Functions do not properly redefine with FunctionWrappers in v1.10?

[ChrisRackauckas]

I don't quite understand what's going on here so it's a bit hard to title it. I found it in a test regression in OrdinaryDiffEq.jl SciML/OrdinaryDiffEq.jl#2093 which started giving the wrong error. Seems innocuous, but digging in made it weirder. The MWE I cam up with is:

# Setup
using FunctionWrappers, ForwardDiff, OrdinaryDiffEq

const a = Float64[1.0]
function lorenz!(du, u, p, t)
    du[1] = 10.0(u[2] - u[1])
    a[1] = t
    du[2] = u[1] * (28.0 - u[3]) - u[2]
    du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
u = [1.0; 0.0; 0.0]
du = copy(u)
t = 0.0
dualgen(::Type{T}) where {T} = ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, T}, T, 1}
T = Float64
T1 = Float64
dualT = dualgen(T)

# Version 1
R = Nothing
A = Tuple{Vector{dualgen(T)}, Vector{dualgen(T)}, SciMLBase.NullParameters, Float64}
ff = FunctionWrappers.FunctionWrapper{R, A}(SciMLBase.Void(lorenz!))

ff(du,u,SciMLBase.NullParameters(),t)

Which gives:

julia> ff(du,u,SciMLBase.NullParameters(),t)
ERROR: TypeError: in cfunction, expected Union{}, got a value of type Nothing
Stacktrace:
 [1] macro expansion
   @ FunctionWrappers C:\Users\accou\.julia\packages\FunctionWrappers\Q5cBx\src\FunctionWrappers.jl:137 [inlined]
 [2] do_ccall(f::FunctionWrappers.FunctionWrapper{…}, args::Tuple{…})
   @ FunctionWrappers C:\Users\accou\.julia\packages\FunctionWrappers\Q5cBx\src\FunctionWrappers.jl:125
 [3] (::FunctionWrappers.FunctionWrapper{Nothing, Tuple{…}})(::Vector{Float64}, ::Vararg{Any})
   @ FunctionWrappers C:\Users\accou\.julia\packages\FunctionWrappers\Q5cBx\src\FunctionWrappers.jl:144
 [4] top-level scope
   @ REPL[27]:1
Some type information was truncated. Use `show(err)` to see complete types.

And you might go, that's not an MWE! Delete stuff. Well... deleting stuff and replacing it with the same thing... is fine. Here's the definition of Void: https://github.com/SciML/SciMLBase.jl/blob/v2.11.7/src/utils.jl#L477-L483 . Let's just remove a bit of package code by copy pasting that into the MWE:

struct Void{F}
    f::F
end
function (f::Void)(args...)
    f.f(args...)
    nothing
end
ff = FunctionWrappers.FunctionWrapper{R, A}(Void(lorenz!))
ff(du,u,SciMLBase.NullParameters(),t)

Tada! That works fine. What about getting rid of SciMLBase.NullParameters, that's just a singleton so what about nothing:

R = Nothing
A = Tuple{Vector{dualgen(T)}, Vector{dualgen(T)}, Nothing, Float64}
ff = FunctionWrappers.FunctionWrapper{R, A}(SciMLBase.Void(lorenz!))

ff(du,u,nothing,t)

That works fine too!

So it seems this exact combination of arguments, and only using the version of things in the precompiled (?) package, causes the error. And I don't know what this error really is. It's a v1.10 only issue, so I'm posting here though it's also maybe FunctionWrappers.jl related?

[ChrisRackauckas]

Umm it went away now. Even more confused, but okay.

[ChrisRackauckas]

Okay nope, even more confused. You have to run the failing test before running the MWE?

using FunctionWrappers, ForwardDiff, OrdinaryDiffEq, Test

const a = Float64[1.0]
function lorenz!(du, u, p, t)
    du[1] = 10.0(u[2] - u[1])
    a[1] = u[2]
    du[2] = u[1] * (28.0 - u[3]) - u[2]
    du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
u0 = [1.0; 0.0; 0.0]
tspan = (0.0, 1.0)
prob = ODEProblem(lorenz!, u0, tspan)
@test_throws OrdinaryDiffEq.FirstAutodiffJacError solve(prob, Rosenbrock23())

function lorenz!(du, u, p, t)
    du[1] = 10.0(u[2] - u[1])
    a[1] = t
    du[2] = u[1] * (28.0 - u[3]) - u[2]
    du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
prob = ODEProblem(lorenz!, u0, tspan)

