Errors when running julia --project -i scripts/basic-example.jl

[wolski]

Error when running wew-mac:TuringModels.jl witoldwolski$ julia --project -i scripts/basic-example.jl

I am getting errors (see below).

However, starting the Julia REPL with julia and no --project options and copy-pasting the code from basic-example.jl all works nicely.

When starting julia with the --project option wew-mac:TuringModels.jl witoldwolski$ julia --project and copy pasting the same code from basic-example.jl I am also getting the error.

wew-mac:TuringModels.jl witoldwolski$ julia --project -i scripts/basic-example.jl
Sampling 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| Time: 0:00:01
ERROR: LoadError: MethodError: no method matching ADgradient(::Val{:ForwardDiff}, ::WARNING: both Bijectors and Base export "stack"; uses of it in module Turing must be qualified
Turing.LogDensityFunction{DynamicPPL.TypedVarInfo{NamedTuple{(:s, :m), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:s, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:s, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:m, Setfield.IdentityLens}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:m, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{typeof(gdemo), (:x, :y), (), (), Tuple{Float64, Int64}, Tuple{}, DynamicPPL.DefaultContext}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}; gradientconfig::ForwardDiff.GradientConfig{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 2, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 2}}})

Closest candidates are:
  ADgradient(::Val{:ForwardDiff}, ::Any; chunk, tag, x) got unsupported keyword argument "gradientconfig"
   @ LogDensityProblemsADForwardDiffExt ~/.julia/packages/LogDensityProblemsAD/pwc6T/ext/LogDensityProblemsADForwardDiffExt.jl:98
  ADgradient(::Val{kind}, ::Any; kwargs...) where kind
   @ LogDensityProblemsAD ~/.julia/packages/LogDensityProblemsAD/pwc6T/src/LogDensityProblemsAD.jl:68
  ADgradient(::Turing.Essential.ReverseDiffAD{false}, ::Turing.LogDensityFunction) got unsupported keyword argument "gradientconfig"
   @ Turing ~/.julia/packages/Turing/UsWJl/src/essential/ad.jl:115
  ...

Stacktrace:
  [1] kwerr(::NamedTuple{(:gradientconfig,), Tuple{ForwardDiff.GradientConfig{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 2, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.TuringTag, Float64}, Float64, 2}}}}}, ::Function, ::Val{:ForwardDiff}, ::Turing.LogDensityFunction{DynamicPPL.TypedVarInfo{NamedTuple{(:s, :m), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:s, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:s, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:m, Setfield.IdentityLens}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:m, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{typeof(gdemo), (:x, :y), (), (), Tuple{Float64, Int64}, Tuple{}, DynamicPPL.DefaultContext}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext})
    @ Base ./error.jl:165
  [2] ADgradient(ad::Turing.Essential.ForwardDiffAD{0, true}, ℓ::Turing.LogDensityFunction{DynamicPPL.TypedVarInfo{NamedTuple{(:s, :m), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:s, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:s, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:m, Setfield.IdentityLens}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:m, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{typeof(gdemo), (:x, :y), (), (), Tuple{Float64, Int64}, Tuple{}, DynamicPPL.DefaultContext}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext})
    @ Turing.Essential ~/.julia/packages/Turing/UsWJl/src/essential/ad.jl:102
  [3] ADgradient(ℓ::Turing.LogDensityFunction{DynamicPPL.TypedVarInfo{NamedTuple{(:s, :m), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:s, Setfield.IdentityLens}, Int64}, Vector{InverseGamma{Float64}}, Vector{AbstractPPL.VarName{:s, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:m, Setfield.IdentityLens}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:m, Setfield.IdentityLens}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{typeof(gdemo), (:x, :y), (), (), Tuple{Float64, Int64}, Tuple{}, DynamicPPL.DefaultContext}, DynamicPPL.Sampler{NUTS{Turing.Essential.ForwardDiffAD{0}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext})
    @ Turing.Essential ~/.julia/packages/Turing/UsWJl/src/essential/ad.jl:82

[rikhuijzer]

This looks like an issue inside Turing.jl. I suspect that your Turing version between the —project environment and your global (no —project) is different.

I’ll close this issue as it seems unrelated to TuringModels.jl. Feel free to reopen if you believe the issue isn’t caused by Turing.jl itself

[rikhuijzer]

Oh my bad. The problem is probably just that this repository is using a very old version of Turing which isn’t compatible with the newest Julia version. I’ll add updating this repo to my task list

[wolski]

@rikhuijzer OK. Can leave the issue open until you update the repo?

[rikhuijzer]

I've been thinking about my time and where I should spend it and think it's probably not at this project. So I'm gonna go ahead and archive this repository.