Package evaluation to test Turing on Julia 1.14.0-DEV.2113 (886384998d*) started at 2026-05-04T00:35:55.746


################################################################################
# Set-up
#

Installing PkgEval dependencies (TestEnv)...
  Activating project at `~/.julia/environments/v1.14`

Set-up completed after 14.1s


################################################################################
# Installation
#

Installing Turing...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [fce5fe82] + Turing v0.45.0
    Updating `~/.julia/environments/v1.14/Manifest.toml`
  [47edcb42] + ADTypes v1.22.0
  [621f4979] + AbstractFFTs v1.5.0
  [80f14c24] + AbstractMCMC v5.15.1
  [7a57a42e] + AbstractPPL v0.14.2
  [1520ce14] + AbstractTrees v0.4.5
  [7d9f7c33] + Accessors v0.1.44
  [79e6a3ab] + Adapt v4.5.2
  [0bf59076] + AdvancedHMC v0.8.3
  [5b7e9947] + AdvancedMH v0.8.10
  [576499cb] + AdvancedPS v0.7.2
  [b5ca4192] + AdvancedVI v0.6.2
  [66dad0bd] + AliasTables v1.1.3
  [dce04be8] + ArgCheck v2.5.0
  [4fba245c] + ArrayInterface v7.24.0
  [198e06fe] + BangBang v0.4.9
  [76274a88] + Bijectors v0.15.24
  [d360d2e6] + ChainRulesCore v1.26.1
  [0ca39b1e] + Chairmarks v1.3.1
  [9e997f8a] + ChangesOfVariables v0.1.10
  [38540f10] + CommonSolve v0.2.6
  [bbf7d656] + CommonSubexpressions v0.3.1
  [34da2185] + Compat v4.18.1
  [a33af91c] + CompositionsBase v0.1.2
  [88cd18e8] + ConsoleProgressMonitor v0.1.2
  [187b0558] + ConstructionBase v1.6.0
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.19.4
  [e2d170a0] + DataValueInterfaces v1.0.0
  [8bb1440f] + DelimitedFiles v1.9.1
  [b429d917] + DensityInterface v0.4.0
  [163ba53b] + DiffResults v1.1.0
  [b552c78f] + DiffRules v1.15.1
  [a0c0ee7d] + DifferentiationInterface v0.7.17
  [0703355e] + DimensionalData v0.30.1
  [31c24e10] + Distributions v0.25.125
  [ffbed154] + DocStringExtensions v0.9.5
  [366bfd00] + DynamicPPL v0.41.7
  [cad2338a] + EllipticalSliceSampling v2.0.0
  [4e289a0a] + EnumX v1.0.7
  [f151be2c] + EnzymeCore v0.8.20
  [e2ba6199] + ExprTools v0.1.10
  [411431e0] + Extents v0.1.6
  [9aa1b823] + FastClosures v0.3.2
  [1a297f60] + FillArrays v1.16.0
  [6a86dc24] + FiniteDiff v2.31.0
  [4a37a8b9] + FlexiChains v0.6.0
  [f6369f11] + ForwardDiff v1.3.3
  [069b7b12] + FunctionWrappers v1.1.3
  [77dc65aa] + FunctionWrappersWrappers v1.8.0
  [d9f16b24] + Functors v0.5.2
  [46192b85] + GPUArraysCore v0.2.0
  [34004b35] + HypergeometricFunctions v0.3.28
  [22cec73e] + InitialValues v0.3.1
  [85a1e053] + Interfaces v0.3.2
  [8197267c] + IntervalSets v0.7.14
  [3587e190] + InverseFunctions v0.1.17
  [41ab1584] + InvertedIndices v1.3.1
  [92d709cd] + IrrationalConstants v0.2.6
  [82899510] + IteratorInterfaceExtensions v1.0.0
  [692b3bcd] + JLLWrappers v1.7.1
  [682c06a0] + JSON v1.5.2
  [1d6d02ad] + LeftChildRightSiblingTrees v0.2.1
  [6f1fad26] + Libtask v0.9.17
  [d3d80556] + LineSearches v7.6.1
  [6fdf6af0] + LogDensityProblems v2.2.0
  [996a588d] + LogDensityProblemsAD v1.13.1
  [2ab3a3ac] + LogExpFunctions v0.3.29
  [e6f89c97] + LoggingExtras v1.2.0
  [be115224] + MCMCDiagnosticTools v0.3.17
  [e80e1ace] + MLJModelInterface v1.12.1
  [1914dd2f] + MacroTools v0.5.16
  [dbb5928d] + MappedArrays v0.4.3
  [e1d29d7a] + Missings v1.2.0
  [dbe65cb8] + MistyClosures v2.1.0
  [d41bc354] + NLSolversBase v8.0.0
  [77ba4419] + NaNMath v1.1.3
  [429524aa] + Optim v2.0.1
  [3bd65402] + Optimisers v0.4.7
  [7f7a1694] + Optimization v5.5.1
  [bca83a33] + OptimizationBase v5.1.1
  [36348300] + OptimizationOptimJL v0.4.13
  [bac558e1] + OrderedCollections v1.8.1
  [90014a1f] + PDMats v0.11.37
  [69de0a69] + Parsers v2.8.4
  [569bd051] + PartitionedDistributions v0.0.1
  [85a6dd25] + PositiveFactorizations v0.2.4
  [d236fae5] + PreallocationTools v1.2.0
  [aea7be01] + PrecompileTools v1.3.3
  [21216c6a] + Preferences v1.5.2
  [33c8b6b6] + ProgressLogging v0.1.6
  [92933f4c] + ProgressMeter v1.11.0
  [43287f4e] + PtrArrays v1.4.0
  [1fd47b50] + QuadGK v2.11.3
  [74087812] + Random123 v1.7.1
  [e6cf234a] + RandomNumbers v1.6.0
  [3cdcf5f2] + RecipesBase v1.3.4
  [731186ca] + RecursiveArrayTools v4.3.0
  [189a3867] + Reexport v1.2.2
  [ae029012] + Requires v1.3.1
  [79098fc4] + Rmath v0.9.0
  [f2b01f46] + Roots v3.0.0
  [7e49a35a] + RuntimeGeneratedFunctions v0.5.18
  [26aad666] + SSMProblems v0.6.1
  [0bca4576] + SciMLBase v3.7.1
⌅ [a6db7da4] + SciMLLogging v1.9.1
  [c0aeaf25] + SciMLOperators v1.17.0
  [431bcebd] + SciMLPublic v1.0.1
  [53ae85a6] + SciMLStructures v1.10.0
  [30f210dd] + ScientificTypesBase v3.1.0
  [efcf1570] + Setfield v1.1.2
  [a2af1166] + SortingAlgorithms v1.2.2
  [9f842d2f] + SparseConnectivityTracer v1.2.1
  [0a514795] + SparseMatrixColorings v0.4.27
  [276daf66] + SpecialFunctions v2.7.2
  [1e83bf80] + StaticArraysCore v1.4.4
  [64bff920] + StatisticalTraits v3.5.0
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.8.0
  [2913bbd2] + StatsBase v0.34.10
  [4c63d2b9] + StatsFuns v1.5.2
  [ec057cc2] + StructUtils v2.8.1
  [2efcf032] + SymbolicIndexingInterface v0.3.46
  [3783bdb8] + TableTraits v1.0.1
  [bd369af6] + Tables v1.12.1
  [5d786b92] + TerminalLoggers v0.1.7
  [781d530d] + TruncatedStacktraces v1.4.0
  [fce5fe82] + Turing v0.45.0
  [efe28fd5] + OpenSpecFun_jll v0.5.6+0
  [f50d1b31] + Rmath_jll v0.5.1+0
  [56f22d72] + Artifacts v1.11.0
  [2a0f44e3] + Base64 v1.11.0
  [ade2ca70] + Dates v1.11.0
  [8ba89e20] + Distributed v1.11.0
  [7b1f6079] + FileWatching v1.11.0
  [9fa8497b] + Future v1.11.0
  [b77e0a4c] + InteractiveUtils v1.11.0
  [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.13.0
  [56ddb016] + Logging v1.11.0
  [d6f4376e] + Markdown v1.11.0
  [a63ad114] + Mmap v1.11.0
  [de0858da] + Printf v1.11.0
  [3fa0cd96] + REPL v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v1.0.0
  [9e88b42a] + Serialization v1.11.0
  [6462fe0b] + Sockets v1.11.0
  [2f01184e] + SparseArrays v1.13.0
  [f489334b] + StyledStrings v1.13.0
  [4607b0f0] + SuiteSparse
  [fa267f1f] + TOML v1.0.3
  [8dfed614] + Test v1.11.0
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.5.1+0
  [4536629a] + OpenBLAS_jll v0.3.33+0
  [05823500] + OpenLibm_jll v0.8.7+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [8e850b90] + libblastrampoline_jll v5.15.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 6.35s


