`OptimizationFunction` with `AutoForwardDiff` doesn't work with sparse `ODEProblem`

[tpdsantos]

Describe the bug 🐞

When trying to optimize an ODEProblem with sparse=true, the KLUFactorization gives an error with sparse matrices. With sparse=false the optimization runs as expected.

Minimal Reproducible Example 👇

using ModelingToolkit, OrdinaryDiffEq, SymbolicIndexingInterface
using Optimization, OptimizationOptimJL, ForwardDiff

using SciMLStructures: Tunable, replace
using ModelingToolkit: t_nounits as t, D_nounits as D

@mtkmodel robertson begin
    @parameters begin
        k[1:3] = [0.04, 3e7, 1e4]
    end
    @variables begin
        y(t)[1:3] = [1.0, 0.0, nothing]
    end
    @equations begin
        D(y)[1] ~ -k[1]*y[1] + k[3]*y[2]*y[3]
        D(y)[2] ~  k[1]*y[1] - k[3]*y[2]*y[3] - k[2]*y[2]*y[2]
        sum([y[i] for i in 1:3]) ~ 1
    end
end

@mtkbuild m = robertson()
prob = ODEProblem(m, [], (0.0, 1000), jac=true, sparse=true)

setter! = setp(m, (m.k[1], m.k[2], m.k[3]))
p0guess = [0.04, 3e7, 1e4]
ps = parameter_values(prob)
ps = replace(Tunable(), ps, Any[j for j in ps.tunable])
newprob = remake(prob, p = ps)

sol = solve(newprob, Rodas5P())
tsteps = copy(sol.t)
calc = Array(sol)
data = calc .+ 0.01*randn(size(calc))

function loss(x, p)
    odeprob = p[1]
    tsteps  = p[2]
    data    = p[3]

    setter!(odeprob, (x[1], x[2], x[3]))
    sol = solve(odeprob, Rodas5P(), saveat=tsteps)
    return sum(abs2, data .- Array(sol))
end

optfun = OptimizationFunction(loss, AutoForwardDiff())
optprob = OptimizationProblem(optfun, p0guess, (newprob, tsteps, data))
optsol = solve(optprob, BFGS())

Error & Stacktrace ⚠️

ERROR: MethodError: no method matching KLU.KLUFactorization(::SparseArrays.SparseMatrixCSC{ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 3}, Int64})
The type `KLU.KLUFactorization` exists, but no method is defined for this combination of argument types when trying to construct it.

Closest candidates are:
  KLU.KLUFactorization(::Any, ::Any, ::Any, ::Any)
   @ KLU C:\Users\tiago.santos\.julia\packages\KLU\Eh2kE\src\KLU.jl:133
  KLU.KLUFactorization(::SparseArrays.SparseMatrixCSC{Tv, Ti}) where {Tv<:Union{Float64, ComplexF64}, Ti<:Union{Int32, Int64}}
   @ KLU C:\Users\tiago.santos\.julia\packages\KLU\Eh2kE\src\KLU.jl:167

