Can't get a user defined function to work in my Turing Model specification

DoktorMike · June 24, 2021, 7:33am

I have this simple Turing model which I cannot get to work. The full MWE is given below.

using Turing, Distributions

function myfilter(x::AbstractVector, λ)
    xnew = x
    xnew[1] = x[1]
    for i in 2:length(x)
        xnew[i] = x[i] + λ*xnew[i-1]
    end
    xnew
end

# Make a simple transformed linear regression with parameter λ = 0.5 and β = 3
x = rand(100)*1000
x[rand(1:length(x), 50)] .= 0
y = 3*myfilter(x, 0.5) + randn(100) * 100

# Specify the turing model
@model mwe(x, y) = begin
    β ~ Normal(0, 5)
    λ ~ Beta(1,1)
    σ ~ Normal(3, 3)
    xx = myfilter(x, λ)
    for i in 1:length(y)
        μ = β*xx[i]
        y[i] ~ Normal(μ, exp(σ))
    end
end

# Sample it
model = mwe(x, y)
nchains = 4
chain = sample(model, NUTS(0.65), MCMCThreads(), 3_000, nchains);
chain

I get a long error message when trying to run this model.
However, if I define a dummy myfilter function like this

function myfilter(x::AbstractVector, λ)
    xnew = x .+ λ
    xnew
end

it works. So I’m wondering why the myfilter function doesn’t work in the original example? Is it because I’m indexing into the vector and changing data?

The full error message is here:

TaskFailedException

    nested task error: TaskFailedException
    Stacktrace:
     [1] wait
       @ ./task.jl:322 [inlined]
     [2] threading_run(func::Function)
       @ Base.Threads ./threadingconstructs.jl:34
     [3] macro expansion
       @ ./threadingconstructs.jl:93 [inlined]
     [4] macro expansion
       @ ~/.julia/packages/AbstractMCMC/ByHEr/src/sample.jl:338 [inlined]
     [5] (::AbstractMCMC.var"#31#41"{Bool, Base.Iterators.Pairs{Symbol, UnionAll, Tuple{Symbol}, NamedTuple{(:chain_type,), Tuple{UnionAll}}}, Int64, Int64, Vector{Any}, Vector{UInt64}, Vector{DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}}, Vector{DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}}, Vector{Random._GLOBAL_RNG}})()
       @ AbstractMCMC ./task.jl:411

