Multithreading option not working

[ablaom]

The code below works fine if acceleration option is omitted.

using MLJ # or `MLJBase, MLJModels, MLJEnsembles` for minimal install

DecisionTreeClassifier = @iload DecisionTreeClassifier pkg=DecisionTree

atom = DecisionTreeClassifier()
model = EnsembleModel(
    atom;
    bagging_fraction=0.6,
    rng=123,
    acceleration=CPUThreads(),
    out_of_bag_measure = [log_loss, accuracy],
)

X, y = @load_iris # a table and a vector

julia> mach = machine(model, X, y) |> fit!
[ Info: Training machine(ProbabilisticEnsembleModel(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
Ensemble-building in parallel on 5 threads.
┌ Error: Problem fitting the machine machine(ProbabilisticEnsembleModel(model = DecisionTreeClassifier(max_depth = -1, …), …), …). 
└ @ MLJBase ~/MLJ/MLJBase/src/machines.jl:682
[ Info: Running type checks... 
[ Info: Type checks okay. 
ERROR: TaskFailedException
Stacktrace:
  [1] wait
    @ ./task.jl:345 [inlined]
  [2] threading_run(fun::MLJEnsembles.var"#170#threadsfor_fun#29"{MLJEnsembles.var"#170#threadsfor_fun#28#30"{typeof(MLJEnsembles.get_ensemble_and_indices), Vector{Any}, Int64, Int64, Tuple{Matrix{Float64}, Vector{UInt32}, Vector{Symbol}, CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}}}, ProgressMeter.Progress, Random.MersenneTwister, Int64, Int64, MLJDecisionTreeInterface.DecisionTreeClassifier, UnitRange{Int64}}}, static::Bool)
    @ Base.Threads ./threadingconstructs.jl:38
  [3] macro expansion
    @ ./threadingconstructs.jl:89 [inlined]
  [4] _fit(res::CPUThreads{Nothing}, func::Function, verbosity::Int64, stuff::Tuple{MLJDecisionTreeInterface.DecisionTreeClassifier, Int64, Int64, Int64, Random.MersenneTwister, ProgressMeter.Progress, Tuple{Matrix{Float64}, Vector{UInt32}, Vector{Symbol}, CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}}}})                                                                               
    @ MLJEnsembles ~/.julia/packages/MLJEnsembles/NtgQL/src/ensembles.jl:414
  [5] fit(::MLJEnsembles.ProbabilisticEnsembleModel{MLJDecisionTreeInterface.DecisionTreeClassifier}, ::Int64, ::NamedTuple{(:sepal_length, :sepal_width, :petal_length, :petal_width), NTuple{4, Vector{Float64}}}, ::CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}})      
    @ MLJEnsembles ~/.julia/packages/MLJEnsembles/NtgQL/src/ensembles.jl:476
  [6] fit_only!(mach::Machine{MLJEnsembles.ProbabilisticEnsembleModel{MLJDecisionTreeInterface.DecisionTreeClassifier}, true}; rows::Nothing, verbosity::Int64, force::Bool, composite::
Nothing)                                                                                   
    @ MLJBase ~/MLJ/MLJBase/src/machines.jl:680
  [7] fit_only!
    @ ~/MLJ/MLJBase/src/machines.jl:606 [inlined]
  [8] #fit!#63
    @ ~/MLJ/MLJBase/src/machines.jl:778 [inlined]
  [9] fit!
    @ ~/MLJ/MLJBase/src/machines.jl:775 [inlined]
 [10] |>(x::Machine{MLJEnsembles.ProbabilisticEnsembleModel{MLJDecisionTreeInterface.DecisionTreeClassifier}, true}, f::typeof(fit!))
    @ Base ./operators.jl:911
 [11] top-level scope
    @ REPL[31]:1