Stacktrace:
  [1] init_cacheval(alg::LinearSolve.KLUFactorization, A::SparseArrays.SparseMatrixCSC{…}, b::Vector{…}, u::Vector{…}, Pl::LinearSolve.InvPreconditioner{…}, Pr::LinearAlgebra.Diagonal{…}, maxiters::Int64, abstol::ForwardDiff.Dual{…}, reltol::ForwardDiff.Dual{…}, verbose::Bool, assumptions::LinearSolve.OperatorAssumptions{…})
    @ LinearSolve C:\Users\tiago.santos\.julia\packages\LinearSolve\8iclj\src\factorization.jl:897
  [2] macro expansion
    @ C:\Users\tiago.santos\.julia\packages\LinearSolve\8iclj\src\default.jl:334 [inlined]
  [3] init_cacheval(alg::LinearSolve.DefaultLinearSolver, A::SparseArrays.SparseMatrixCSC{…}, b::Vector{…}, u::Vector{…}, Pl::LinearSolve.InvPreconditioner{…}, Pr::LinearAlgebra.Diagonal{…}, maxiters::Int64, abstol::ForwardDiff.Dual{…}, reltol::ForwardDiff.Dual{…}, verbose::Bool, assump::LinearSolve.OperatorAssumptions{…})
    @ LinearSolve C:\Users\tiago.santos\.julia\packages\LinearSolve\8iclj\src\default.jl:317
  [4] init(::LinearProblem{…}, ::LinearSolve.DefaultLinearSolver; alias_A::Bool, alias_b::Bool, abstol::Float64, reltol::Float64, maxiters::Int64, verbose::Bool, Pl::LinearSolve.InvPreconditioner{…}, Pr::LinearAlgebra.Diagonal{…}, assumptions::LinearSolve.OperatorAssumptions{…}, sensealg::LinearSolve.LinearSolveAdjoint{…}, kwargs::@Kwargs{})
    @ LinearSolve C:\Users\tiago.santos\.julia\packages\LinearSolve\8iclj\src\common.jl:201
  [5] init(::LinearProblem{…}, ::Nothing; assumptions::LinearSolve.OperatorAssumptions{…},
 kwargs::@Kwargs{…})
    @ LinearSolve C:\Users\tiago.santos\.julia\packages\LinearSolve\8iclj\src\default.jl:296
  [6] alg_cache(alg::Rodas5P{…}, u::Vector{…}, rate_prototype::Vector{…}, ::Type{…}, ::Type{…}, ::Type{…}, uprev::Vector{…}, uprev2::Vector{…}, f::ODEFunction{…}, t::Float64, dt::Float64, reltol::Float64, p::MTKParameters{…}, calck::Bool, ::Val{…})
    @ OrdinaryDiffEqRosenbrock C:\Users\tiago.santos\.julia\packages\OrdinaryDiffEqRosenbrock\6r4An\src\rosenbrock_caches.jl:780
  [7] __init(prob::ODEProblem{…}, alg::Rodas5P{…}, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{…}; saveat::Vector{…}, tstops::Tuple{}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Nothing, callback::Nothing, dense::Bool, calck::Bool, dt::Float64, dtmin::Float64, dtmax::Float64, force_dtmin::Bool, adaptive::Bool, gamma::Rational{…}, abstol::Nothing, reltol::Nothing, qmin::Rational{…}, qmax::Int64, qsteady_min::Int64, qsteady_max::Rational{…}, beta1::Nothing, beta2::Nothing, qoldinit::Rational{…}, controller::Nothing, fullnormalize::Bool, failfactor::Int64, maxiters::Int64, internalnorm::typeof(DiffEqBase.ODE_DEFAULT_NORM), internalopnorm::typeof(LinearAlgebra.opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), verbose::Bool, timeseries_errors::Bool, dense_errors::Bool, advance_to_tstop::Bool, stop_at_next_tstop::Bool, initialize_save::Bool, progress::Bool, progress_steps::Int64, progress_name::String, progress_message::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), progress_id::Symbol, userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias::ODEAliasSpecifier, initializealg::OrdinaryDiffEqCore.DefaultInit, kwargs::@Kwargs{})
    @ OrdinaryDiffEqCore C:\Users\tiago.santos\.julia\packages\OrdinaryDiffEqCore\33WQj\src\solve.jl:406
  [8] __solve(::ODEProblem{…}, ::Rodas5P{…}; kwargs::@Kwargs{…})
    @ OrdinaryDiffEqCore C:\Users\tiago.santos\.julia\packages\OrdinaryDiffEqCore\33WQj\src\solve.jl:6
  [9] solve_call(_prob::ODEProblem{…}, args::Rodas5P{…}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@Kwargs{…})
    @ DiffEqBase C:\Users\tiago.santos\.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:634
