I am getting errors (see below).
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