################################################################################
# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling project...
ERROR: LoadError: UndefVarError: `WorldView` not defined in `Compiler`
Suggestion: check for spelling errors or missing imports.
Stacktrace:
  [1] getproperty(x::Module, f::Symbol)
    @ Base ./Base_compiler.jl:51
  [2] top-level scope
    @ ~/.julia/packages/Mooncake/AuwJJ/src/interpreter/abstract_interpretation.jl:90
  [3] include(mapexpr::Function, mod::Module, _path::String)
    @ Base ./Base.jl:327
  [4] top-level scope
    @ ~/.julia/packages/Mooncake/AuwJJ/src/Mooncake.jl:186
  [5] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
  [6] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
  [7] top-level scope
    @ stdin:5
  [8] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
  [9] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [10] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [11] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [12] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/Mooncake/AuwJJ/src/interpreter/abstract_interpretation.jl:90
in expression starting at /home/pkgeval/.julia/packages/Mooncake/AuwJJ/src/Mooncake.jl:1
in expression starting at stdin:5
              ✗ Mooncake
  23.5 s  ✓ FlexiChains
  14.9 s  ✓ AdvancedVI → AdvancedVIReverseDiffExt
  17.7 s  ✓ Bijectors → BijectorsReverseDiffExt
  18.8 s  ✓ DynamicPPL
   6.4 s  ✓ AdvancedVI → AdvancedVIBijectorsExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_using(to::Module, path::Expr, flags::UInt8)
    @ Base ./module.jl:137 [inlined]
 [11] top-level scope
    @ ~/.julia/packages/Mooncake/AuwJJ/ext/MooncakeDistributionsExt.jl:3
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/Mooncake/AuwJJ/ext/MooncakeDistributionsExt.jl:1
in expression starting at stdin:5
              ✗ Mooncake → MooncakeDistributionsExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_import(::Bool, ::Module, ::Expr, ::Expr, ::Vararg{Expr})
    @ Base ./module.jl:101
 [11] top-level scope
    @ ~/.julia/packages/Mooncake/AuwJJ/ext/MooncakeLogExpFunctionsExt.jl:6
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/Mooncake/AuwJJ/ext/MooncakeLogExpFunctionsExt.jl:1
in expression starting at stdin:5
              ✗ Mooncake → MooncakeLogExpFunctionsExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_import(::Bool, ::Module, ::Expr, ::Expr, ::Vararg{Expr})
    @ Base ./module.jl:101
 [11] top-level scope
    @ ~/.julia/packages/Mooncake/AuwJJ/ext/MooncakeFunctionWrappersExt.jl:5
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/Mooncake/AuwJJ/ext/MooncakeFunctionWrappersExt.jl:1
in expression starting at stdin:5
              ✗ Mooncake → MooncakeFunctionWrappersExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_using(to::Module, path::Expr, flags::UInt8)
    @ Base ./module.jl:137 [inlined]
 [11] top-level scope
    @ ~/.julia/packages/Mooncake/AuwJJ/ext/MooncakeSpecialFunctionsExt.jl:3
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/Mooncake/AuwJJ/ext/MooncakeSpecialFunctionsExt.jl:1
in expression starting at stdin:5
              ✗ Mooncake → MooncakeSpecialFunctionsExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_import(::Bool, ::Module, ::Expr, ::Expr, ::Vararg{Expr})
    @ Base ./module.jl:101
 [11] top-level scope
    @ ~/.julia/packages/DifferentiationInterface/IS0Dg/ext/DifferentiationInterfaceMooncakeExt/DifferentiationInterfaceMooncakeExt.jl:5
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/DifferentiationInterface/IS0Dg/ext/DifferentiationInterfaceMooncakeExt/DifferentiationInterfaceMooncakeExt.jl:1
in expression starting at stdin:5
              ✗ DifferentiationInterface → DifferentiationInterfaceMooncakeExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] _eval_import(imported::Bool, to::Module, from::Nothing, paths::Expr)
    @ Base ./module.jl:111
 [10] top-level scope
    @ ~/.julia/packages/FunctionWrappersWrappers/YcpKm/ext/FunctionWrappersWrappersMooncakeExt.jl:4
 [11] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [12] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [13] top-level scope
    @ stdin:5
 [14] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [15] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [16] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [17] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [18] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/FunctionWrappersWrappers/YcpKm/ext/FunctionWrappersWrappersMooncakeExt.jl:1
in expression starting at stdin:5
              ✗ FunctionWrappersWrappers → FunctionWrappersWrappersMooncakeExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_using(to::Module, path::Expr, flags::UInt8)
    @ Base ./module.jl:137 [inlined]
 [11] top-level scope
    @ ~/.julia/packages/RecursiveArrayTools/CbC7J/ext/RecursiveArrayToolsMooncakeExt.jl:4
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/RecursiveArrayTools/CbC7J/ext/RecursiveArrayToolsMooncakeExt.jl:1
in expression starting at stdin:5
              ✗ RecursiveArrayTools → RecursiveArrayToolsMooncakeExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_using(to::Module, path::Expr, flags::UInt8)
    @ Base ./module.jl:137 [inlined]
 [11] top-level scope
    @ ~/.julia/packages/SciMLBase/rOg8U/ext/SciMLBaseMooncakeExt.jl:3
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/SciMLBase/rOg8U/ext/SciMLBaseMooncakeExt.jl:1
in expression starting at stdin:5
              ✗ SciMLBase → SciMLBaseMooncakeExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_using(to::Module, path::Expr, flags::UInt8)
    @ Base ./module.jl:137 [inlined]
 [11] top-level scope
    @ ~/.julia/packages/OptimizationBase/NoYrE/ext/OptimizationMooncakeExt.jl:3
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/OptimizationBase/NoYrE/ext/OptimizationMooncakeExt.jl:1
in expression starting at stdin:5
              ✗ OptimizationBase → OptimizationMooncakeExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_using(to::Module, path::Expr, flags::UInt8)
    @ Base ./module.jl:137 [inlined]
 [11] top-level scope
    @ ~/.julia/packages/AdvancedVI/2WrpF/ext/AdvancedVIMooncakeExt.jl:5
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/AdvancedVI/2WrpF/ext/AdvancedVIMooncakeExt.jl:1
in expression starting at stdin:5
              ✗ AdvancedVI → AdvancedVIMooncakeExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_import(::Bool, ::Module, ::Expr, ::Expr, ::Vararg{Expr})
    @ Base ./module.jl:101
 [11] top-level scope
    @ ~/.julia/packages/Bijectors/xWM2Q/ext/BijectorsMooncakeExt.jl:3
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/Bijectors/xWM2Q/ext/BijectorsMooncakeExt.jl:1
in expression starting at stdin:5
              ✗ Bijectors → BijectorsMooncakeExt
  11.7 s  ✓ FlexiChains → FlexiChainsMCMCChainsExt
  11.3 s  ✓ FlexiChains → FlexiChainsRecipesBaseExt
   9.1 s  ✓ FlexiChains → FlexiChainsAdvancedHMCExt
  10.7 s  ✓ DynamicPPL → DynamicPPLMCMCChainsExt
   6.8 s  ✓ DynamicPPL → DynamicPPLForwardDiffExt
   6.6 s  ✓ DynamicPPL → DynamicPPLEnzymeCoreExt
  16.8 s  ✓ DynamicPPL → DynamicPPLReverseDiffExt
  26.5 s  ✓ FlexiChains → FlexiChainsDynamicPPLExt
ERROR: LoadError: Precompiled image Base.PkgId(Base.UUID("da2b9cff-9c12-43a0-ae48-6db2b0edb7d6"), "Mooncake") not available with flags CacheFlags(; use_pkgimages=false, debug_level=1, check_bounds=1, inline=true, opt_level=0)
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:56
  [2] __require_prelocked(pkg::Base.PkgId, env::String)
    @ Base ./loading.jl:2818
  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)
    @ Base ./loading.jl:2672
  [4] macro expansion
    @ ./loading.jl:2599 [inlined]
  [5] String(s::Symbol)
    @ Base ./lock.jl:376 [inlined]
  [6] __require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2563
  [7] require(into::Module, mod::Symbol)
    @ Base ./loading.jl:2539 [inlined]
  [8] eval_import_path(at::Module, from::Nothing, path::Expr, keyword::String)
    @ Base ./module.jl:36 [inlined]
  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)
    @ Base ./module.jl:60
 [10] _eval_import(::Bool, ::Module, ::Expr, ::Expr, ::Vararg{Expr})
    @ Base ./module.jl:101
 [11] top-level scope
    @ ~/.julia/packages/DynamicPPL/pqVkv/ext/DynamicPPLMooncakeExt.jl:4
 [12] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
 [13] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
 [14] top-level scope
    @ stdin:5
 [15] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
 [16] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [17] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [18] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [19] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/DynamicPPL/pqVkv/ext/DynamicPPLMooncakeExt.jl:1
in expression starting at stdin:5
              ✗ DynamicPPL → DynamicPPLMooncakeExt
  16.3 s  ✓ Turing
  16.0 s  ✓ Turing → TuringDynamicHMCExt
  15 dependencies successfully precompiled in 285 seconds. 339 already precompiled.

Precompilation completed after 308.36s


################################################################################
# Testing
#

     Testing Turing
      Status `/tmp/jl_nSjQd9/Project.toml`
  [47edcb42] ADTypes v1.22.0
  [80f14c24] AbstractMCMC v5.15.1
  [7a57a42e] AbstractPPL v0.14.2
  [5b7e9947] AdvancedMH v0.8.10
  [576499cb] AdvancedPS v0.7.2
  [b5ca4192] AdvancedVI v0.6.2
  [4c88cf16] Aqua v0.8.14
  [198e06fe] BangBang v0.4.9
  [76274a88] Bijectors v0.15.24
  [aaaa29a8] Clustering v0.15.8
  [861a8166] Combinatorics v1.1.0
  [a0c0ee7d] DifferentiationInterface v0.7.17
  [31c24e10] Distributions v0.25.125
  [bbc10e6e] DynamicHMC v3.6.0
  [366bfd00] DynamicPPL v0.41.7
  [26cc04aa] FiniteDifferences v0.12.33
  [4a37a8b9] FlexiChains v0.6.0
  [f6369f11] ForwardDiff v1.3.3
  [09f84164] HypothesisTests v0.11.7
  [6f1fad26] Libtask v0.9.17
  [6fdf6af0] LogDensityProblems v2.2.0
  [996a588d] LogDensityProblemsAD v1.13.1
  [c7f686f2] MCMCChains v7.7.0
  [da2b9cff] Mooncake v0.5.27
  [7f7a1694] Optimization v5.5.1
  [3e6eede4] OptimizationBBO v0.4.7
  [4e6fcdb7] OptimizationNLopt v0.3.11
  [36348300] OptimizationOptimJL v0.4.13
  [90014a1f] PDMats v0.11.37
  [37e2e3b7] ReverseDiff v1.16.2
  [276daf66] SpecialFunctions v2.7.2
  [860ef19b] StableRNGs v1.0.4
  [10745b16] Statistics v1.11.1
  [2913bbd2] StatsBase v0.34.10
  [4c63d2b9] StatsFuns v1.5.2
  [a759f4b9] TimerOutputs v0.5.29
  [fce5fe82] Turing v0.45.0
  [37e2e46d] LinearAlgebra v1.13.0
  [56ddb016] Logging v1.11.0
  [44cfe95a] Pkg v1.14.0
  [9a3f8284] Random v1.11.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_nSjQd9/Manifest.toml`
  [47edcb42] ADTypes v1.22.0
  [621f4979] AbstractFFTs v1.5.0
  [80f14c24] AbstractMCMC v5.15.1
  [7a57a42e] AbstractPPL v0.14.2
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.44
  [79e6a3ab] Adapt v4.5.2
  [0bf59076] AdvancedHMC v0.8.3
  [5b7e9947] AdvancedMH v0.8.10
  [576499cb] AdvancedPS v0.7.2
  [b5ca4192] AdvancedVI v0.6.2
  [66dad0bd] AliasTables v1.1.3
  [4c88cf16] Aqua v0.8.14
  [dce04be8] ArgCheck v2.5.0
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.24.0
  [13072b0f] AxisAlgorithms v1.1.0
  [39de3d68] AxisArrays v0.4.8
  [198e06fe] BangBang v0.4.9
  [76274a88] Bijectors v0.15.24
  [a134a8b2] BlackBoxOptim v0.6.4
  [fa961155] CEnum v0.5.0
  [d360d2e6] ChainRulesCore v1.26.1
  [0ca39b1e] Chairmarks v1.3.1
  [9e997f8a] ChangesOfVariables v0.1.10
  [aaaa29a8] Clustering v0.15.8
  [861a8166] Combinatorics v1.1.0
  [38540f10] CommonSolve v0.2.6
  [bbf7d656] CommonSubexpressions v0.3.1
  [34da2185] Compat v4.18.1
  [a33af91c] CompositionsBase v0.1.2
  [88cd18e8] ConsoleProgressMonitor v0.1.2
  [187b0558] ConstructionBase v1.6.0
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.19.4
  [e2d170a0] DataValueInterfaces v1.0.0
  [8bb1440f] DelimitedFiles v1.9.1
  [b429d917] DensityInterface v0.4.0
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  [be115224] MCMCDiagnosticTools v0.3.17
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  [c020b1a1] NaturalSort v1.0.0
  [b8a86587] NearestNeighbors v0.4.27
  [6fe1bfb0] OffsetArrays v1.17.0
  [429524aa] Optim v2.0.1
  [3bd65402] Optimisers v0.4.7
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  [90014a1f] PDMats v0.11.37
  [69de0a69] Parsers v2.8.4
  [569bd051] PartitionedDistributions v0.0.1
  [85a6dd25] PositiveFactorizations v0.2.4
  [d236fae5] PreallocationTools v1.2.0
  [aea7be01] PrecompileTools v1.3.3
  [21216c6a] Preferences v1.5.2
  [08abe8d2] PrettyTables v3.3.2
  [27ebfcd6] Primes v0.5.7
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  [92933f4c] ProgressMeter v1.11.0
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  [c84ed2f1] Ratios v0.4.5
  [3cdcf5f2] RecipesBase v1.3.4
  [731186ca] RecursiveArrayTools v4.3.0
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.1
  [37e2e3b7] ReverseDiff v1.16.2
  [708f8203] Richardson v1.4.2
  [79098fc4] Rmath v0.9.0
  [f2b01f46] Roots v3.0.0
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⌅ [a6db7da4] SciMLLogging v1.9.1
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  [53ae85a6] SciMLStructures v1.10.0
  [30f210dd] ScientificTypesBase v3.1.0
  [efcf1570] Setfield v1.1.2
  [699a6c99] SimpleTraits v0.9.5
  [a2af1166] SortingAlgorithms v1.2.2
  [9f842d2f] SparseConnectivityTracer v1.2.1
  [0a514795] SparseMatrixColorings v0.4.27
  [d4ead438] SpatialIndexing v0.1.6
  [276daf66] SpecialFunctions v2.7.2
  [860ef19b] StableRNGs v1.0.4
  [90137ffa] StaticArrays v1.9.18
  [1e83bf80] StaticArraysCore v1.4.4
  [64bff920] StatisticalTraits v3.5.0
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.8.0
  [2913bbd2] StatsBase v0.34.10
  [4c63d2b9] StatsFuns v1.5.2
  [5e0ebb24] Strided v2.5.0
  [4db3bf67] StridedViews v0.5.1
  [892a3eda] StringManipulation v0.4.4
  [ec057cc2] StructUtils v2.8.1
  [2efcf032] SymbolicIndexingInterface v0.3.46
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  [4607b0f0] SuiteSparse
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  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.5.1+0
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  [3f19e933] p7zip_jll v17.8.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
[ Info: [Turing]: progress logging is disabled globally
ERROR: LoadError: UndefVarError: `WorldView` not defined in `Compiler`
Suggestion: check for spelling errors or missing imports.
Stacktrace:
  [1] getproperty(x::Module, f::Symbol)
    @ Base ./Base_compiler.jl:51
  [2] top-level scope
    @ ~/.julia/packages/Mooncake/AuwJJ/src/interpreter/abstract_interpretation.jl:90
  [3] include(mapexpr::Function, mod::Module, _path::String)
    @ Base ./Base.jl:327
  [4] top-level scope
    @ ~/.julia/packages/Mooncake/AuwJJ/src/Mooncake.jl:186
  [5] include(mod::Module, _path::String)
    @ Base ./Base.jl:326
  [6] include_package_for_output(pkg::Base.PkgId, input::String, syntax_version::VersionNumber, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt128}}, source::Nothing)
    @ Base ./loading.jl:3271
  [7] top-level scope
    @ stdin:5
  [8] eval(m::Module, e::Any)
    @ Core ./boot.jl:517
  [9] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base ./loading.jl:3113
 [10] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Nothing, Type{Symbol}, Tuple{Vector{SubString{String}}}})
    @ Base.Broadcast ./loading.jl:3123 [inlined]
 [11] exec_options(opts::Base.JLOptions)
    @ Base ./client.jl:350
 [12] _start()
    @ Base ./client.jl:593
in expression starting at /home/pkgeval/.julia/packages/Mooncake/AuwJJ/src/interpreter/abstract_interpretation.jl:90
in expression starting at /home/pkgeval/.julia/packages/Mooncake/AuwJJ/src/Mooncake.jl:1
in expression starting at stdin:5
  1 dependency had output during precompilation:
┌ Mooncake
│  [Output was shown above]
└  