 [10] solve_up(prob::ODEProblem{…}, sensealg::Nothing, u0::Vector{…}, p::MTKParameters{…},
 args::Rodas5P{…}; kwargs::@Kwargs{…})
    @ DiffEqBase C:\Users\tiago.santos\.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1122
 [11] solve_up
    @ C:\Users\tiago.santos\.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1101 [inlined]
 [12] solve(prob::ODEProblem{…}, args::Rodas5P{…}; sensealg::Nothing, u0::Nothing, p::Nothing, wrap::Val{…}, kwargs::@Kwargs{…})
    @ DiffEqBase C:\Users\tiago.santos\.julia\packages\DiffEqBase\R2Vjs\src\solve.jl:1038
 [13] (::var"#loss#263"{…})(x::Vector{…}, p::Tuple{…})
    @ Main C:\Users\tiago.santos\OneDrive - iBET\WIP\Immobilized Benzonase\test-optim-sparsity.jl:53
 [14] FixTail
    @ C:\Users\tiago.santos\.julia\packages\DifferentiationInterface\UWUBZ\src\utils\context.jl:7 [inlined]
 [15] vector_mode_dual_eval!
    @ C:\Users\tiago.santos\.julia\packages\ForwardDiff\UBbGT\src\apiutils.jl:24 [inlined]
 [16] vector_mode_gradient!(result::Vector{…}, f::DifferentiationInterface.FixTail{…}, x::Vector{…}, cfg::ForwardDiff.GradientConfig{…})
    @ ForwardDiff C:\Users\tiago.santos\.julia\packages\ForwardDiff\UBbGT\src\gradient.jl:98
 [17] gradient!
    @ C:\Users\tiago.santos\.julia\packages\ForwardDiff\UBbGT\src\gradient.jl:39 [inlined]
 [18] gradient!(f::var"#loss#263"{…}, grad::Vector{…}, prep::DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{…}, backend::AutoForwardDiff{…}, x::Vector{…}, contexts::DifferentiationInterface.Constant{…})
    @ DifferentiationInterfaceForwardDiffExt C:\Users\tiago.santos\.julia\packages\DifferentiationInterface\UWUBZ\ext\DifferentiationInterfaceForwardDiffExt\onearg.jl:362
 [19] (::OptimizationBase.var"#grad#16"{…})(res::Vector{…}, θ::Vector{…})
    @ OptimizationBase C:\Users\tiago.santos\.julia\packages\OptimizationBase\gvXsf\src\OptimizationDIExt.jl:28
 [20] (::OptimizationOptimJL.var"#8#14"{…})(G::Vector{…}, θ::Vector{…})
    @ OptimizationOptimJL C:\Users\tiago.santos\.julia\packages\OptimizationOptimJL\e3bUa\src\OptimizationOptimJL.jl:166
 [21] value_gradient!!(obj::TwiceDifferentiable{Float64, Vector{…}, Matrix{…}, Vector{…}},
 x::Vector{Float64})
    @ NLSolversBase C:\Users\tiago.santos\.julia\packages\NLSolversBase\kavn7\src\interface.jl:82
 [22] initial_state(method::BFGS{…}, options::Optim.Options{…}, d::TwiceDifferentiable{…},
 initial_x::Vector{…})
    @ Optim C:\Users\tiago.santos\.julia\packages\Optim\HvjCd\src\multivariate\solvers\first_order\bfgs.jl:94
 [23] optimize(d::TwiceDifferentiable{…}, initial_x::Vector{…}, method::BFGS{…}, options::Optim.Options{…})
    @ Optim C:\Users\tiago.santos\.julia\packages\Optim\HvjCd\src\multivariate\optimize\optimize.jl:36
 [24] __solve(cache::OptimizationCache{…})
    @ OptimizationOptimJL C:\Users\tiago.santos\.julia\packages\OptimizationOptimJL\e3bUa\src\OptimizationOptimJL.jl:218
 [25] solve!(cache::OptimizationCache{…})
    @ SciMLBase C:\Users\tiago.santos\.julia\packages\SciMLBase\Pma4a\src\solve.jl:187
 [26] solve(::OptimizationProblem{…}, ::BFGS{…}; kwargs::@Kwargs{})
    @ SciMLBase C:\Users\tiago.santos\.julia\packages\SciMLBase\Pma4a\src\solve.jl:95
 [27] solve(::OptimizationProblem{…}, ::BFGS{…})
    @ SciMLBase C:\Users\tiago.santos\.julia\packages\SciMLBase\Pma4a\src\solve.jl:92
 [28] sparsity_optim(; isplot::Bool)
    @ Main C:\Users\tiago.santos\OneDrive - iBET\WIP\Immobilized Benzonase\test-optim-sparsity.jl:60
 [29] sparsity_optim()
    @ Main C:\Users\tiago.santos\OneDrive - iBET\WIP\Immobilized Benzonase\test-optim-sparsity.jl:11
 [30] top-level scope
    @ REPL[105]:1
Some type information was truncated. Use `show(err)` to see complete types.

