Unbound GlobalRef not allowed in value position

[penelopeysm]

Reporting here because I assume it's a Libtask bug, and that there's a Turing-free MWE which I don't have time to find right now.

Fails with Turing 0.41.3, AdvancedPS 0.7.0, Libtask 0.9.10.

using Turing
N = 60
K = 2
D = 2
w = [0.5, 0.5]
μ0 = [-3.5 +0.5; +3.5 -0.5]
μ1 = [0.0 0.0; 0.0 0.0]
@model function bayesianMixtureModel(x)
    k = Vector{Int64}(undef, N)
    μ = Array{Float64}(undef, (D, K))
    for k in 1:K
        μ[:, k] ~ MvNormal(μ1[:, k], 2.0 .* I)
    end
end
mixtureModel0 = MixtureModel([MvNormal(μ0[:, k], I) for k in 1:K], w)
x = rand(mixtureModel0, N)
model = bayesianMixtureModel(x)
spl = PG(10)
chains = sample(model, spl, 100)

julia> chains = sample(model, spl, 100)
Unbound GlobalRef not allowed in value position
Sampling 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| Time: 0:00:05
ERROR:
Stacktrace:
  [1] error(s::String)
    @ Core.Compiler ./error.jl:35
  [2] check_op(ir::Core.Compiler.IRCode, domtree::Core.Compiler.GenericDomTree{…}, op::Any, use_bb::Int64, use_idx::Int64, printed_use_idx::Int64, print::Bool, isforeigncall::Bool, arg_idx::Int64, allow_frontend_forms::Bool)
    @ Core.Compiler ./compiler/ssair/verify.jl:61
  [3] verify_ir(ir::Core.Compiler.IRCode, print::Bool, allow_frontend_forms::Bool, 𝕃ₒ::Core.Compiler.PartialsLattice{Core.Compiler.ConstsLattice})
    @ Core.Compiler ./compiler/ssair/verify.jl:393
  [4] verify_ir
    @ ./compiler/ssair/verify.jl:98 [inlined]
  [5] optimise_ir!(ir::Core.Compiler.IRCode; show_ir::Bool, do_inline::Bool)
    @ Libtask ~/.julia/packages/Libtask/AGx8L/src/utils.jl:46
  [6] optimise_ir!
    @ ~/.julia/packages/Libtask/AGx8L/src/utils.jl:40 [inlined]
  [7] build_callable(sig::Type{Tuple{typeof(bayesianMixtureModel), DynamicPPL.Model{…}, DynamicPPL.VarInfo{…}, Matrix{…}}})
    @ Libtask ~/.julia/packages/Libtask/AGx8L/src/copyable_task.jl:98
  [8] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
    @ Libtask ~/.julia/packages/Libtask/AGx8L/src/copyable_task.jl:313
  [9] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
    @ Libtask ~/.julia/packages/Libtask/AGx8L/src/copyable_task.jl:303
 [10] #TapedTask#69
    @ ~/ppl/lib/src/mcmc/particle_mcmc.jl:54 [inlined]
 [11] TapedTask
    @ ~/ppl/lib/src/mcmc/particle_mcmc.jl:53 [inlined]
 [12] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.VarInfo{…}, DynamicPPL.Model{…}, Tuple{…}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{…}})
    @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/mkUwY/ext/AdvancedPSLibtaskExt.jl:38
 [13] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.VarInfo{…}, DynamicPPL.Model{…}, Tuple{…}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{…}})
    @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/mkUwY/ext/AdvancedPSLibtaskExt.jl:84
 [14] AdvancedPS.Trace(model::DynamicPPL.Model{…}, varinfo::DynamicPPL.VarInfo{…}, rng::AdvancedPS.TracedRNG{…}, resample::Bool)
    @ Turing.Inference ~/ppl/lib/src/mcmc/particle_mcmc.jl:454
 [15] (::Turing.Inference.var"#78#79"{DynamicPPL.Model{…}, DynamicPPL.VarInfo{…}})(::Int64)
    @ Turing.Inference ./none:0
 [16] iterate
    @ ./generator.jl:48 [inlined]
 [17] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#78#79"{DynamicPPL.Model{…}, DynamicPPL.VarInfo{…}}})
    @ Base ./array.jl:791
 [18] initialstep(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{…}, spl::PG{…}, vi::DynamicPPL.VarInfo{…}; kwargs::@Kwargs{…})
    @ Turing.Inference ~/ppl/lib/src/mcmc/particle_mcmc.jl:264
 [19] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{…}, spl::PG{…}; initial_params::InitFromPrior, kwargs::@Kwargs{})
    @ Turing.Inference ~/ppl/lib/src/mcmc/abstractmcmc.jl:180
 [20] step
    @ ~/ppl/lib/src/mcmc/abstractmcmc.jl:162 [inlined]
 [21] macro expansion
    @ ~/.julia/packages/AbstractMCMC/mcqES/src/sample.jl:188 [inlined]
 [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, UnionAll, Nothing, @Kwargs{…}, Random.TaskLocalRNG, DynamicPPL.Model{…}, PG{…}, Int64, Float64, Int64, Int64})()
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/mcqES/src/logging.jl:134
 [23] with_logstate(f::AbstractMCMC.var"#29#30"{…}, logstate::Base.CoreLogging.LogState)
    @ Base.CoreLogging ./logging/logging.jl:524
 [24] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{…}, LoggingExtras.EarlyFilteredLogger{…}}})
    @ Base.CoreLogging ./logging/logging.jl:635
 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/mcqES/src/logging.jl:157
 [26] macro expansion
    @ ~/.julia/packages/AbstractMCMC/mcqES/src/logging.jl:133 [inlined]
 [27] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{…}, sampler::PG{…}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{…})
    @ AbstractMCMC ~/.julia/packages/AbstractMCMC/mcqES/src/sample.jl:168
 [28] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{…}, spl::PG{…}, N::Int64; initial_params::InitFromPrior, check_model::Bool, chain_type::Type, kwargs::@Kwargs{})
    @ Turing.Inference ~/ppl/lib/src/mcmc/abstractmcmc.jl:85
 [29] sample
    @ ~/ppl/lib/src/mcmc/abstractmcmc.jl:74 [inlined]
 [30] #sample#1
    @ ~/ppl/lib/src/mcmc/abstractmcmc.jl:71 [inlined]
 [31] sample(model::DynamicPPL.Model{typeof(bayesianMixtureModel), (:x,), (), (), Tuple{…}, Tuple{}, DynamicPPL.DefaultContext}, spl::PG{AdvancedPS.ResampleWithESSThreshold{…}}, N::Int64)
    @ Turing.Inference ~/ppl/lib/src/mcmc/abstractmcmc.jl:68
 [32] top-level scope
    @ REPL[13]:1
Some type information was truncated. Use `show(err)` to see complete types.

[penelopeysm]

Still reproducible on Turing 0.43.2, Libtask v0.9.14

[penelopeysm]

Stupendously, Claude minimised this in about 2 minutes

using Libtask
a = 1.0
function f()
  return a + 1.0
end

TapedTask(nothing, f)