AD: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/runtests.jl:37
  Got exception outside of a @test
  LoadError: The following 1 package failed to precompile:
  Mooncake 
  Failed to precompile Mooncake [da2b9cff-9c12-43a0-ae48-6db2b0edb7d6] to "/home/pkgeval/.julia/compiled/v1.14/Mooncake/jl_9v6aVt" (ProcessExited(1)).
  in expression starting at /home/pkgeval/.julia/packages/Turing/4hMHm/test/ad.jl:1

constructor: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/essential/container.jl:20
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ContainerTests.var"#test#test##0", DynamicPPL.Model{Main.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ContainerTests.var"#test#test##0", DynamicPPL.Model{Main.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ContainerTests.var"#test#test##0", DynamicPPL.Model{Main.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ContainerTests.var"#test#test##0", DynamicPPL.Model{Main.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/essential/container.jl:10
   [12] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [13] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/essential/container.jl:21 [inlined]
   [14] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [15] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/essential/container.jl:26 [inlined]
   [16] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [17] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [18] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:42 [inlined]
   [20] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [21] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [22] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [23] top-level scope
      @ none:6
   [24] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [25] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [26] _start()
      @ Base ./client.jl:593

fork: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/essential/container.jl:39
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ContainerTests.var"#normal#normal##0", DynamicPPL.Model{Main.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ContainerTests.var"#normal#normal##0", DynamicPPL.Model{Main.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ContainerTests.var"#normal#normal##0", DynamicPPL.Model{Main.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ContainerTests.var"#normal#normal##0", DynamicPPL.Model{Main.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/essential/container.jl:10
   [12] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [13] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/essential/container.jl:40 [inlined]
   [14] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [15] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/essential/container.jl:53 [inlined]
   [16] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [17] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [18] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:42 [inlined]
   [20] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [21] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [22] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [23] top-level scope
      @ none:6
   [24] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [25] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [26] _start()
      @ Base ./client.jl:593
┌ Info: Found initial step size
└   ϵ = 3.2
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6500000000000001
┌ Warning: There were 1 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Info: Found initial step size
└   ϵ = 1.7000000000000002
┌ Warning: There were 2 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Warning: There were 3 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Warning: Only a single process available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:732
┌ Info: Found initial step size
└   ϵ = 3.2
┌ Info: Found initial step size
└   ϵ = 3.2
┌ Warning: failed to find valid initial parameters in 10 tries; consider providing a different initialisation strategy with the `initial_params` keyword
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:63
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
[ Info: Using a NamedTuple for `initial_params` will be deprecated in a future release. Please use `InitFromParams(namedtuple)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
[ Info: Using a Dict for `initial_params` will be deprecated in a future release. Please use `InitFromParams(dict)` instead.
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Number of chains (10) is greater than number of samples per chain (1)
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:549
┌ Info: Found initial step size
└   ϵ = 1.6

PG: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/callbacks.jl:24
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{typeof(Main.CallbacksTests.test_normals), DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] TapedTask
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{typeof(Main.CallbacksTests.test_normals), DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{typeof(Main.CallbacksTests.test_normals), DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/callbacks.jl:11
   [16] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [17] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/callbacks.jl:25 [inlined]
   [18] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/callbacks.jl:25 [inlined]
   [20] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [21] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [22] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [23] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [24] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [25] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [26] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [27] top-level scope
      @ none:6
   [28] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [29] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [30] _start()
      @ Base ./client.jl:593
┌ Info: Found initial step size
└   ϵ = 1.6
[ Info: [Turing]: progress logging is disabled globally
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: It looks like you are using `Threads.@threads` in your model definition.
│ 
│ Note that since version 0.39 of DynamicPPL, threadsafe evaluation of models is disabled by default. If you need it, you will need to explicitly enable it by creating the model, and then running `model = setthreadsafe(model, true)`.
│ 
│ Threadsafe model evaluation is only needed when parallelising tilde-statements (not arbitrary Julia code), and avoiding it can often lead to significant performance improvements.
│ 
│ Please see https://turinglang.org/docs/usage/threadsafe-evaluation/ for more details of when threadsafe evaluation is actually required.
└ @ DynamicPPL ~/.julia/packages/DynamicPPL/pqVkv/src/compiler.jl:357

basic model: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:28
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#normal#normal##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#normal#normal##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#normal#normal##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#normal#normal##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; nparticles::Int64, initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:181
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:166 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; check_model::Bool, chain_type::Type, initial_params::DynamicPPL.InitFromPrior, progress::Bool, discard_initial::Int64, thinning::Int64, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:151
   [27] sample
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:129 [inlined]
   [28] #sample#3
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
   [29] sample(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
   [30] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:14
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:29 [inlined]
   [33] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [34] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:36 [inlined]
   [35] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [36] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [39] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [40] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [41] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [42] top-level scope
      @ none:6
   [43] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [44] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [45] _start()
      @ Base ./client.jl:593

errors when number of observations is not fixed: Test Failed at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:49
  Expression: sample(fail_smc(), SMC(), 100)
    Expected: ErrorException
      Thrown: MethodError
      MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
      The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
      Closest candidates are:
        Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
         @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
        Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
         @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
      Stacktrace:
        [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
          @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
        [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
          @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
        [3] optimise_ir!(ir::Compiler.IRCode)
          @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
        [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
          @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
        [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
          @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
        [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
          @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
        [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
          @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
        [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
          @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
        [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
          @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
       [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
          @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
       [11] (::Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
          @ Turing.Inference ./none:-1
       [12] iterate
          @ ./generator.jl:48 [inlined]
       [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
          @ Base ./array.jl:833
       [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; nparticles::Int64, initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64})
          @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:181
       [15] step
          @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:166 [inlined]
       [16] step_warmup
          @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
       [17] #_step_or_step_warmup#25
          @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
       [18] _step_or_step_warmup
          @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
       [19] macro expansion
          @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
       [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
          @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
       [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
          @ Base.CoreLogging ./logging/logging.jl:542
       [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
          @ Base.CoreLogging ./logging/logging.jl:653
       [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
          @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
       [24] macro expansion
          @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
       [25] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64})
          @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
       [26] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; check_model::Bool, chain_type::Type, initial_params::DynamicPPL.InitFromPrior, progress::Bool, discard_initial::Int64, thinning::Int64, verbose::Bool, kwargs::@Kwargs{})
          @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:151
       [27] sample
          @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:129 [inlined]
       [28] #sample#3
          @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
       [29] sample(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#fail_smc#fail_smc##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
          @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
       [30] top-level scope
          @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:14
       [31] macro expansion
          @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
       [32] macro expansion
          @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:40 [inlined]
       [33] macro expansion
          @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
       [34] macro expansion
          @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:49 [inlined]
       [35] macro expansion
          @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:980 [inlined]
       [36] macro expansion
          @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:49 [inlined]
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:14
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [3] macro expansion
     @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:40 [inlined]
   [4] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [5] macro expansion
     @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:49 [inlined]

errors when number of observations is not fixed: Test Failed at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:50
  Expression: sample(fail_smc(), SMC(), 100)
    Expected: "number of observations"
     Message: "MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)\nThe type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.\n\nClosest candidates are:\n  Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)\n   @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860\n  Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)\n   @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893\n"
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:14
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [3] macro expansion
     @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:40 [inlined]
   [4] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [5] macro expansion
     @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:50 [inlined]