Environment (please complete the following information):

• Output of using Pkg; Pkg.status()

Status `C:\Users\tiago.santos\.julia\environments\v1.11\Project.toml`
  [47edcb42] ADTypes v1.12.1
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⌃ [e9467ef8] GLMakie v0.10.18
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  [961ee093] ModelingToolkit v9.62.0
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Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated`

• Output of using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)

hy use `status --outdated`

julia> using Pkg; Pkg.status(; mode=PKGMODE_MANIFEST)
Status `C:\Users\tiago.santos\.julia\environments\v1.11\Manifest.toml`
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  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.1+2
  [efcefdf7] PCRE2_jll v10.42.0+1
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`

• Output of versioninfo()

Julia Version 1.11.3
Commit d63adeda50 (2025-01-21 19:42 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 8 × Intel(R) Core(TM) i5-10310U CPU @ 1.70GHz
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, skylake)
Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)

Additional context

Add any other context about the problem here.

[ChrisRackauckas]

Needs using Sparspak now with LinearSolve.jl v3. We should get a better error message on that.

[tpdsantos]

I'm trying to replicate this in Ubuntu 24.04 and adding using Sparspak does not solve the issue... Also, the default LinearSolve is version 2.39

[ChrisRackauckas]

can you show me what you ran? and try v3

[tpdsantos]

I'm trying to install v3 first, but it says that in order to install it, I need DifferentialEquations v5 or v6... I'll try to downgrade to see if it's fixed

[tpdsantos]

]I ran a fresh install of Julia with only the necessary packages. While trying to install LinearSolve v3 I get the following compatibility error:

ERROR: Unsatisfiable requirements detected for package RecursiveArrayTools [731186ca]:
 RecursiveArrayTools [731186ca] log:
 ├─possible versions are: 0.16.0 - 3.29.0 or uninstalled
 ├─restricted by compatibility requirements with LinearSolve [7ed4a6bd] to versions: 3.8.0 - 3.29.0 or uninstalled, leaving only versions: 3.8.0 - 3.29.0
 │ └─LinearSolve [7ed4a6bd] log:
 │   ├─possible versions are: 0.1.0 - 3.0.0 or uninstalled
 │   ├─restricted to versions * by project [43a2c169], leaving only versions: 0.1.0 - 3.0.0
 │   │ └─project [43a2c169] log:
 │   │   ├─possible versions are: 0.0.0 or uninstalled
 │   │   └─project [43a2c169] is fixed to version 0.0.0
 │   └─restricted to versions 3 by an explicit requirement, leaving only versions: 3.0.0
 └─restricted by compatibility requirements with DifferentialEquations [0c46a032] to versions: 0.16.0 - 2.38.10 — no versions left
   └─DifferentialEquations [0c46a032] log:
     ├─possible versions are: 5.0.0 - 7.15.0 or uninstalled
     ├─restricted to versions * by project [43a2c169], leaving only versions: 5.0.0 - 7.15.0
     │ └─project [43a2c169] log: see above
     └─restricted by compatibility requirements with LinearSolve [7ed4a6bd] to versions: 5.0.0 - 6.20.0 or uninstalled, leaving only versions: 5.0.0 - 6.20.0
       └─LinearSolve [7ed4a6bd] log: see above

The packages that are installed:

@v1.11) pkg> status
Status `~/.julia/environments/v1.11/Project.toml`
  [336ed68f] CSV v0.10.15
⌃ [13f3f980] CairoMakie v0.12.18
  [501788e0] CollocationMethods v0.1.0 `../../../OneDrive/WIP/Repositories/CollocationMethods`
  [a93c6f00] DataFrames v1.7.0
   [0c46a032] DifferentialEquations v7.16.0
  [f6369f11] ForwardDiff v0.10.38
⌃ [e9467ef8] GLMakie v0.10.18
⌅ [7ed4a6bd] LinearSolve v2.39.0
  [2fda8390] LsqFit v0.15.0
  [65ed5ab3] ModelingBI v0.1.0 `../../../OneDrive/WIP/Repositories/ModelingBI`
  [961ee093] ModelingToolkit v9.62.0
  [f5f84d89] NumericalTools v0.1.0 `../../../OneDrive/WIP/Repositories/NumericalTools`
  [7f7a1694] Optimization v4.1.1
  [36348300] OptimizationOptimJL v0.4.1
  [1dea7af3] OrdinaryDiffEq v6.91.0
  [53ae85a6] SciMLStructures v1.6.1
  [e56a9233] Sparspak v0.3.9
  [2efcf032] SymbolicIndexingInterface v0.3.37
  [3bb67fe8] TranscodingStreams v0.11.3
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated`

[ChrisRackauckas]

Already latest releases should untangle that now.