        nested task error: TypeError: in typeassert, expected Float64, got a value of type ForwardDiff.Dual{Nothing, Float64, 3}
        Stacktrace:
          [1] setindex!(A::Vector{Float64}, x::ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}, i1::Int64)
            @ Base ./array.jl:839
          [2] myfilter
            @ ./REPL[108]:5 [inlined]
          [3] #21
            @ ./REPL[114]:5 [inlined]
          [4] (::var"#21#22")(__rng__::Random._GLOBAL_RNG, __model__::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, __varinfo__::DynamicPPL.ThreadSafeVarInfo{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}}}, ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}, Vector{Base.RefValue{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}}}, __sampler__::DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, __context__::DynamicPPL.DefaultContext, x::Vector{Float64}, y::Vector{Float64})
            @ Main ./none:0
          [5] macro expansion
            @ ~/.julia/packages/DynamicPPL/emAbx/src/model.jl:0 [inlined]
          [6] _evaluate
            @ ~/.julia/packages/DynamicPPL/emAbx/src/model.jl:150 [inlined]
          [7] evaluate_threadsafe
            @ ~/.julia/packages/DynamicPPL/emAbx/src/model.jl:140 [inlined]
          [8] (::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}})(rng::Random._GLOBAL_RNG, varinfo::DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}, Vector{Set{DynamicPPL.Selector}}}}}, ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}, sampler::DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, context::DynamicPPL.DefaultContext)
            @ DynamicPPL ~/.julia/packages/DynamicPPL/emAbx/src/model.jl:94
          [9] Model
            @ ~/.julia/packages/DynamicPPL/emAbx/src/model.jl:98 [inlined]
         [10] f
            @ ~/.julia/packages/Turing/TbEZL/src/core/ad.jl:111 [inlined]
         [11] vector_mode_dual_eval
            @ ~/.julia/packages/ForwardDiff/QOqCN/src/apiutils.jl:37 [inlined]
         [12] vector_mode_gradient!(result::Vector{Float64}, f::Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, x::Vector{Float64}, cfg::ForwardDiff.GradientConfig{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}})
            @ ForwardDiff ~/.julia/packages/ForwardDiff/QOqCN/src/gradient.jl:113
         [13] gradient!
            @ ~/.julia/packages/ForwardDiff/QOqCN/src/gradient.jl:37 [inlined]
         [14] gradient!(result::Vector{Float64}, f::Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, x::Vector{Float64}, cfg::ForwardDiff.GradientConfig{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Turing.Core.var"#f#3"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.DefaultContext}, Float64}, Float64, 3}}})
            @ ForwardDiff ~/.julia/packages/ForwardDiff/QOqCN/src/gradient.jl:35
         [15] gradient_logp(::Turing.Core.ForwardDiffAD{40}, θ::Vector{Float64}, vi::DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, model::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, sampler::DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, ctx::DynamicPPL.DefaultContext)
            @ Turing.Core ~/.julia/packages/Turing/TbEZL/src/core/ad.jl:121
         [16] gradient_logp (repeats 2 times)
            @ ~/.julia/packages/Turing/TbEZL/src/core/ad.jl:83 [inlined]
         [17] ∂logπ∂θ
            @ ~/.julia/packages/Turing/TbEZL/src/inference/hmc.jl:433 [inlined]
         [18] ∂H∂θ
            @ ~/.julia/packages/AdvancedHMC/MIxdK/src/hamiltonian.jl:31 [inlined]
         [19] phasepoint
            @ ~/.julia/packages/AdvancedHMC/MIxdK/src/hamiltonian.jl:69 [inlined]
         [20] phasepoint(rng::Random._GLOBAL_RNG, θ::Vector{Float64}, h::AdvancedHMC.Hamiltonian{AdvancedHMC.DiagEuclideanMetric{Float64, Vector{Float64}}, Turing.Inference.var"#logπ#52"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}}, Turing.Inference.var"#∂logπ∂θ#51"{DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}, DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}}})
            @ AdvancedHMC ~/.julia/packages/AdvancedHMC/MIxdK/src/hamiltonian.jl:139
         [21] initialstep(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, spl::DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, vi::DynamicPPL.TypedVarInfo{NamedTuple{(:β, :λ, :σ), Tuple{DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:β, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:β, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:λ, Tuple{}}, Int64}, Vector{Beta{Float64}}, Vector{AbstractPPL.VarName{:λ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}, DynamicPPL.Metadata{Dict{AbstractPPL.VarName{:σ, Tuple{}}, Int64}, Vector{Normal{Float64}}, Vector{AbstractPPL.VarName{:σ, Tuple{}}}, Vector{Float64}, Vector{Set{DynamicPPL.Selector}}}}}, Float64}; init_params::Nothing, nadapts::Int64, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
            @ Turing.Inference ~/.julia/packages/Turing/TbEZL/src/inference/hmc.jl:167
         [22] step(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, spl::DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}; resume_from::Nothing, kwargs::Base.Iterators.Pairs{Symbol, Int64, Tuple{Symbol}, NamedTuple{(:nadapts,), Tuple{Int64}}})
            @ DynamicPPL ~/.julia/packages/DynamicPPL/emAbx/src/sampler.jl:87
         [23] macro expansion
            @ ~/.julia/packages/AbstractMCMC/ByHEr/src/sample.jl:123 [inlined]
         [24] macro expansion
            @ ~/.julia/packages/AbstractMCMC/ByHEr/src/logging.jl:15 [inlined]
         [25] mcmcsample(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, sampler::DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, discard_initial::Int64, thinning::Int64, chain_type::Type, kwargs::Base.Iterators.Pairs{Symbol, Int64, Tuple{Symbol}, NamedTuple{(:nadapts,), Tuple{Int64}}})
            @ AbstractMCMC ~/.julia/packages/AbstractMCMC/ByHEr/src/sample.jl:114
         [26] #sample#40
            @ ~/.julia/packages/Turing/TbEZL/src/inference/hmc.jl:133 [inlined]
         [27] macro expansion
            @ ~/.julia/packages/AbstractMCMC/ByHEr/src/sample.jl:347 [inlined]
         [28] (::AbstractMCMC.var"#927#threadsfor_fun#42"{UnitRange{Int64}, Bool, Base.Iterators.Pairs{Symbol, UnionAll, Tuple{Symbol}, NamedTuple{(:chain_type,), Tuple{UnionAll}}}, Int64, Vector{Any}, Vector{UInt64}, Vector{DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}}, Vector{DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}}, Vector{Random._GLOBAL_RNG}})(onethread::Bool)
            @ AbstractMCMC ./threadingconstructs.jl:81
         [29] (::AbstractMCMC.var"#927#threadsfor_fun#42"{UnitRange{Int64}, Bool, Base.Iterators.Pairs{Symbol, UnionAll, Tuple{Symbol}, NamedTuple{(:chain_type,), Tuple{UnionAll}}}, Int64, Vector{Any}, Vector{UInt64}, Vector{DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}}, Vector{DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}}, Vector{Random._GLOBAL_RNG}})()
            @ AbstractMCMC ./threadingconstructs.jl:48
Stacktrace:
  [1] sync_end(c::Channel{Any})
    @ Base ./task.jl:369
  [2] macro expansion
    @ ./task.jl:388 [inlined]
  [3] macro expansion
    @ ~/.julia/packages/AbstractMCMC/ByHEr/src/sample.jl:316 [inlined]
  [4] macro expansion
    @ ~/.julia/packages/ProgressLogging/6KXlp/src/ProgressLogging.jl:328 [inlined]
  [5] macro expansion
    @ ~/.julia/packages/AbstractMCMC/ByHEr/src/logging.jl:8 [inlined]
  [6] mcmcsample(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, sampler::DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, ::MCMCThreads, N::Int64, nchains::Int64; progress::Bool, progressname::String, kwargs::Base.Iterators.Pairs{Symbol, UnionAll, Tuple{Symbol}, NamedTuple{(:chain_type,), Tuple{UnionAll}}})
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/ByHEr/src/sample.jl:310
  [7] sample(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, sampler::DynamicPPL.Sampler{NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}}, ensemble::MCMCThreads, N::Int64, n_chains::Int64; chain_type::Type, progress::Bool, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ Turing.Inference ~/.julia/packages/Turing/TbEZL/src/inference/Inference.jl:217
  [8] sample
    @ ~/.julia/packages/Turing/TbEZL/src/inference/Inference.jl:217 [inlined]
  [9] #sample#6
    @ ~/.julia/packages/Turing/TbEZL/src/inference/Inference.jl:202 [inlined]
 [10] sample
    @ ~/.julia/packages/Turing/TbEZL/src/inference/Inference.jl:202 [inlined]
 [11] #sample#5
    @ ~/.julia/packages/Turing/TbEZL/src/inference/Inference.jl:189 [inlined]
 [12] sample(model::DynamicPPL.Model{var"#21#22", (:x, :y), (), (), Tuple{Vector{Float64}, Vector{Float64}}, Tuple{}}, alg::NUTS{Turing.Core.ForwardDiffAD{40}, (), AdvancedHMC.DiagEuclideanMetric}, ensemble::MCMCThreads, N::Int64, n_chains::Int64)
    @ Turing.Inference ~/.julia/packages/Turing/TbEZL/src/inference/Inference.jl:189