chain log-density metadata: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:53
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; nparticles::Int64, initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:181
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:166 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; check_model::Bool, chain_type::Type, initial_params::DynamicPPL.InitFromPrior, progress::Bool, discard_initial::Int64, thinning::Int64, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:151
   [27] sample
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:129 [inlined]
   [28] #sample#3
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
   [29] sample(model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
   [30] test_chain_logp_metadata(spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}})
      @ Main.SamplerTestUtils ~/.julia/packages/Turing/4hMHm/test/test_utils/sampler.jl:22
   [31] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:14
   [32] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [33] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:54 [inlined]
   [34] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [35] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:54 [inlined]
   [36] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [37] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [38] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [39] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [40] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [41] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [42] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [43] top-level scope
      @ none:6
   [44] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [45] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [46] _start()
      @ Base ./client.jl:593

logevidence: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:57
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#test#test##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#test#test##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#test#test##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#test#test##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; nparticles::Int64, initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:181
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:166 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; check_model::Bool, chain_type::Type, initial_params::DynamicPPL.InitFromPrior, progress::Bool, discard_initial::Int64, thinning::Int64, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:151
   [27] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:129
   [28] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:14
   [29] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [30] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:58 [inlined]
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:68 [inlined]
   [33] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [34] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [35] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [36] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [39] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [40] top-level scope
      @ none:6
   [41] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [42] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [43] _start()
      @ Base ./client.jl:593

discard_initial and thinning are ignored: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:102
  Test threw exception
  Expression: sample(normal(), SMC(), 10; discard_initial = 5)
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#4#5", DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#4#5", DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#4#5", DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#4#5", DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; nparticles::Int64, initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:181
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:166 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{TestLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::TestLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; check_model::Bool, chain_type::Type, initial_params::DynamicPPL.InitFromPrior, progress::Bool, discard_initial::Int64, thinning::Int64, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:151
   [27] sample
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:129 [inlined]
   [28] sample(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; kwargs::@Kwargs{discard_initial::Int64})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
   [29] (::Main.ParticleMCMCTests.var"#6#7")()
      @ Main.ParticleMCMCTests ./none:-1
   [30] with_logstate(f::Main.ParticleMCMCTests.var"#6#7", logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [31] with_logger(f::Function, logger::TestLogger)
      @ Base.CoreLogging ./logging/logging.jl:653
   [32] collect_test_logs(f::Function; kwargs::@Kwargs{})
      @ Test /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:126 [inlined]
   [33] collect_test_logs(f::Function)
      @ Test /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:124 [inlined]
   [34] match_logs(f::Function, patterns::Tuple{Symbol, Regex}; match_mode::Symbol, kwargs::@Kwargs{})
      @ Test /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:307 [inlined]
   [35] match_logs(f::Function, patterns::Tuple{Symbol, Regex})
      @ Test /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:306
   [36] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:14
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:94 [inlined]
   [39] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [40] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:102 [inlined]
┌ Warning: SMC samplers do not support `discard_initial` or `thinning`. These keyword arguments will be ignored.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:149

discard_initial and thinning are ignored: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:93
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#4#5", DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#4#5", DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#4#5", DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#4#5", DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#50#51"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; nparticles::Int64, initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:181
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:166 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64}, Random.TaskLocalRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, nparticles::Int64})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; check_model::Bool, chain_type::Type, initial_params::DynamicPPL.InitFromPrior, progress::Bool, discard_initial::Int64, thinning::Int64, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:151
   [27] sample
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:129 [inlined]
   [28] sample(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; kwargs::@Kwargs{discard_initial::Int64})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
   [29] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:14
   [30] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [31] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:94 [inlined]
   [32] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [33] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:103 [inlined]
   [34] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [35] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [36] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [37] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [38] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [39] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [40] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [41] top-level scope
      @ none:6
   [42] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [43] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [44] _start()
      @ Base ./client.jl:593
┌ Warning: It looks like you are using `Threads.@threads` in your model definition.
│ 
│ Note that since version 0.39 of DynamicPPL, threadsafe evaluation of models is disabled by default. If you need it, you will need to explicitly enable it by creating the model, and then running `model = setthreadsafe(model, true)`.
│ 
│ Threadsafe model evaluation is only needed when parallelising tilde-statements (not arbitrary Julia code), and avoiding it can often lead to significant performance improvements.
│ 
│ Please see https://turinglang.org/docs/usage/threadsafe-evaluation/ for more details of when threadsafe evaluation is actually required.
└ @ DynamicPPL ~/.julia/packages/DynamicPPL/pqVkv/src/compiler.jl:357

chain log-density metadata: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:140
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [27] sample
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
   [28] #sample#3
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
   [29] sample(model::DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
   [30] test_chain_logp_metadata(spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}})
      @ Main.SamplerTestUtils ~/.julia/packages/Turing/4hMHm/test/test_utils/sampler.jl:22
   [31] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:122
   [32] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [33] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:141 [inlined]
   [34] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [35] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:141 [inlined]
   [36] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [37] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [38] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [39] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [40] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [41] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [42] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [43] top-level scope
      @ none:6
   [44] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [45] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [46] _start()
      @ Base ./client.jl:593

logevidence: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:144
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#test#test##1", DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#test#test##1", DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#test#test##1", DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#test#test##1", DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [27] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94
   [28] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:122
   [29] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [30] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:145 [inlined]
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:155 [inlined]
   [33] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [34] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [35] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [36] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [39] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [40] top-level scope
      @ none:6
   [41] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [42] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [43] _start()
      @ Base ./client.jl:593

reference particle: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:165
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] TapedTask
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [27] sample
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
   [28] #sample#3
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
   [29] sample(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
   [30] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:122
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:166 [inlined]
   [33] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [34] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:166 [inlined]
   [35] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [36] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [39] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [40] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [41] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [42] top-level scope
      @ none:6
   [43] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [44] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [45] _start()
      @ Base ./client.jl:593

addlogprob leads to reweighting: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:171
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [27] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94
   [28] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:122
   [29] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [30] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:174 [inlined]
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:184 [inlined]
   [33] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [34] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [35] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [36] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [39] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [40] top-level scope
      @ none:6
   [41] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [42] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [43] _start()
      @ Base ./client.jl:593

keyword argument handling: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:189
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{typeof(Core.kwcall), @NamedTuple{n::Float64}, Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{n::Float64})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] TapedTask
      @ ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401 [inlined]
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64}, @NamedTuple{n::Float64}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64}, @NamedTuple{n::Float64}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64}, @NamedTuple{n::Float64}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [27] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#kwarg_demo#kwarg_demo##0"{Main.ParticleMCMCTests.var"#kwarg_demo#12#16"}, (:y,), (:n,), (), Tuple{Float64}, Tuple{Float64}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94
   [28] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:122
   [29] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [30] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:190 [inlined]
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:195 [inlined]
   [33] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [34] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [35] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [36] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [39] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [40] top-level scope
      @ none:6
   [41] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [42] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [43] _start()
      @ Base ./client.jl:593

submodels without kwargs: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:204
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#nested#nested##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#nested#nested##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#nested#nested##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#nested#nested##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [27] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94
   [28] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:122
   [29] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [30] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:205 [inlined]
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:217 [inlined]
   [33] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [34] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [35] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [36] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [39] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [40] top-level scope
      @ none:6
   [41] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [42] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [43] _start()
      @ Base ./client.jl:593

submodels with kwargs: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:221
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [27] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94
   [28] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:122
   [29] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [30] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:222 [inlined]
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/particle_mcmc.jl:231 [inlined]
   [33] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [34] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [35] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [36] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [39] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [40] top-level scope
      @ none:6
   [41] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [42] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [43] _start()
      @ Base ./client.jl:593
[ Info: (varname = s, exact = 2.0416666666666665, evaluated = 2.0703723323764933)
[ Info: (varname = m, exact = 1.1666666666666667, evaluated = 1.159950127444649)
[ Info: Testing emcee with large number of iterations
[ Info: (varname = s, exact = 2.0416666666666665, evaluated = 2.041349397195655)
[ Info: (varname = m, exact = 1.1666666666666667, evaluated = 1.1787532039447761)
[ Info: Starting ESS tests
[ Info: Starting ESS inference tests
[ Info: (varname = m, exact = 0.8, evaluated = 0.8172942592919593)
[ Info: (varname = m[1], exact = 0.0, evaluated = -0.02456171083886478)
[ Info: (varname = m[2], exact = 0.8, evaluated = 0.8075869528540663)

gdemo with CSMC + ESS: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:61
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   ┌[18] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [20] step_warmup(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [21] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [22] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [23] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [24] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [25] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [26] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [27] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [28] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [29] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [30] mcmcsample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [31] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [32] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94
    [33] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:14
    [34] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [35] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:48 [inlined]
    [36] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [37] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:62 [inlined]
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:63 [inlined]
    [40] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [41] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
    [42] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [43] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
    [44] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [45] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
    [46] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [47] top-level scope
       @ none:6
    [48] eval(m::Module, e::Any)
       @ Core ./boot.jl:517
    [49] exec_options(opts::Base.JLOptions)
       @ Base ./client.jl:318
    [50] _start()
       @ Base ./client.jl:593

MoGtest_default with CSMC + ESS: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:67
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS, Turing.Inference.ESS}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   ┌[18] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [20] step_warmup(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{3, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS, Turing.Inference.ESS}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [21] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [22] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [23] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [24] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [25] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{3, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS, Turing.Inference.ESS}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [26] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, StableRNGs.LehmerRNG, DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{3, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS, Turing.Inference.ESS}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [27] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [28] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [29] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [30] mcmcsample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{3, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS, Turing.Inference.ESS}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [31] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{3, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS, Turing.Inference.ESS}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [32] sample(rng::StableRNGs.LehmerRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{3, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS, Turing.Inference.ESS}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94
    [33] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:14
    [34] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [35] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:48 [inlined]
    [36] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [37] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:68 [inlined]
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/ess.jl:73 [inlined]
    [40] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [41] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
    [42] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [43] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:46 [inlined]
    [44] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [45] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
    [46] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [47] top-level scope
       @ none:6
    [48] eval(m::Module, e::Any)
       @ Core ./boot.jl:517
    [49] exec_options(opts::Base.JLOptions)
       @ Base ./client.jl:318
    [50] _start()
       @ Base ./client.jl:593
[ Info: Skipping test_sampler_analytical for demo_nested_colons due to MCMCChains limitations.
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
WARNING: Method definition (::Type{GibbsTests.Wrapper{T} where T})(T) where {T<:Real} in module GibbsTests at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:36 overwritten at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:199.
WARNING: Method definition (::Type{GibbsTests.Wrapper{T<:Real}})(Any) in module GibbsTests at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:36 overwritten at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:199.