To be clear, this shouldn't be an issue even on the earlier versions, but at least I'm testing on v3 just fine.

Let me know if it's not just a versioning thing. I'll be at an Intel CPU in a bit and it could be something BLAS-dependent.

[tpdsantos]

It fixed the KLUFactorization issue but now I have this error:

ERROR: UndefVarError: `DefaultLinearSolver` not defined in `LinearSolveSparseArraysExt`
Suggestion: check for spelling errors or missing imports.
Stacktrace:
  [1] defaultalg(A::SparseArrays.SparseMatrixCSC{ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 3}, Int64}, b::Vector{ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 3}}, assump::OperatorAssumptions{Bool})
    @ LinearSolveSparseArraysExt ~/.julia/packages/LinearSolve/SFMdw/ext/LinearSolveSparseArraysExt.jl:49
  [2] init(::LinearProblem{…}, ::Nothing; assumptions::OperatorAssumptions{…}, kwargs::@Kwargs{…})
    @ LinearSolve ~/.julia/packages/LinearSolve/SFMdw/src/default.jl:270
  [3] init
    @ ~/.julia/packages/LinearSolve/SFMdw/src/default.jl:266 [inlined]
  [4] alg_cache(alg::Rodas5P{…}, u::Vector{…}, rate_prototype::Vector{…}, ::Type{…}, ::Type{…}, ::Type{…}, uprev::Vector{…}, uprev2::Vector{…}, f::ODEFunction{…}, t::Float64, dt::Float64, reltol::ForwardDiff.Dual{…}, p::MTKParameters{…}, calck::Bool, ::Val{…})
    @ OrdinaryDiffEqRosenbrock ~/.julia/packages/OrdinaryDiffEqRosenbrock/bW9xh/src/rosenbrock_caches.jl:780
  [5] __init(prob::ODEProblem{…}, alg::Rodas5P{…}, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{…}; saveat::Vector{…}, tstops::Tuple{}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Nothing, callback::Nothing, dense::Bool, calck::Bool, dt::Float64, dtmin::Float64, dtmax::Float64, force_dtmin::Bool, adaptive::Bool, gamma::Rational{…}, abstol::Nothing, reltol::Nothing, qmin::Rational{…}, qmax::Int64, qsteady_min::Int64, qsteady_max::Rational{…}, beta1::Nothing, beta2::Nothing, qoldinit::Rational{…}, controller::Nothing, fullnormalize::Bool, failfactor::Int64, maxiters::Int64, internalnorm::typeof(DiffEqBase.ODE_DEFAULT_NORM), internalopnorm::typeof(LinearAlgebra.opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), verbose::Bool, timeseries_errors::Bool, dense_errors::Bool, advance_to_tstop::Bool, stop_at_next_tstop::Bool, initialize_save::Bool, progress::Bool, progress_steps::Int64, progress_name::String, progress_message::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), progress_id::Symbol, userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias::ODEAliasSpecifier, initializealg::OrdinaryDiffEqCore.DefaultInit, kwargs::@Kwargs{})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/oa4Vj/src/solve.jl:406
  [6] __init (repeats 5 times)
    @ ~/.julia/packages/OrdinaryDiffEqCore/oa4Vj/src/solve.jl:11 [inlined]
  [7] __solve(::ODEProblem{…}, ::Rodas5P{…}; kwargs::@Kwargs{…})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/oa4Vj/src/solve.jl:6
  [8] __solve
    @ ~/.julia/packages/OrdinaryDiffEqCore/oa4Vj/src/solve.jl:1 [inlined]
  [9] #solve_call#35
    @ ~/.julia/packages/DiffEqBase/TQ6hN/src/solve.jl:635 [inlined]
 [10] solve_up(prob::ODEProblem{…}, sensealg::Nothing, u0::Vector{…}, p::MTKParameters{…}, args::Rodas5P{…}; kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/TQ6hN/src/solve.jl:1124
 [11] solve_up
    @ ~/.julia/packages/DiffEqBase/TQ6hN/src/solve.jl:1102 [inlined]
 [12] solve(prob::ODEProblem{…}, args::Rodas5P{…}; sensealg::Nothing, u0::Nothing, p::Nothing, wrap::Val{…}, kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/TQ6hN/src/solve.jl:1039
 [13] (::var"#loss#10"{SymbolicIndexingInterface.ParameterHookWrapper{…}})(x::Vector{ForwardDiff.Dual{…}}, args::Tuple{ODESystem, ODEProblem{…}, Vector{…}, Vector{…}})