EvoArt · June 24, 2021, 2:05pm

My guess would be that in the second version of the function x + lambda calls a base method that adds a forward diff dual thingy to a float and returns forward diff dual. Whereas in the original function xnew = x creates a vector of floats, and when you try to set new values with forward diff dual values you get the error.

I’m no expert, but that’s just my guess. Also, this should probably be under the probabilistic programming domain.

Christopher_Fisher · June 24, 2021, 2:18pm

I think EvoArt is correct. The segment of the error message indicates some part of your code expects a Float64, but received a Dual. I suspected that the problem is that xnew is defined in terms of x, which appears be a Float64. You might try something like xnew = zeros(typeof(λ), n), where n is the desired length of xnew.

DoktorMike · June 24, 2021, 5:49pm

Thanks for the tip. I moved it to the PPL domain.

DoktorMike · June 24, 2021, 5:49pm

Thanks Christopher. I will try this and report back if it solves it.

Christopher_Fisher · June 25, 2021, 8:50am

No problem. I had a chance to look at your example in more detail. The following function works with your example model:

function myfilter(x::AbstractVector, λ)
    n = length(x)
    xnew = zeros(typeof(λ), n)
    xnew[1] = x[1]
    for i in 2:n
        xnew[i] = x[i] + λ * xnew[i-1]
    end
    xnew
end

DoktorMike · June 27, 2021, 8:02am

Thanks a lot @Christopher_Fisher! That did indeed solve it. For the record I can also say that removing the type on x also solves it.

function myfilter(x, λ)
    xnew = x
    for i = 2:length(x)
        xnew[i] = x[i] + λ * xnew[i - 1]
    end
    xnew
end

Thus I set my own trap when I specified the type on x. Thanks for the help guys.