Sampler call order: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:149
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{Main.GibbsTests.var"#test_model#test_model##1", DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Int64, DynamicPPL.TypeWrap{Vector{Float64}}}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{Main.GibbsTests.var"#test_model#test_model##1", DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{Main.GibbsTests.var"#test_model#test_model##1", DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{Main.GibbsTests.var"#test_model#test_model##1", DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, DynamicPPL.DefaultContext}, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step(::Random.TaskLocalRNG, ::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}}, DynamicPPL.DefaultContext}, false}, ::Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
      @ Main.GibbsTests ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:195
   [17] step
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:187 [inlined]
   [18] #step_warmup#9
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [19] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, samplers::Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}, states::Tuple{DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{6, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :n), Tuple{Float64, Int64}}}, MHLinkedValues::DynamicPPL.VNTAccumulator{:MHLinkedValues, typeof(Turing.Inference.store_linked_values), DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}, MHUnspecifiedPriors::DynamicPPL.VNTAccumulator{:MHUnspecifiedPriors, Turing.Inference.StoreUnspecifiedPriors, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{Distributions.Normal{Float64}}}}}}}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{6, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :n), Tuple{Float64, Int64, Int64}}}, MHLinkedValues::DynamicPPL.VNTAccumulator{:MHLinkedValues, typeof(Turing.Inference.store_linked_values), DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}, MHUnspecifiedPriors::DynamicPPL.VNTAccumulator{:MHUnspecifiedPriors, Turing.Inference.StoreUnspecifiedPriors, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   [20] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, samplers::Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r, :n), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, Int64}}, states::Tuple{DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{6, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :n), Tuple{Float64, Int64}}}, MHLinkedValues::DynamicPPL.VNTAccumulator{:MHLinkedValues, typeof(Turing.Inference.store_linked_values), DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}, MHUnspecifiedPriors::DynamicPPL.VNTAccumulator{:MHUnspecifiedPriors, Turing.Inference.StoreUnspecifiedPriors, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{Distributions.Normal{Float64}}}}}}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:571
   [21] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, samplers::Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{Float64, Int64, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{Float64}}, DynamicPPL.VarNamedTuples.PartialArray{Float64, 1, Vector{Float64}, Vector{Bool}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:571
   [22] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{12, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
   [23] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [24] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [25] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [26] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{12, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [27] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{12, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [28] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [29] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [30] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [31] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{12, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [32] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{12, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [33] sample
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
   [34] #sample#3
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
   [35] sample(model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1100")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{12, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:xs, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:ys, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:q, AbstractPPL.Property{:a, AbstractPPL.Iden}}}, Vector{AbstractPPL.VarName{:r, AbstractPPL.Index{Tuple{Int64}, @NamedTuple{}, AbstractPPL.Iden}}}}, Tuple{Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.NUTS{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.DiagEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}, Main.GibbsTests.AlgWrapper{Turing.Inference.MH{Returns{DynamicPPL.InitFromPrior}, DynamicPPL.UnlinkAll}}}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
   [36] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:152
   [37] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [38] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:245 [inlined]
   [39] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [40] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [41] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [42] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:56 [inlined]
   [43] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [44] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [45] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [46] top-level scope
      @ none:6
   [47] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [48] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [49] _start()
      @ Base ./client.jl:593
[ Info: Starting Gibbs tests

Gibbs constructors: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:379
  Test threw exception
  Expression: sample(gdemo_default, s2, N) isa VNChain
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] TapedTask
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   ┌[18] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [20] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{1, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [21] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [22] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [23] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [24] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [25] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{1, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [26] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{1, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [27] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [28] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [29] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [30] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{1, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [31] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{1, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [32] sample
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
    [33] #sample#3
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
    [34] sample(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{1, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
    [35] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
    [36] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [37] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:357 [inlined]
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:379 [inlined]
    [40] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:781 [inlined]

Gibbs constructors: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:380
  Test threw exception
  Expression: sample(gdemo_default, s3, N) isa VNChain
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] TapedTask
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMCDA{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   ┌[18] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [20] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMCDA{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [21] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [22] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [23] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [24] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [25] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMCDA{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [26] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMCDA{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [27] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [28] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [29] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [30] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMCDA{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [31] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMCDA{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [32] sample
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
    [33] #sample#3
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
    [34] sample(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMCDA{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
    [35] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
    [36] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [37] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:357 [inlined]
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:380 [inlined]
    [40] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:781 [inlined]

Gibbs constructors: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:382
  Test threw exception
  Expression: sample(gdemo_default, s5, N) isa VNChain
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] TapedTask
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{Turing.Inference.HMCState{AdvancedHMC.HMCKernel{AdvancedHMC.FullMomentumRefreshment, AdvancedHMC.Trajectory{AdvancedHMC.EndPointTS, AdvancedHMC.Leapfrog{Float64}, AdvancedHMC.FixedNSteps}}, AdvancedHMC.Hamiltonian{AdvancedHMC.UnitEuclideanMetric{Float64, Tuple{Int64}}, AdvancedHMC.GaussianKinetic, Base.Fix1{typeof(LogDensityProblems.logdensity), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Base.Fix1{typeof(LogDensityProblems.logdensity_and_gradient), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}, AdvancedHMC.PhasePoint{Vector{Float64}, AdvancedHMC.DualValue{Float64, Vector{Float64}}}, AdvancedHMC.Adaptation.NoAdaptation, DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Turing.Inference.HMCState{AdvancedHMC.HMCKernel{AdvancedHMC.FullMomentumRefreshment, AdvancedHMC.Trajectory{AdvancedHMC.EndPointTS, AdvancedHMC.Leapfrog{Float64}, AdvancedHMC.FixedNSteps}}, AdvancedHMC.Hamiltonian{AdvancedHMC.UnitEuclideanMetric{Float64, Tuple{Int64}}, AdvancedHMC.GaussianKinetic, Base.Fix1{typeof(LogDensityProblems.logdensity), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Base.Fix1{typeof(LogDensityProblems.logdensity_and_gradient), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}, AdvancedHMC.PhasePoint{Vector{Float64}, AdvancedHMC.DualValue{Float64, Vector{Float64}}}, AdvancedHMC.Adaptation.NoAdaptation, DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Turing.Inference.HMCState{AdvancedHMC.HMCKernel{AdvancedHMC.FullMomentumRefreshment, AdvancedHMC.Trajectory{AdvancedHMC.EndPointTS, AdvancedHMC.Leapfrog{Float64}, AdvancedHMC.FixedNSteps}}, AdvancedHMC.Hamiltonian{AdvancedHMC.UnitEuclideanMetric{Float64, Tuple{Int64}}, AdvancedHMC.GaussianKinetic, Base.Fix1{typeof(LogDensityProblems.logdensity), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Base.Fix1{typeof(LogDensityProblems.logdensity_and_gradient), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}, AdvancedHMC.PhasePoint{Vector{Float64}, AdvancedHMC.DualValue{Float64, Vector{Float64}}}, AdvancedHMC.Adaptation.NoAdaptation, DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
    [18] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{Turing.Inference.HMCState{AdvancedHMC.HMCKernel{AdvancedHMC.FullMomentumRefreshment, AdvancedHMC.Trajectory{AdvancedHMC.EndPointTS, AdvancedHMC.Leapfrog{Float64}, AdvancedHMC.FixedNSteps}}, AdvancedHMC.Hamiltonian{AdvancedHMC.UnitEuclideanMetric{Float64, Tuple{Int64}}, AdvancedHMC.GaussianKinetic, Base.Fix1{typeof(LogDensityProblems.logdensity), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Base.Fix1{typeof(LogDensityProblems.logdensity_and_gradient), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}, AdvancedHMC.PhasePoint{Vector{Float64}, AdvancedHMC.DualValue{Float64, Vector{Float64}}}, AdvancedHMC.Adaptation.NoAdaptation, DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Turing.Inference.HMCState{AdvancedHMC.HMCKernel{AdvancedHMC.FullMomentumRefreshment, AdvancedHMC.Trajectory{AdvancedHMC.EndPointTS, AdvancedHMC.Leapfrog{Float64}, AdvancedHMC.FixedNSteps}}, AdvancedHMC.Hamiltonian{AdvancedHMC.UnitEuclideanMetric{Float64, Tuple{Int64}}, AdvancedHMC.GaussianKinetic, Base.Fix1{typeof(LogDensityProblems.logdensity), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Base.Fix1{typeof(LogDensityProblems.logdensity_and_gradient), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}, AdvancedHMC.PhasePoint{Vector{Float64}, AdvancedHMC.DualValue{Float64, Vector{Float64}}}, AdvancedHMC.Adaptation.NoAdaptation, DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:571
    [19] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{Turing.Inference.HMCState{AdvancedHMC.HMCKernel{AdvancedHMC.FullMomentumRefreshment, AdvancedHMC.Trajectory{AdvancedHMC.EndPointTS, AdvancedHMC.Leapfrog{Float64}, AdvancedHMC.FixedNSteps}}, AdvancedHMC.Hamiltonian{AdvancedHMC.UnitEuclideanMetric{Float64, Tuple{Int64}}, AdvancedHMC.GaussianKinetic, Base.Fix1{typeof(LogDensityProblems.logdensity), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Base.Fix1{typeof(LogDensityProblems.logdensity_and_gradient), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}, AdvancedHMC.PhasePoint{Vector{Float64}, AdvancedHMC.DualValue{Float64, Vector{Float64}}}, AdvancedHMC.Adaptation.NoAdaptation, DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:571
    [20] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:571
   ┌[21] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [23] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{5, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [24] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [25] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [26] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [27] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [28] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{5, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [29] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{5, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [30] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [31] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [32] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [33] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{5, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [34] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{5, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [35] sample
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
    [36] #sample#3
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
    [37] sample(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{5, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
    [38] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
    [39] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [40] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:357 [inlined]
    [41] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [42] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:382 [inlined]
    [43] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:781 [inlined]

Gibbs constructors: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:383
  Test threw exception
  Expression: sample(gdemo_default, s6, N) isa VNChain
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] TapedTask
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo_d), DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/repeat_sampler.jl:80 [inlined]
    [18] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{Turing.Inference.HMCState{AdvancedHMC.HMCKernel{AdvancedHMC.FullMomentumRefreshment, AdvancedHMC.Trajectory{AdvancedHMC.EndPointTS, AdvancedHMC.Leapfrog{Float64}, AdvancedHMC.FixedNSteps}}, AdvancedHMC.Hamiltonian{AdvancedHMC.UnitEuclideanMetric{Float64, Tuple{Int64}}, AdvancedHMC.GaussianKinetic, Base.Fix1{typeof(LogDensityProblems.logdensity), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}, Base.Fix1{typeof(LogDensityProblems.logdensity_and_gradient), DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}, AdvancedHMC.PhasePoint{Vector{Float64}, AdvancedHMC.DualValue{Float64, Vector{Float64}}}, AdvancedHMC.Adaptation.NoAdaptation, DynamicPPL.LogDensityFunction{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}, DifferentiationInterfaceForwardDiffExt.ForwardDiffGradientPrep{Tuple{typeof(DynamicPPL.logdensity_at), ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, Vector{Float64}, Tuple{DifferentiationInterface.Constant{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndTransform{DynamicPPL.DynamicLink}}}}, DifferentiationInterface.Constant{DynamicPPL.LinkAll}, DifferentiationInterface.Constant{DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}}, ForwardDiff.GradientConfig{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}, Float64, 1}}}, NTuple{5, Nothing}}, Vector{Float64}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}, false}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
    [19] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.RepeatSampler{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:571
   ┌[20] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [22] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.RepeatSampler{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [23] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [24] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [25] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [26] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [27] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.RepeatSampler{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.RepeatSampler{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [29] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [30] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [31] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [32] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.RepeatSampler{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [33] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.RepeatSampler{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [34] sample
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
    [35] #sample#3
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
    [36] sample(model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.RepeatSampler{Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
    [37] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:357 [inlined]
    [40] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [41] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:383 [inlined]
    [42] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:781 [inlined]