    @ Main ~/OneDrive/WIP/Immobilized Benzonase/BI-optims.jl:93
 [14] #7
    @ ~/OneDrive/WIP/Immobilized Benzonase/BI-optims.jl:114 [inlined]
 [15] FixTail
    @ ~/.julia/packages/DifferentiationInterface/srtnM/src/utils/context.jl:7 [inlined]
 [16] vector_mode_dual_eval!
    @ ~/.julia/packages/ForwardDiff/UBbGT/src/apiutils.jl:24 [inlined]
 [17] vector_mode_gradient!(result::Vector{Float64}, f::DifferentiationInterface.FixTail{var"#7#12"{…}, Tuple{…}}, x::Vector{Float64}, cfg::ForwardDiff.GradientConfig{ForwardDiff.Tag{…}, Float64, 3, Vector{…}})
    @ ForwardDiff ~/.julia/packages/ForwardDiff/UBbGT/src/gradient.jl:98
 [18] gradient!
    @ ~/.julia/packages/ForwardDiff/UBbGT/src/gradient.jl:39 [inlined]
 [19] gradient!(f::var"#7#12"{…}, grad::Vector{…}, prep::DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{…}, backend::AutoForwardDiff{…}, x::Vector{…}, contexts::DifferentiationInterface.Constant{…})
    @ DifferentiationInterfaceForwardDiffExt ~/.julia/packages/DifferentiationInterface/srtnM/ext/DifferentiationInterfaceForwardDiffExt/onearg.jl:362
 [20] (::OptimizationBase.var"#grad#16"{SciMLBase.NullParameters, OptimizationFunction{…}, AutoForwardDiff{…}})(res::Vector{Float64}, θ::Vector{Float64})
    @ OptimizationBase ~/.julia/packages/OptimizationBase/gvXsf/src/OptimizationDIExt.jl:28
 [21] (::OptimizationOptimJL.var"#19#23"{OptimizationCache{…}, OptimizationOptimJL.var"#18#22"{…}})(G::Vector{Float64}, θ::Vector{Float64})
    @ OptimizationOptimJL ~/.julia/packages/OptimizationOptimJL/e3bUa/src/OptimizationOptimJL.jl:285
 [22] value_gradient!!(obj::OnceDifferentiable{Float64, Vector{Float64}, Vector{Float64}}, x::Vector{Float64})
    @ NLSolversBase ~/.julia/packages/NLSolversBase/kavn7/src/interface.jl:82
 [23] value_gradient!!(bw::Optim.BarrierWrapper{OnceDifferentiable{Float64, Vector{Float64}, Vector{Float64}}, Optim.BoxBarrier{Vector{Float64}, Vector{Float64}}, Float64, Float64, Vector{Float64}}, x::Vector{Float64})
    @ Optim ~/.julia/packages/Optim/HvjCd/src/multivariate/solvers/constrained/fminbox.jl:81
 [24] initial_state(method::BFGS{…}, options::Optim.Options{…}, d::Optim.BarrierWrapper{…}, initial_x::Vector{…})
    @ Optim ~/.julia/packages/Optim/HvjCd/src/multivariate/solvers/first_order/bfgs.jl:94
 [25] optimize(df::OnceDifferentiable{…}, l::Vector{…}, u::Vector{…}, initial_x::Vector{…}, F::Fminbox{…}, options::Optim.Options{…})
    @ Optim ~/.julia/packages/Optim/HvjCd/src/multivariate/solvers/constrained/fminbox.jl:322
 [26] __solve(cache::OptimizationCache{OptimizationFunction{…}, OptimizationBase.ReInitCache{…}, Vector{…}, Vector{…}, Nothing, Nothing, Nothing, Fminbox{…}, Bool, var"#track_results#11", Nothing})
    @ OptimizationOptimJL ~/.julia/packages/OptimizationOptimJL/e3bUa/src/OptimizationOptimJL.jl:312
 [27] solve!(cache::OptimizationCache{OptimizationFunction{…}, OptimizationBase.ReInitCache{…}, Vector{…}, Vector{…}, Nothing, Nothing, Nothing, Fminbox{…}, Bool, var"#track_results#11", Nothing})
    @ SciMLBase ~/.julia/packages/SciMLBase/YTOjh/src/solve.jl:187
 [28] solve(::OptimizationProblem{…}, ::BFGS{…}; kwargs::@Kwargs{…})
    @ SciMLBase ~/.julia/packages/SciMLBase/YTOjh/src/solve.jl:95
 [29] CST_ED_optim_prob(linsolver::AutoForwardDiff{nothing, Nothing}; isplot::Bool)
    @ Main ~/OneDrive/WIP/Immobilized Benzonase/BI-optims.jl:119
 [30] CST_ED_optim_prob(linsolver::AutoForwardDiff{nothing, Nothing})
    @ Main ~/OneDrive/WIP/Immobilized Benzonase/BI-optims.jl:65
 [31] top-level scope
    @ REPL[12]:1
Some type information was truncated. Use `show(err)` to see complete types.