    nested task error: AssertionError: length(ints) == 501
    Stacktrace:
      [1] mt_setfull!(r::Random.MersenneTwister, #unused#::Type{UInt64})
        @ Random /Applications/Julia-1.8.app/Contents/Resources/julia/share/julia/stdlib/v1.8/Random/src/RNGs.jl:226
      [2] reserve1
        @ /Applications/Julia-1.8.app/Contents/Resources/julia/share/julia/stdlib/v1.8/Random/src/RNGs.jl:257 [inlined]
      [3] mt_pop!
        @ /Applications/Julia-1.8.app/Contents/Resources/julia/share/julia/stdlib/v1.8/Random/src/RNGs.jl:262 [inlined]
      [4] rand
        @ /Applications/Julia-1.8.app/Contents/Resources/julia/share/julia/stdlib/v1.8/Random/src/RNGs.jl:419 [inlined]
      [5] rand
        @ /Applications/Julia-1.8.app/Contents/Resources/julia/share/julia/stdlib/v1.8/Random/src/Random.jl:257 [inlined]
      [6] rand(rng::Random.MersenneTwister, sp::Random.SamplerRangeNDL{UInt64, Int64})
        @ Random /Applications/Julia-1.8.app/Contents/Resources/julia/share/julia/stdlib/v1.8/Random/src/generation.jl:344
      [7] rand
        @ /Applications/Julia-1.8.app/Contents/Resources/julia/share/julia/stdlib/v1.8/Random/src/Random.jl:254 [inlined]
      [8] fisher_yates_sample!(rng::Random.MersenneTwister, a::UnitRange{Int64}, x::Vector{Int64})                                                                                    
        @ StatsBase ~/.julia/packages/StatsBase/XgjIN/src/sampling.jl:199
      [9] sample!(rng::Random.MersenneTwister, a::UnitRange{Int64}, x::Vector{Int64}; replace::Bool, ordered::Bool)                                                               
        @ StatsBase ~/.julia/packages/StatsBase/XgjIN/src/sampling.jl:484
     [10] #sample#207
        @ ~/.julia/packages/StatsBase/XgjIN/src/sampling.jl:511 [inlined]
     [11] #15
        @ ./none:0 [inlined]
     [12] iterate
        @ ./generator.jl:47 [inlined]
     [13] collect_to!
        @ ./array.jl:845 [inlined]
     [14] collect_to_with_first!
        @ ./array.jl:823 [inlined]
     [15] collect(itr::Base.Generator{UnitRange{Int64}, MLJEnsembles.var"#15#17"{Int64, Int64, Random.MersenneTwister}})         
        @ Base ./array.jl:797
     [16] get_ensemble_and_indices
        @ ~/.julia/packages/MLJEnsembles/NtgQL/src/ensembles.jl:153 [inlined]
     [17] macro expansion
        @ ~/.julia/packages/MLJEnsembles/NtgQL/src/ensembles.jl:416 [inlined]
     [18] (::MLJEnsembles.var"#170#threadsfor_fun#29"{MLJEnsembles.var"#170#threadsfor_fun#28#30"{typeof(MLJEnsembles.get_ensemble_and_indices), Vector{Any}, Int64, Int64, Tuple{Matrix{Float64}, Vector{UInt32}, Vector{Symbol}, CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}}}, ProgressMeter.Progress, Random.MersenneTwister, Int64, Int64, MLJDecisionTreeInterface.DecisionTreeClassifier, UnitRange{Int64}}})(tid::Int64; onethread::Bool)
        @ MLJEnsembles ./threadingconstructs.jl:84
     [19] #170#threadsfor_fun
        @ ./threadingconstructs.jl:51 [inlined]
     [20] (::Base.Threads.var"#1#2"{MLJEnsembles.var"#170#threadsfor_fun#29"{MLJEnsembles.var"#170#threadsfor_fun#28#30"{typeof(MLJEnsembles.get_ensemble_and_indices), Vector{Any}, Int64, Int64, Tuple{Matrix{Float64}, Vector{UInt32}, Vector{Symbol}, CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}}}, ProgressMeter.Progress, Random.MersenneTwister, Int64, Int64, MLJDecisionTreeInterface.DecisionTreeClassifier, UnitRange{Int64}}}, Int64})()
        @ Base.Threads ./threadingconstructs.jl:30