CSMC and HMC on gdemo: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:389
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   ┌[18] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [20] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [21] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [22] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [23] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [24] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [25] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [26] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [27] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [28] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [29] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [30] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [31] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [32] sample
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
    [33] #sample#3
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
    [34] sample(model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
    [35] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
    [36] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [37] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:389 [inlined]
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:390 [inlined]
    [40] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [41] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:391 [inlined]
    [42] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [43] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
    [44] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [45] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:56 [inlined]
    [46] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [47] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
    [48] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [49] top-level scope
       @ none:6
    [50] eval(m::Module, e::Any)
       @ Core ./boot.jl:517
    [51] exec_options(opts::Base.JLOptions)
       @ Base ./client.jl:318
    [52] _start()
       @ Base ./client.jl:593
┌ Info: Found initial step size
└   ϵ = 1.6
[ Info: (varname = s, exact = 2.0416666666666665, evaluated = 2.1066878216673537)
[ Info: (varname = m, exact = 1.1666666666666667, evaluated = 1.1887493336099382)

CSMC and ESS on gdemo: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:403
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{Float64, Float64}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   ┌[18] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [20] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [21] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [22] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [23] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [24] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [25] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [26] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [27] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [28] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [29] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [30] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [31] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [32] sample
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
    [33] #sample#3
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
    [34] sample(model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.ESS}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
    [35] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
    [36] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [37] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:389 [inlined]
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:404 [inlined]
    [40] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [41] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:405 [inlined]
    [42] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [43] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
    [44] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [45] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:56 [inlined]
    [46] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [47] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
    [48] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [49] top-level scope
       @ none:6
    [50] eval(m::Module, e::Any)
       @ Core ./boot.jl:517
    [51] exec_options(opts::Base.JLOptions)
       @ Base ./client.jl:318
    [52] _start()
       @ Base ./client.jl:593

CSMC on gdemo: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:410
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
    [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
    [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
    [3] optimise_ir!(ir::Compiler.IRCode)
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
    [4] build_callable(sig::Type{Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
    [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
    [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
      @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
    [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
    [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
    [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, Tuple{typeof(Main.Models.gdemo), DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Float64, Float64}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
      @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
   [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
   [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}})(::Int64)
      @ Turing.Inference ./none:-1
   [12] iterate
      @ ./generator.jl:48 [inlined]
   [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}}})
      @ Base ./array.jl:833
   [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
   [15] step
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
   [16] step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
   [17] #_step_or_step_warmup#25
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
   [18] _step_or_step_warmup
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
   [19] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
   [20] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64})()
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
   [21] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
      @ Base.CoreLogging ./logging/logging.jl:542
   [22] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
      @ Base.CoreLogging ./logging/logging.jl:653
   [23] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
   [24] macro expansion
      @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
   [25] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
      @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
   [26] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
   [27] sample
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
   [28] #sample#3
      @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
   [29] sample(model::DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, N::Int64)
      @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
   [30] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
   [31] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [32] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:389 [inlined]
   [33] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [34] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:411 [inlined]
   [35] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [36] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:412 [inlined]
   [37] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [38] top-level scope
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
   [39] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [40] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:56 [inlined]
   [41] macro expansion
      @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [42] macro expansion
      @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
   [43] include(mapexpr::Function, mod::Module, _path::String)
      @ Base ./Base.jl:327
   [44] top-level scope
      @ none:6
   [45] eval(m::Module, e::Any)
      @ Core ./boot.jl:517
   [46] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:318
   [47] _start()
      @ Base ./client.jl:593

PG and HMC on MoGtest_default: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:416
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   ┌[18] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [20] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [21] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [22] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [23] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [24] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [25] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [26] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [27] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [28] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [29] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [30] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [31] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [32] sample
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
    [33] #sample#3
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
    [34] sample(model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{2, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
    [35] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
    [36] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [37] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:389 [inlined]
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:417 [inlined]
    [40] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [41] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:421 [inlined]
    [42] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [43] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
    [44] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [45] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:56 [inlined]
    [46] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [47] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
    [48] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [49] top-level scope
       @ none:6
    [50] eval(m::Module, e::Any)
       @ Core ./boot.jl:517
    [51] exec_options(opts::Base.JLOptions)
       @ Base ./client.jl:318
    [52] _start()
       @ Base ./client.jl:593
[ Info: (varname = s, exact = 2.0416666666666665, evaluated = 2.1021788421430716)
[ Info: (varname = m, exact = 1.1666666666666667, evaluated = 1.1760477860471288)

Multiple overlapping samplers on MoGtest_default: Error During Test at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:439
  Got exception outside of a @test
  MethodError: no method matching Compiler.IRInterpretationState(::Compiler.NativeInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64, ::UInt64)
  The type `Compiler.IRInterpretationState` exists, but no method is defined for this combination of argument types when trying to construct it.
  Closest candidates are:
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, ::Compiler.SpecInfo, ::Compiler.IRCode, ::Core.MethodInstance, ::Vector{Any}, ::UInt64, ::UInt64)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:860
    Compiler.IRInterpretationState(::Compiler.AbstractInterpreter, !Matched::Core.CodeInstance, !Matched::Core.MethodInstance, !Matched::Vector{Any}, ::Any)
     @ Base /opt/julia/share/julia/Compiler/src/inferencestate.jl:893
  Stacktrace:
     [1] __infer_ir!(ir::Compiler.IRCode, interp::Compiler.NativeInterpreter, mi::Core.MethodInstance)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:115
     [2] optimise_ir!(ir::Compiler.IRCode; show_ir::Bool, do_inline::Bool)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:52
     [3] optimise_ir!(ir::Compiler.IRCode)
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/utils.jl:40
     [4] build_callable(sig::Type{Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:189
     [5] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any}; kwargs::@Kwargs{})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:411
     [6] Libtask.TapedTask(::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, ::Function, ::Vararg{Any})
       @ Libtask ~/.julia/packages/Libtask/MQIAO/src/copyable_task.jl:401
     [7] Libtask.TapedTask(taped_globals::AdvancedPSLibtaskExt.TapedGlobals{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}, model::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:79 [inlined]
     [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:38
     [9] AdvancedPS.Trace(::Turing.Inference.TracedModel{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, Tuple{typeof(Main.Models.MoGtest), DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, Matrix{Float64}}, @NamedTuple{}}, ::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}})
       @ AdvancedPSLibtaskExt ~/.julia/packages/AdvancedPS/ZHu61/ext/AdvancedPSLibtaskExt.jl:107
    [10] AdvancedPS.Trace(model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.OnlyAccsVarInfo{DynamicPPL.AccumulatorTuple{4, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}, RawValues::DynamicPPL.VNTAccumulator{:RawValues, DynamicPPL.GetRawValues, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:474
    [11] (::Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}})(::Int64)
       @ Turing.Inference ./none:-1
    [12] iterate
       @ ./generator.jl:48 [inlined]
    [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#55#56"{DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}}})
       @ Base ./array.jl:833
    [14] step(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:297
    [15] step
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/particle_mcmc.jl:287 [inlined]
    [16] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:z1, AbstractPPL.Iden}, AbstractPPL.VarName{:z2, AbstractPPL.Iden}, AbstractPPL.VarName{:z3, AbstractPPL.Iden}, AbstractPPL.VarName{:z4, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}; kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, verbose::Bool, discard_sample::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined]
    [17] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::typeof(AbstractMCMC.step_warmup), varname_vecs::Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Turing.Inference.ESS, Turing.Inference.ESS, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, vnt::DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{Float64, Float64, Vararg{Int64, 4}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:553
   ┌[18] gibbs_initialstep_recursive
   │   @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:530 [inlined]
   ╰──── repeated 2 times
    [20] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{7, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Turing.Inference.ESS, Turing.Inference.ESS, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}; initial_params::DynamicPPL.InitFromPrior, discard_sample::Bool, kwargs::@Kwargs{num_warmup::Int64, verbose::Bool})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:504
    [21] step_warmup
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/gibbs.jl:489 [inlined]
    [22] #_step_or_step_warmup#25
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined]
    [23] _step_or_step_warmup
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined]
    [24] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined]
    [25] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{7, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Turing.Inference.ESS, Turing.Inference.ESS, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, Int64, Float64, Int64})()
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:134
    [26] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{FlexiChains.VNChain}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool}, Random.TaskLocalRNG, DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, Turing.Inference.Gibbs{7, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Turing.Inference.ESS, Turing.Inference.ESS, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, Int64, Float64, Int64}, logstate::Base.CoreLogging.LogState)
       @ Base.CoreLogging ./logging/logging.jl:542
    [27] with_logger(f::Function, logger::LoggingExtras.TeeLogger{Tuple{LoggingExtras.EarlyFilteredLogger{TerminalLoggers.TerminalLogger, AbstractMCMC.var"#with_progresslogger##0#with_progresslogger##1"{Module}}, LoggingExtras.EarlyFilteredLogger{Base.CoreLogging.ConsoleLogger, AbstractMCMC.var"#with_progresslogger##2#with_progresslogger##3"{Module}}}})
       @ Base.CoreLogging ./logging/logging.jl:653
    [28] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger)
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157
    [29] macro expansion
       @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined]
    [30] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, sampler::Turing.Inference.Gibbs{7, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Turing.Inference.ESS, Turing.Inference.ESS, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64; progress::Bool, progressname::String, callback::Nothing, num_warmup::Int64, discard_initial::Int64, thinning::Int64, chain_type::Type, initial_state::Nothing, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, verbose::Bool})
       @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204
    [31] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{7, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Turing.Inference.ESS, Turing.Inference.ESS, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64; initial_params::DynamicPPL.InitFromPrior, check_model::Bool, chain_type::Type, verbose::Bool, kwargs::@Kwargs{})
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:106
    [32] sample
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:94 [inlined]
    [33] #sample#3
       @ ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:91 [inlined]
    [34] sample(model::DynamicPPL.Model{typeof(Main.Models.MoGtest), (:D,), (), (), Tuple{Matrix{Float64}}, Tuple{}, DynamicPPL.DefaultContext, false}, spl::Turing.Inference.Gibbs{7, Tuple{Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}, Vector{AbstractPPL.VarName{:mu1, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{:mu2, AbstractPPL.Iden}}, Vector{AbstractPPL.VarName{sym, AbstractPPL.Iden} where sym}}, Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMC{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}, Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, Turing.Inference.ESS, Turing.Inference.ESS, Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, N::Int64)
       @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/abstractmcmc.jl:88
    [35] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:352
    [36] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [37] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:389 [inlined]
    [38] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [39] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:440 [inlined]
    [40] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [41] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:449 [inlined]
    [42] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [43] top-level scope
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:33
    [44] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [45] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:56 [inlined]
    [46] macro expansion
       @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
    [47] macro expansion
       @ ~/.julia/packages/Turing/4hMHm/test/runtests.jl:25 [inlined]
    [48] include(mapexpr::Function, mod::Module, _path::String)
       @ Base ./Base.jl:327
    [49] top-level scope
       @ none:6
    [50] eval(m::Module, e::Any)
       @ Core ./boot.jl:517
    [51] exec_options(opts::Base.JLOptions)
       @ Base ./client.jl:318
    [52] _start()
       @ Base ./client.jl:593
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: There were 1 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Warning: There were 1 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: There were 1 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Warning: There were 1 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: There were 2 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 6.4
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel
└ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544
┌ Info: Found initial step size
└   ϵ = 1.6