Do I need to add any extra argument?

Output of versioninfo()

Julia Version 1.11.3
Commit d63adeda50d (2025-01-21 19:42 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × Intel(R) Xeon(R) Gold 6242 CPU @ 2.80GHz
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, cascadelake)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

[tpdsantos]

after new updates, the old error message about the KLU.Factorization came back, running the exact same problem:

ERROR: MethodError: no method matching LinearSolveSparseArraysExt.KLU.KLUFactorization(::SparseArrays.SparseMatrixCSC{ForwardDiff.Dual{ForwardDiff.Tag{…}, Float64, 3}, Int64})
The type `LinearSolveSparseArraysExt.KLU.KLUFactorization` exists, but no method is defined for this combination of argument types when trying to construct it.

Closest candidates are:
  LinearSolveSparseArraysExt.KLU.KLUFactorization(::Any, ::Any, ::Any, ::Any)
   @ LinearSolveSparseArraysExt ~/.julia/packages/LinearSolve/QuCP8/src/KLU/klu.jl:140
  LinearSolveSparseArraysExt.KLU.KLUFactorization(::SparseArrays.SparseMatrixCSC{Tv, Ti}) where {Tv<:Union{Float64, ComplexF64}, Ti<:Union{Int32, Int64}}
   @ LinearSolveSparseArraysExt ~/.julia/packages/LinearSolve/QuCP8/src/KLU/klu.jl:174

Packages installed:

julia> using Pkg; Pkg.status()
Status `~/.julia/environments/v1.11/Project.toml`
  [6e4b80f9] BenchmarkTools v1.6.0
  [336ed68f] CSV v0.10.15
⌃ [13f3f980] CairoMakie v0.12.18
  [501788e0] CollocationMethods v0.1.0 `../../../OneDrive/WIP/Repositories/CollocationMethods`
  [a93c6f00] DataFrames v1.7.0
  [0c46a032] DifferentialEquations v7.16.0
  [7da242da] Enzyme v0.13.30
  [f6369f11] ForwardDiff v0.10.38
⌃ [e9467ef8] GLMakie v0.10.18
  [929cbde3] LLVM v9.2.0
  [7ed4a6bd] LinearSolve v3.3.1
  [2fda8390] LsqFit v0.15.0
  [65ed5ab3] ModelingBI v0.1.0 `../../../OneDrive/WIP/Repositories/ModelingBI`
  [961ee093] ModelingToolkit v9.64.0
  [f5f84d89] NumericalTools v0.1.0 `../../../OneDrive/WIP/Repositories/NumericalTools`
  [7f7a1694] Optimization v4.1.1
  [36348300] OptimizationOptimJL v0.4.1
  [1dea7af3] OrdinaryDiffEq v6.91.0
  [37e2e3b7] ReverseDiff v1.15.3
  [295af30f] Revise v3.7.2
  [1ed8b502] SciMLSensitivity v7.74.0
  [53ae85a6] SciMLStructures v1.6.1
  [e56a9233] Sparspak v0.3.9
  [2efcf032] SymbolicIndexingInterface v0.3.37
  [3bb67fe8] TranscodingStreams v0.11.3
⌃ [e88e6eb3] Zygote v0.6.75
Info Packages marked with ⌃ have new versions available and may be upgradable.

[ChrisRackauckas]

This now gives the right error message and properly changes to Sparspak when added.