(ones(2))
+tspan = (0.0, 1.0)
+par = [rand(), rand()]
+
+algs = [Tsit5(), BS3(), Vern9(), DP5()]
+
+for alg in algs
+    function cost(p)
+        prob = ODEProblem((du, u, p, t) -> (du[1] = p[1]*u[1] + p[2]*u[2]; du[2] = p[2]*u[1]), ca0, tspan, p)
+        sol = solve(prob, alg; save_everystep = false)
+        return 1 - norm(sol[end])^2
+    end
+    @test_nowarn Zygote.gradient(cost, par)
+end