======================================================================================
Information request received. A stacktrace will print followed by a 1.0 second profile.
--trace-compile is enabled during profile collection.
======================================================================================

cmd: /opt/julia/bin/julia 97 running 1 of 1

signal (10): User defined signal 1
_ZNK4llvm5Value33stripAndAccumulateConstantOffsetsERKNS_10DataLayoutERNS_5APIntEbbNS_12function_refIFbRS0_S5_EEE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN4llvm32GetPointerBaseWithConstantOffsetEPNS_5ValueERlRKNS_10DataLayoutEb.constprop.0 at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN12_GLOBAL__N_18DSEState11isOverwriteEPKN4llvm11InstructionES4_RKNS1_14MemoryLocationES7_RlS8_ at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN12_GLOBAL__N_18DSEState15getDomMemoryDefEPN4llvm9MemoryDefEPNS1_12MemoryAccessERKNS1_14MemoryLocationEPKNS1_5ValueERjSC_bSC_b at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN12_GLOBAL__N_1L19eliminateDeadStoresERN4llvm8FunctionERNS0_9AAResultsERNS0_9MemorySSAERNS0_13DominatorTreeERNS0_17PostDominatorTreeERKNS0_17TargetLibraryInfoERKNS0_8LoopInfoE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN4llvm7DSEPass3runERNS_8FunctionERNS_15AnalysisManagerIS1_JEEE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
run at /source/usr/include/llvm/IR/PassManagerInternal.h:91:41
_ZN4llvm11PassManagerINS_8FunctionENS_15AnalysisManagerIS1_JEEEJEE3runERS1_RS3_ at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
run at /source/usr/include/llvm/IR/PassManagerInternal.h:91:41
_ZN4llvm27ModuleToFunctionPassAdaptor3runERNS_6ModuleERNS_15AnalysisManagerIS1_JEEE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
run at /source/usr/include/llvm/IR/PassManagerInternal.h:91:41
_ZN4llvm11PassManagerINS_6ModuleENS_15AnalysisManagerIS1_JEEEJEE3runERS1_RS3_ at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
run at /source/src/pipeline.cpp:977:12
operator() at /source/src/jitlayers.cpp:1298:17
operator() at /source/src/jitlayers.cpp:1435:12 [inlined]
optimizeModule at /source/src/jitlayers.cpp:2353:18
materialize at /source/src/jitlayers.cpp:905:31
_ZN4llvm3orc19MaterializationTask3runEv at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
dispatch at /source/src/julia-task-dispatcher.h:353:11
_ZN4llvm3orc16ExecutionSession22dispatchOutstandingMUsEv at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN4llvm3orc16ExecutionSession17OL_completeLookupESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EESt10shared_ptrINS0_23AsynchronousSymbolQueryEESt8functionIFvRKNS_8DenseMapIPNS0_8JITDylibENS_8DenseSetINS0_15SymbolStringPtrENS_12DenseMapInfoISF_vEEEENSG_ISD_vEENS_6detail12DenseMapPairISD_SI_EEEEEE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN4llvm3orc25InProgressFullLookupState8completeESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN4llvm3orc16ExecutionSession19OL_applyQueryPhase1ESt10unique_ptrINS0_21InProgressLookupStateESt14default_deleteIS3_EENS_5ErrorE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
_ZN4llvm3orc16ExecutionSession6lookupENS0_10LookupKindERKSt6vectorISt4pairIPNS0_8JITDylibENS0_19JITDylibLookupFlagsEESaIS8_EENS0_15SymbolLookupSetENS0_11SymbolStateENS_15unique_functionIFvNS_8ExpectedINS_8DenseMapINS0_15SymbolStringPtrENS0_17ExecutorSymbolDefENS_12DenseMapInfoISI_vEENS_6detail12DenseMapPairISI_SJ_EEEEEEEEESt8functionIFvRKNSH_IS6_NS_8DenseSetISI_SL_EENSK_IS6_vEENSN_IS6_SV_EEEEEE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line)
publishCIs at /source/src/jitlayers.cpp:2056:14
jl_compile_codeinst_impl at /source/src/jitlayers.cpp:510:39
jl_compile_method_internal at /source/src/gf.c:3650:27
_jl_invoke at /source/src/gf.c:4103:16 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
#step#28 at /home/pkgeval/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:205:220
step at /home/pkgeval/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:156:75 [inlined]
#step_warmup#9 at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118:10 [inlined]
step_warmup at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118:4 [inlined]
#_step_or_step_warmup#25 at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126:15 [inlined]
_step_or_step_warmup at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124:5 [inlined]
macro expansion at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223:9 [inlined]
macro expansion at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:137:11 [inlined]
#mcmcsample#27 at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204:179
mcmcsample at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164:122
unknown function (ip: 0x7e97c905e453) at (unknown file)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
#sample#27 at /home/pkgeval/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:119:46
sample at /home/pkgeval/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:85:76
unknown function (ip: 0x7e97c905d8f4) at (unknown file)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
#62 at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:684:146
unknown function (ip: 0x7e97c905d7af) at (unknown file)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
jl_apply at /source/src/julia.h:2327:12 [inlined]
start_task at /source/src/task.c:1275:19
unknown function (ip: (nil)) at (unknown file)


==============================================================
Profile collected. A report will print at the next yield point.
Disabling --trace-compile
==============================================================

┌ Info: Found initial step size
└   ϵ = 1.6
┌ Info: Found initial step size
└   ϵ = 0.8

======================================================================================
Information request received. A stacktrace will print followed by a 1.0 second profile.
--trace-compile is enabled during profile collection.
======================================================================================

cmd: /opt/julia/bin/julia 1 running 0 of 1

signal (10): User defined signal 1
epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404
uv_run at /workspace/srcdir/libuv/src/unix/core.c:430
ijl_task_get_next at /source/src/scheduler.c:457:34
wait at ./task.jl:1246:50
wait_forever at ./task.jl:1168:5
jfptr_wait_forever_0.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
jl_apply at /source/src/julia.h:2327:12 [inlined]
start_task at /source/src/task.c:1275:19
unknown function (ip: (nil)) at (unknown file)


==============================================================
Profile collected. A report will print at the next yield point.
Disabling --trace-compile
==============================================================

┌ Warning: There were no samples collected in one or more groups.
│ This may be due to idle threads, or you may need to run your
│ program longer (perhaps by running it multiple times),
│ or adjust the delay between samples with `Profile.init()`.
└ @ Profile /opt/julia/share/julia/stdlib/v1.14/Profile/src/Profile.jl:1361
Overhead ╎ [+additional indent] Count File:Line  Function
=========================================================
Thread 1 (default) Task 0x000076fa4f5f5ff0 Total snapshots: 480. Utilization: 0%
   ╎480 @Base/task.jl:1168  wait_forever()
479╎ 480 @Base/task.jl:1246  wait()

