Problem with Hyperoptim.jl

[bdas123]

Here is a snippet of my code.

model = Model(calc_sse)
addvar!(model, zeros(540), zeros(540).+100, init = x0)
alg = HyperoptAlg(NLoptAlg(:LD_MMA))
options = HyperoptOptions(sub_options = NLoptOptions(ftol_rel = 1e-2), sampler = GPSampler())
@time result = optimize(model, alg, x0, options = options)

When I run it, I get the following error:

The function Base.propertynames was overloaded for type Hyperopt.Hyperoptimizer{Hyperopt.GPSampler, NonconvexMultistart.var"#3#8"{Hyperopt.GPSampler, NonconvexNLopt.NLoptWorkspace{NonconvexCore.VecModel{NonconvexCore.Objective{NonconvexCore.var"#147#149"{typeof(calc_sse), NonconvexCore.Unflatten{Tuple{Vector{Float64}}, NonconvexCore.var"#unflatten_to_Tuple#71"{Tuple{Int64}, Tuple{Int64}, Tuple{typeof(identity)}}}}, Base.RefValue{Float64}, Set{Symbol}}, NonconvexCore.VectorOfFunctions{Vector{NonconvexCore.EqConstraint}}, NonconvexCore.VectorOfFunctions{Vector{NonconvexCore.IneqConstraint}}, NonconvexCore.VectorOfFunctions{Vector{NonconvexCore.SDConstraint}}, Vector{Float64}, Vector{Float64}, Vector{Float64}}, NLopt.Opt, Vector{Float64}, NLoptOptions{NamedTuple{(:suboptions, :ftol_rel, :ftol_abs, :xtol_rel, :xtol_abs), Tuple{NLoptOptions{NamedTuple{(), Tuple{}}}, Float64, Float64, Float64, Float64}}}, NLoptAlg{Nothing}, Base.RefValue{Int64}}, HyperoptOptions{NLoptOptions{NamedTuple{(:suboptions, :ftol_rel, :ftol_abs, :xtol_rel, :xtol_abs), Tuple{NLoptOptions{NamedTuple{(), Tuple{}}}, Float64, Float64, Float64, Float64}}}, Nothing, Nothing, Int64, Int64, Hyperopt.GPSampler, Float64, Bool}}}.
Please make sure the following methods are also overloaded for this type:
ConstructionBase.setproperties
ConstructionBase.getproperties # optional in VERSION >= julia v1.

[mohamed82008]

what versions of packages are you using, please print the result of ]st in the REPL

[bdas123]

Probably more than you asked for, but here you go!

[6e4b80f9] BenchmarkTools v1.3.1
[336ed68f] CSV v0.10.3
[d360d2e6] ChainRulesCore v1.15.0
[cdddcdb0] ChainRulesTestUtils v1.8.1
[d38c429a] Contour v0.5.7
[a93c6f00] DataFrames v1.3.4
[f6369f11] ForwardDiff v0.10.30
[28b8d3ca] GR v0.64.4
[a75be94c] GalacticOptim v3.4.0
[7073ff75] IJulia v1.23.2
[b6b21f68] Ipopt v1.0.2
[4076af6c] JuMP v1.1.0
[76087f3c] NLopt v0.6.5
[01bcebdf] Nonconvex v1.0.3
[bf347577] NonconvexIpopt v0.1.4
[11b12826] NonconvexMultistart v0.1.1
[b43a31b8] NonconvexNLopt v0.1.5
[429524aa] Optim v1.7.0
[7f7a1694] Optimization v3.6.0
[3e6eede4] OptimizationBBO v0.1.0
[36348300] OptimizationOptimJL v0.1.1
[eadc2687] Pandas v1.5.3
[f0f68f2c] PlotlyJS v0.18.8
[91a5bcdd] Plots v1.31.1
[d330b81b] PyPlot v2.10.0
[ebc72ef8] SciPy v0.1.1
[bd369af6] Tables v1.7.0
[1e6cf692] TestEnv v1.7.3
[0f1e0344] WebIO v0.8.18
[e88e6eb3] Zygote v0.6.40
[37e2e46d] LinearAlgebra

[mohamed82008]

Try ]add [email protected]. Should be fixed now.

[mohamed82008]

Since tests pass in the repo, I am fairly confident this issue is fixed now with the latest release of NonconvexMultistart. Please open another issue if you have another problem.

[bdas123]

It works, thank you for the help!