# Error running Museinference.jl example

**URL:** <https://discourse.julialang.org/t/error-running-museinference-jl-example/103360>\
**Category:** Probabilistic Programming\
**Tags:** package, bayesian-inference, museinference\
**Created:** [August 30, 2023, 10:38am UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360 "2023-08-30T10:38:20Z")\
**Posts on this page:** 8\
**Page:** 1

<div class="post-metadata">

**Author:** ![mgp](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mgp/32/28599_2.png) [@mgp](https://discourse.julialang.org/u/mgp)\
**Post date:** [August 30, 2023, 10:38am UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360/1 "2023-08-30T10:38:20Z")

</div>

Not sure if this should be a new topic. It follows on from [https://discourse.julialang.org/t/ann-museinference-jl-drop-in-replacement-for-hmc-vi-try-it-on-your-problem/73468](https://discourse.julialang.org/t/ann-museinference-jl-drop-in-replacement-for-hmc-vi-try-it-on-your-problem/73468).

When I run the example code

```julia
@model function funnel()
    θ ~ Normal(0, 3)
    z ~ MvNormal(zeros(512), exp(θ/2))
    x ~ MvNormal(z, 1)
end

x = (funnel() | (θ=0,))() # draw sample of `x` to use as simulated data
model = funnel() | (;x)

muse(model, 0, get_covariance=true)

```

I get an error `InexactError: Int64(-2.0175508218727827)`, which seems to be attempting to identify a `threadid` (although I don’t think it’s multithreaded).

Thanks for any help.