# Throws the wrong error
@test_throws OrdinaryDiffEq.FirstAutodiffTgradError solve(prob, Rosenbrock23())

u = [1.0; 0.0; 0.0]
du = copy(u)
t = 0.0
dualgen(::Type{T}) where {T} = ForwardDiff.Dual{ForwardDiff.Tag{DiffEqBase.OrdinaryDiffEqTag, T}, T, 1}
T = Float64
T1 = Float64
dualT = dualgen(T)

# Version 1
R = Nothing
A = Tuple{Vector{dualgen(T)}, Vector{dualgen(T)}, SciMLBase.NullParameters, Float64}
ff = FunctionWrappers.FunctionWrapper{R, A}(SciMLBase.Void(lorenz!))

ff(du,u,SciMLBase.NullParameters(),t)

If you omit the test runs before it, it will not error.

[ChrisRackauckas]

using FunctionWrappers, ForwardDiff, OrdinaryDiffEq, Test

const a = Float64[1.0]
function lorenz!(du, u, p, t)
    du[1] = 10.0(u[2] - u[1])
    a[1] = u[2]
    du[2] = u[1] * (28.0 - u[3]) - u[2]
    du[3] = u[1] * u[2] - (8 / 3) * u[3]
end

function lorenz!(du, u, p, t)
    du[1] = 10.0(u[2] - u[1])
    a[1] = t
    du[2] = u[1] * (28.0 - u[3]) - u[2]
    du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
u0 = [1.0; 0.0; 0.0]
tspan = (0.0,1.0)
prob = ODEProblem(lorenz!, u0, tspan)

# Throws the wrong error
@test_throws OrdinaryDiffEq.FirstAutodiffTgradError solve(prob, Rosenbrock23())

This throws the right error and the subsequent call works fine, but the following does not:

using FunctionWrappers, ForwardDiff, OrdinaryDiffEq, Test

const a = Float64[1.0]
function lorenz!(du, u, p, t)
    du[1] = 10.0(u[2] - u[1])
    a[1] = u[2]
    du[2] = u[1] * (28.0 - u[3]) - u[2]
    du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
u0 = [1.0; 0.0; 0.0]
tspan = (0.0, 1.0)
prob = ODEProblem(lorenz!, u0, tspan)
@test_throws OrdinaryDiffEq.FirstAutodiffJacError solve(prob, Rosenbrock23())

function lorenz!(du, u, p, t)
    du[1] = 10.0(u[2] - u[1])
    a[1] = t
    du[2] = u[1] * (28.0 - u[3]) - u[2]
    du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
u0 = [1.0; 0.0; 0.0]
tspan = (0.0,1.0)
prob = ODEProblem(lorenz!, u0, tspan)

# Throws the wrong error
@test_throws OrdinaryDiffEq.FirstAutodiffTgradError solve(prob, Rosenbrock23())

and the subsequent call errors like in the OP.

I think what this is suggesting is that function re-definition #265 stuff with FunctionWrappers somehow broke. It requires that the internal function wrapper with SciMLBase.Void(lorenz!) is called with the first function, and then when the function is re-defined and the function wrapper is rebuilt it does not seem to be correctly using the redefinition of the function, but instead reverts back to the first definition.

[vtjnash]

Sounds like a FunctionWrappers issue then? I don't think it ever gained full correct support for #265

[ChrisRackauckas]

It wasn't miscompiling on v1.9. You can see from our AD and ModelingToolkit downstream tests here https://github.com/SciML/OrdinaryDiffEq.jl/actions/runs/7333458887/job/19968912271?pr=2093 that it's a v1.10 only issue and not v1.9. I'm not sure if that requires a fix here or in FunctionWrappers.jl but this is the kind of issue I'd like to find a way to patch ASAP.

[pablosanjose]

Perhaps related to the issue yuyichao/FunctionWrappers.jl#30 ?
There the problem takes the form of a segfault upon running this snippet in 1.10 (linux)

using LinearAlgebra, FunctionWrappers
function test()
    function sfunc()
        e = eigen([1.0 + 0im ;;])
        return e
    end
    E = LinearAlgebra.Eigen{Complex{Float64}, Complex{Float64}, Matrix{Complex{Float64}}, Vector{Complex{Float64}}}
    asolver = FunctionWrappers.FunctionWrapper{E,Tuple{}}(sfunc)
    return asolver
end
s = test()
s()
using Symbolics
s()