Here’s the complete error

```julia
ERROR: InexactError: Int64(-2.0175508218727827)
Stacktrace:
  [1] Int64
    @ .\float.jl:900 [inlined]
  [2] convert
    @ .\number.jl:7 [inlined]
  [3] setindex!
    @ .\array.jl:969 [inlined]
  [4] acclogp!!
    @ C:\Users\mpritchard\.julia\packages\DynamicPPL\oJMmE\src\threadsafe.jl:25 [inlined]
  [5] tilde_observe!!
    @ C:\Users\mpritchard\.julia\packages\DynamicPPL\oJMmE\src\context_implementations.jl:184 [inlined]
  [6] tilde_observe!!
    @ C:\Users\mpritchard\.julia\packages\DynamicPPL\oJMmE\src\context_implementations.jl:170 [inlined]
  [7] funnel( __model__ ::DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.ConditionContext{NamedTuple{(:θ,), Tuple{Float32}}, DynamicPPL.DefaultContext}}, __varinfo__ ::DynamicPPL.ThreadSafeVarInfo{DynamicPPL.SimpleVarInfo{NamedTuple{(), Tuple{}}, Int64, MuseInference.PartialTransformation{Tuple{AbstractPPL.VarName{:z, Setfield.IdentityLens}}}}, Vector{Int64}}, __context__ ::DynamicPPL.SamplingContext{DynamicPPL.SampleFromPrior, DynamicPPL.ConditionContext{NamedTuple{(:θ,), Tuple{Float32}}, DynamicPPL.DefaultContext}, Xoshiro})
    @ Main c:\Users\mpritchard\Desktop\Untitled-1__asdf.jl:27
  [8] _evaluate!!
    @ C:\Users\mpritchard\.julia\packages\DynamicPPL\oJMmE\src\model.jl:582 [inlined]
  [9] evaluate_threadsafe!!(model::DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.ConditionContext{NamedTuple{(:θ,), Tuple{Float32}}, DynamicPPL.DefaultContext}}, varinfo::DynamicPPL.SimpleVarInfo{NamedTuple{(), Tuple{}}, Int64, MuseInference.PartialTransformation{Tuple{AbstractPPL.VarName{:z, Setfield.IdentityLens}}}}, context::DynamicPPL.SamplingContext{DynamicPPL.SampleFromPrior, DynamicPPL.DefaultContext, Xoshiro})
    @ DynamicPPL C:\Users\mpritchard\.julia\packages\DynamicPPL\oJMmE\src\model.jl:571
 [10] evaluate!!
    @ C:\Users\mpritchard\.julia\packages\DynamicPPL\oJMmE\src\model.jl:506 [inlined]
 [11] evaluate!!
    @ C:\Users\mpritchard\.julia\packages\DynamicPPL\oJMmE\src\model.jl:519 [inlined]
 [12] evaluate!!(model::DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.ConditionContext{NamedTuple{(:θ,), Tuple{Float32}}, DynamicPPL.DefaultContext}}, rng::Xoshiro, varinfo::DynamicPPL.SimpleVarInfo{NamedTuple{(), Tuple{}}, Int64, MuseInference.PartialTransformation{Tuple{AbstractPPL.VarName{:z, Setfield.IdentityLens}}}})    
    @ DynamicPPL C:\Users\mpritchard\.julia\packages\DynamicPPL\oJMmE\src\model.jl:519
 [13] sample_x_z(prob::TuringMuseProblem{AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext}}, rng::Xoshiro, θ::ComponentArrays.ComponentVector{Float32, Vector{Float32}, Tuple{ComponentArrays.Axis{(θ = 1,)}}})
    @ MuseInference C:\Users\mpritchard\.julia\packages\MuseInference\d1Xjv\src\turing.jl:214
 [14] (::MuseInference.var"#47#53"{Nothing, TuringMuseProblem{AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext}}})(rng::Xoshiro)
    @ MuseInference C:\Users\mpritchard\.julia\packages\MuseInference\d1Xjv\src\muse.jl:146
 [15] iterate
    @ .\generator.jl:47 [inlined]
 [16] _collect(c::Vector{Xoshiro}, itr::Base.Generator{Vector{Xoshiro}, MuseInference.var"#47#53"{Nothing, TuringMuseProblem{AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext}}}}, #unused#::Base.EltypeUnknown, isz::Base.HasShape{1})
    @ Base .\array.jl:802
 [17] collect_similar(cont::Vector{Xoshiro}, itr::Base.Generator{Vector{Xoshiro}, MuseInference.var"#47#53"{Nothing, TuringMuseProblem{AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext}}}})
    @ Base .\array.jl:711
 [18] map(f::Function, A::Vector{Xoshiro})
    @ Base .\abstractarray.jl:3261
 [19] pmap(f::Function, #unused#::MuseInference.LocalWorkerPool, args::Vector{Xoshiro})
    @ MuseInference C:\Users\mpritchard\.julia\packages\MuseInference\d1Xjv\src\util.jl:75
 [20] muse!(result::MuseResult, prob::TuringMuseProblem{AbstractDifferentiation.ReverseRuleConfigBackend{Zygote.ZygoteRuleConfig{Zygote.Context{false}}}, DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext}}, θ₀::Int64; rng::Nothing, z₀::Nothing, 
maxsteps::Int64, θ_rtol::Float64, ∇z_logLike_atol::Float64, nsims::Int64, α::Float64, progress::Bool, pool::MuseInference.LocalWorkerPool, regularize::typeof(identity), H⁻¹_like′::Nothing, H⁻¹_update::Symbol, broyden_memory::Float64, checkpoint_filename::Nothing, get_covariance::Bool, save_MAPs::Bool)
    @ MuseInference C:\Users\mpritchard\.julia\packages\MuseInference\d1Xjv\src\muse.jl:145
 [21] muse!
    @ C:\Users\mpritchard\.julia\packages\MuseInference\d1Xjv\src\muse.jl:112 [inlined]
 [22] #muse!#132
    @ C:\Users\mpritchard\.julia\packages\MuseInference\d1Xjv\src\turing.jl:235 [inlined]
 [23] muse(::DynamicPPL.Model{typeof(funnel), (), (), (), Tuple{}, Tuple{}, DynamicPPL.ConditionContext{NamedTuple{(:x,), Tuple{Vector{Float64}}}, DynamicPPL.DefaultContext}}, ::Vararg{Any}; kwargs::Base.Pairs{Symbol, Bool, Tuple{Symbol}, NamedTuple{(:get_covariance,), Tuple{Bool}}}) @ MuseInference C:\Users\mpritchard\.julia\packages\MuseInference\d1Xjv\src\muse.jl:107
 [24] top-level scope
    @ c:\Users\mpritchard\Desktop\Untitled-1__asdf.jl:35

```

---

<div class="post-metadata">

**Author:** ![mgp](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mgp/32/28599_2.png) [@mgp](https://discourse.julialang.org/u/mgp)\
**Post date:** [August 30, 2023, 10:42am UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360/2 "2023-08-30T10:42:03Z")

</div>

PS, same error running the longer example at [MuseInference.jl · MuseInference](https://cosmicmar.com/MuseInference.jl/latest/)

---

<div class="post-metadata">

**Author:** ![marius311](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/marius311/32/3953_2.png) [@marius311](https://discourse.julialang.org/u/marius311)\
**Post date:** [August 30, 2023, 5:04pm UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360/3 "2023-08-30T17:04:41Z")

</div>

Yea this error pops up when you start Julia with multiple threads, even if you don’t use them, my guess is you are doing so even if not intentionall. I believe its a DynamicPPL bug and have been meaning to file an issue. In the meantime, following [here](https://github.com/marius311/MuseInference.jl/pull/15#issuecomment-1693716537), defining this should fix it:

```julia
import Turing.DynamicPPL as DynPPL
function DynPPL.ThreadSafeVarInfo(vi::DynPPL.SimpleVarInfo)
    return DynPPL.ThreadSafeVarInfo(vi, Vector{Real}(zeros(typeof(DynPPL.getlogp(vi)), Threads.nthreads())))
end

```

Edit: [ThreadSafeVarInfo(::SimpleVarInfo) bug with ForwardDiff · Issue #524 · TuringLang/DynamicPPL.jl · GitHub](https://github.com/TuringLang/DynamicPPL.jl/issues/524)

---

<div class="post-metadata">

**Author:** ![mgp](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mgp/32/28599_2.png) [@mgp](https://discourse.julialang.org/u/mgp)\
**Post date:** [August 31, 2023, 4:15pm UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360/4 "2023-08-31T16:15:46Z")

</div>

Thank you. I’m afraid I now get a new error:

```julia
ERROR: Mutating arrays is not supported -- called setindex!(Vector{Real}, ...)
This error occurs when you ask Zygote to differentiate operations that change
the elements of arrays in place (e.g. setting values with x .= ...)     

```

---

<div class="post-metadata">

**Author:** ![marius311](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/marius311/32/3953_2.png) [@marius311](https://discourse.julialang.org/u/marius311)\
**Post date:** [September 1, 2023, 2:12am UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360/5 "2023-09-01T02:12:19Z")

</div>

Yea, ran into that as well. I believe that’s a bonafide DynamicPPL/Zygote issue, eg:

```julia
Threads.nthreads() # 2 or more
using Turing, Zygote
@model function foo()
    x ~ Normal()
end
model = foo()
Zygote.gradient(x -> logjoint(model, (;x)), 1) # your error

```

You can follow along [here](https://julialang.slack.com/archives/CCYDC34A0/p1693501595935829) to see if we figure it out or if you don’t actually need threads make sure you start Julia with only 1, or if you are fine with ForwardDiff the latest tagged version of MuseInference (0.2.4 from today) is fine with that with any number of threads.

---

<div class="post-metadata">

**Author:** ![torfjelde](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/torfjelde/32/206542_2.png) [@torfjelde](https://discourse.julialang.org/u/torfjelde)\
**Post date:** [September 1, 2023, 9:42am UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360/7 "2023-09-01T09:42:56Z")

</div>

The above comment wasn’t quite accurate; we do support Zygote usage with threads, but not when doing `logjoint(model, (;x))` because this is just effectively a wrapper around

```julia
logjoint(model, SimpleVarInfo((;x), 0.0))

```

In short, in Turing / DynamicPPL we have two different “trace” structures that are used when working with a model:

- `VarInfo` which is the one that has been around since the beginning of Turing, and is the one which is most heavily used.
- `SimpleVarInfo` which is a “new” one that is supposed to be much “simpler” to work with (the implementation of `VarInfo` is quite complicated) and allows us to provide some simpler functionality for querying the model about some information, e.g. `logjoint`, in a nicer way than what we do with `VarInfo`.

By _default_ the threadsafe `VarInfo` uses a `Vector` of `Ref` for each of the threads which are mutated; `Ref` _is_ supported by Zygote. By default, the threadsafe `SimpleVarInfo` uses a `Vector{<:Real}`, i.e. not `Ref`, and hence Zygote complains.

Sooo, the way you can make this work is as follows:

```julia
Zygote.gradient(x -> logjoint(model, SimpleVarInfo((;x), Ref(0.0))), 1)

```

That is, we manually wrap the logp in a `Ref`, which is then compatible with Zygote.

Unfortunately, `SimpleVarInfo` with `Ref` is not as well-tested, so when trying the above I ran into an error which is fixed by adding

```julia
DynamicPPL.getlogp(vi::DynamicPPL.SimpleVarInfo{<:Any,<:Ref}) = vi.logp[]

```

which I’ll now make a PR for 😬

---

<div class="post-metadata">

**Author:** ![mgp](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mgp/32/28599_2.png) [@mgp](https://discourse.julialang.org/u/mgp)\
**Post date:** [September 1, 2023, 3:21pm UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360/8 "2023-09-01T15:21:30Z")

</div>

Thank you. For now I have turned off multiple threads and it works for me.

---

<div class="post-metadata">

**Author:** ![torfjelde](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/torfjelde/32/206542_2.png) [@torfjelde](https://discourse.julialang.org/u/torfjelde)\
**Post date:** [September 1, 2023, 6:58pm UTC](https://discourse.julialang.org/t/error-running-museinference-jl-example/103360/9 "2023-09-01T18:58:53Z")

</div>

> Unfortunately, `SimpleVarInfo` with `Ref` is not as well-tested, so when trying the above I ran into an error which is fixed by adding

This is now fixed on DPPL@0.23.15