┌ Info: Found initial step size
└   ϵ = 1.6
┌ Warning: There were 1 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483
┌ Warning: There were no samples collected in one or more groups.
│ This may be due to idle threads, or you may need to run your
│ program longer (perhaps by running it multiple times),
│ or adjust the delay between samples with `Profile.init()`.
└ @ Profile /opt/julia/share/julia/stdlib/v1.14/Profile/src/Profile.jl:1361
Overhead ╎ [+additional indent] Count File:Line  Function
=========================================================
Thread 1 (default) Task 0x00007e9798132860 Total snapshots: 93. Utilization: 100%
  ╎92 @AbstractMCMC/…sample.jl:684  (::AbstractMCMC.var"#62#63"{Turing.Inferenc…
  ╎ 92 @Turing/src/mcmc/hmc.jl:85  kwcall(::@NamedTuple{progress::Bool, initial…
  ╎  92 @Turing/…rc/mcmc/hmc.jl:119  sample(rng::StableRNGs.LehmerRNG, model::D…
  ╎   92 @AbstractMCMC/…ample.jl:164  kwcall(::@NamedTuple{chain_type::UnionAll…
  ╎    92 @AbstractMCMC/…mple.jl:204  mcmcsample(rng::StableRNGs.LehmerRNG, mod…
  ╎     92 @AbstractMCMC/…ging.jl:137  iterate(r::UnitRange{Int64})
  ╎    ╎ 92 @AbstractMCMC/…mple.jl:255  macro expansion
  ╎    ╎  92 @AbstractMCMC/…ple.jl:124  _step_or_step_warmup
  ╎    ╎   92 @AbstractMCMC/…mple.jl:0  _step_or_step_warmup(::Int64, ::Int64, …
  ╎    ╎    92 @Compiler/…einfer.jl:1732  typeinf_ext_toplevel(mi::Core.MethodI…
  ╎    ╎     92 @Compiler/…einfer.jl:1723  typeinf_ext_toplevel(interp::Compile…
  ╎    ╎    ╎ 92 @Compiler/…infer.jl:1537  typeinf_ext(interp::Compiler.NativeI…
  ╎    ╎    ╎  1  @Compiler/…ation.jl:4859  typeinf(interp::Compiler.NativeInte…
 1╎    ╎    ╎   1  @Compiler/…tate.jl:1235  doworkloop(interp::Compiler.NativeI…
  ╎    ╎    ╎  58 @Compiler/…ation.jl:4868  typeinf(interp::Compiler.NativeInte…
  ╎    ╎    ╎   58 @Compiler/…tion.jl:4590  typeinf_local(interp::Compiler.Nati…
  ╎    ╎    ╎    58 @Compiler/…tion.jl:4006  init_slot_aliases!(slot_aliases::V…
  ╎    ╎    ╎     58 @Compiler/…tion.jl:4049  getindex(A::Vector{Union{Nothing,…
  ╎    ╎    ╎    ╎ 58 @Compiler/…ion.jl:3642  abstract_eval_statement_expr(inte…
  ╎    ╎    ╎    ╎  58 @Compiler/…ion.jl:3278  abstract_eval_call(interp::Compi…
  ╎    ╎    ╎    ╎   58 @Compiler/…on.jl:3260  abstract_call(interp::Compiler.N…
  ╎    ╎    ╎    ╎    58 @Compiler/…on.jl:3100  call_result_unused(sv::Compiler…
  ╎    ╎    ╎    ╎     58 @Compiler/…on.jl:3107  abstract_call(interp::Compiler…
  ╎    ╎    ╎    ╎    ╎ 1  @Compiler/…n.jl:2851  abstract_call_known(interp::Co…
  ╎    ╎    ╎    ╎    ╎  1  @Compiler/…n.jl:2048  abstract_apply(interp::Compil…
  ╎    ╎    ╎    ╎    ╎   1  @Compiler/….jl:2028  (::Compiler.var"#infercalls#a…
  ╎    ╎    ╎    ╎    ╎    1  @Compiler/….jl:3107  abstract_call(interp::Compil…
  ╎    ╎    ╎    ╎    ╎     1  @Compiler/….jl:2999  abstract_call_known(interp:…
  ╎    ╎    ╎    ╎    ╎    ╎ 1  @Compiler/….jl:131  abstract_call_gf_by_type(in…
  ╎    ╎    ╎    ╎    ╎    ╎  1  @Compiler/…jl:344  kwcall(::@NamedTuple{max_me…
  ╎    ╎    ╎    ╎    ╎    ╎   1  @Compiler/…jl:349  #find_method_matches#139
  ╎    ╎    ╎    ╎    ╎    ╎    1  @Compiler/…l:359  find_union_split_method_ma…
  ╎    ╎    ╎    ╎    ╎    ╎     1  @Compiler/…l:371  find_union_split_method_m…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎ 1  @Compiler/…l:110  intersect(a::Compiler.Wo…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎  1  @Compiler/…l:113  findall(sig::Type, tabl…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎   1  @Compiler/…l:70  kwcall(::@NamedTuple{li…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎    1  @Compiler/…l:70  findall(sig::DataType,…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎     1  @Compiler/…l:105  _findall(sig::DataTy…
 1╎    ╎    ╎    ╎    ╎    ╎    ╎    ╎ 1  @Base/…ls.jl:1609  getindex(b::Base.R…
  ╎    ╎    ╎    ╎    ╎ 57 @Compiler/…n.jl:2999  abstract_call_known(interp::Co…
  ╎    ╎    ╎    ╎    ╎  51 @Compiler/…n.jl:131  abstract_call_gf_by_type(inter…
  ╎    ╎    ╎    ╎    ╎   51 @Compiler/…n.jl:344  kwcall(::@NamedTuple{max_meth…
  ╎    ╎    ╎    ╎    ╎    51 @Compiler/….jl:351  #find_method_matches#139
  ╎    ╎    ╎    ╎    ╎     51 @Compiler/….jl:391  find_simple_method_matches(i…
  ╎    ╎    ╎    ╎    ╎    ╎ 51 @Compiler/….jl:110  findall
  ╎    ╎    ╎    ╎    ╎    ╎  51 @Compiler/…jl:113  findall(sig::Type, table::C…
  ╎    ╎    ╎    ╎    ╎    ╎   51 @Compiler/…jl:70  kwcall(::@NamedTuple{limit:…
  ╎    ╎    ╎    ╎    ╎    ╎    51 @Compiler/…jl:70  findall(sig::DataType, tab…
  ╎    ╎    ╎    ╎    ╎    ╎     51 @Compiler/…l:105  _findall(sig::DataType, m…
51╎    ╎    ╎    ╎    ╎    ╎    ╎ 51 @Base/…ls.jl:1609  getindex(b::Base.RefVal…
  ╎    ╎    ╎    ╎    ╎  6  @Compiler/…n.jl:340  abstract_call_gf_by_type(inter…
  ╎    ╎    ╎    ╎    ╎   4  @Compiler/…n.jl:178  (::Compiler.var"#infercalls#a…
  ╎    ╎    ╎    ╎    ╎    4  @Compiler/….jl:769  abstract_call_method(interp::…
  ╎    ╎    ╎    ╎    ╎     1  @Compiler/….jl:1147  typeinf_edge(interp::Compil…
  ╎    ╎    ╎    ╎    ╎    ╎ 1  @Base/…als.jl:1783  specialize_method(method::M…
 1╎    ╎    ╎    ╎    ╎    ╎  1  @Base/…als.jl:1796  specialize_method(method::…
  ╎    ╎    ╎    ╎    ╎     3  @Compiler/….jl:1233  typeinf_edge(interp::Compil…
  ╎    ╎    ╎    ╎    ╎    ╎ 2  @Compiler/….jl:626  return_cached_result(interp…
  ╎    ╎    ╎    ╎    ╎    ╎  2  @Compiler/…jl:121  retrieve_code_info(mi::Core…
  ╎    ╎    ╎    ╎    ╎    ╎   2  @Compiler/…jl:88  get_staged(mi::Core.MethodI…
  ╎    ╎    ╎    ╎    ╎    ╎    2  @Compiler/…jl:0  call_get_staged(mi::Core.Me…
  ╎    ╎    ╎    ╎    ╎    ╎     2  @Base/…pr.jl:1849  (::Core.GeneratedFunctio…
 2╎    ╎    ╎    ╎    ╎    ╎    ╎ 2  @Base/…pr.jl:1811  generated_body_to_codei…
  ╎    ╎    ╎    ╎    ╎    ╎ 1  @Compiler/….jl:629  return_cached_result(interp…
  ╎    ╎    ╎    ╎    ╎    ╎  1  @Compiler/…jl:365  Compiler.InferenceState(res…
  ╎    ╎    ╎    ╎    ╎    ╎   1  @Compiler/…jl:283  find_ssavalue_uses(body::V…
 1╎    ╎    ╎    ╎    ╎    ╎    1  @Compiler/…l:291  find_ssavalue_uses!(uses::…
  ╎    ╎    ╎    ╎    ╎   1  @Compiler/…n.jl:259  (::Compiler.var"#infercalls#a…
  ╎    ╎    ╎    ╎    ╎    1  @Compiler/….jl:189  (::Compiler.var"#handle1#abst…
  ╎    ╎    ╎    ╎    ╎     1  @Compiler/….jl:919  widenwrappedconditional(typ:…
  ╎    ╎    ╎    ╎    ╎    ╎ 1  @Compiler/….jl:945  abstract_call_method_with_c…
  ╎    ╎    ╎    ╎    ╎    ╎  1  @Compiler/…jl:1368  semi_concrete_eval_call(in…
  ╎    ╎    ╎    ╎    ╎    ╎   1  @Compiler/…jl:319  ir_abstract_constant_propa…
  ╎    ╎    ╎    ╎    ╎    ╎    1  @Compiler/…l:333  ir_abstract_constant_propa…
  ╎    ╎    ╎    ╎    ╎    ╎     1  @Compiler/…l:287  scan!(callback::Compiler.…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎ 1  @Compiler/…l:348  (::Compiler.var"#234#235…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎  1  @Compiler/…l:605  getindex(node::Compiler…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎   1  @Compiler/…l:538  <=(x::Int64, y::Int64)
 1╎    ╎    ╎    ╎    ╎    ╎    ╎    1  @Compiler/…l:582  _useref_getindex_opN(…
  ╎    ╎    ╎    ╎    ╎   1  @Compiler/…n.jl:333  (::Compiler.var"#infercalls#a…
  ╎    ╎    ╎    ╎    ╎    1  @Compiler/….jl:317  (::Compiler.var"#infercalls2#…
  ╎    ╎    ╎    ╎    ╎     1  @Base/…nals.jl:1799  multiple_methods(m::Compile…
  ╎    ╎    ╎    ╎    ╎    ╎ 1  @Base/…als.jl:1800  iterate(A::Vector{Compiler.…
  ╎    ╎    ╎    ╎    ╎    ╎  1  @Base/…als.jl:1783  iterate(A::Vector{Compiler…
 1╎    ╎    ╎    ╎    ╎    ╎   1  @Base/…ls.jl:1794  _iterate_abstractarray(A::…
  ╎    ╎    ╎  33 @Compiler/…ation.jl:4875  typeinf(interp::Compiler.NativeInte…
  ╎    ╎    ╎   6  @Compiler/…infer.jl:278  finish_nocycle(interp::Compiler.Nat…
  ╎    ╎    ╎    6  @Compiler/…mize.jl:1021  optimize(interp::Compiler.NativeIn…
  ╎    ╎    ╎     6  @Compiler/…mize.jl:1048  run_passes_ipo_safe
  ╎    ╎    ╎    ╎ 6  @Compiler/…ize.jl:1035  run_passes_ipo_safe(ci::Core.Code…
  ╎    ╎    ╎    ╎  2  @Compiler/…ing.jl:76  ssa_inlining_pass!
  ╎    ╎    ╎    ╎   2  @Compiler/…ng.jl:1613  assemble_inline_todo!(ir::Compil…
  ╎    ╎    ╎    ╎    2  @Compiler/…ng.jl:1366  inline_const_if_inlineable!(ins…
  ╎    ╎    ╎    ╎     2  @Compiler/…ng.jl:1334  compute_inlining_cases(info::C…
  ╎    ╎    ╎    ╎    ╎ 2  @Compiler/…g.jl:1270  info_effects(call_result::Unio…
  ╎    ╎    ╎    ╎    ╎  2  @Compiler/…g.jl:1281  handle_any_call_result!(cases…
  ╎    ╎    ╎    ╎    ╎   2  @Compiler/….jl:1374  handle_concrete_result!(cases…
  ╎    ╎    ╎    ╎    ╎    2  @Compiler/….jl:1385  handle_call_result!(cases::V…
  ╎    ╎    ╎    ╎    ╎     2  @Compiler/….jl:870  any(f::Compiler.var"#210#211…
  ╎    ╎    ╎    ╎    ╎    ╎ 2  @Compiler/….jl:904  analyze_method!(call_result…
  ╎    ╎    ╎    ╎    ╎    ╎  2  @Compiler/…jl:851  resolve_todo(mi::Core.Metho…
  ╎    ╎    ╎    ╎    ╎    ╎   1  @Compiler/…jl:918  get_local_code(inf_result:…
  ╎    ╎    ╎    ╎    ╎    ╎    1  @Compiler/…jl:14  inflate_ir!(ci::Core.CodeI…
  ╎    ╎    ╎    ╎    ╎    ╎     1  @Compiler/…jl:5  matching_cache_argtypes(::…
 1╎    ╎    ╎    ╎    ╎    ╎    ╎ 1  @Compiler/…l:163  most_general_argtypes(me…
  ╎    ╎    ╎    ╎    ╎    ╎   1  @Compiler/…jl:934  retrieve_ir_for_inlining(m…
  ╎    ╎    ╎    ╎    ╎    ╎    1  @Compiler/…l:197  simplify_ir!
  ╎    ╎    ╎    ╎    ╎    ╎     1  @Compiler/…l:2734  cfg_simplify!(ir::Compil…
  ╎    ╎    ╎    ╎    ╎    ╎    ╎ 1  @Compiler/…l:1574  process_node!(compact::…
 1╎    ╎    ╎    ╎    ╎    ╎    ╎  1  @Compiler/…l:1379  renumber_ssa2!(stmt::A…
  ╎    ╎    ╎    ╎  1  @Compiler/…ing.jl:79  ssa_inlining_pass!
  ╎    ╎    ╎    ╎   1  @Compiler/…ing.jl:637  batch_inline!(ir::Compiler.IRCod…
  ╎    ╎    ╎    ╎    1  @Compiler/…ir.jl:803  Compiler.IncrementalCompact(code…
  ╎    ╎    ╎    ╎     1  @Base/array.jl:576  collect(r::Base.OneTo{Int64})
  ╎    ╎    ╎    ╎    ╎ 1  @Base/array.jl:578  Array(A::Base.OneTo{Int64})
  ╎    ╎    ╎    ╎    ╎  1  @Base/array.jl:364  Vector{Int64}(r::Base.OneTo{Int…
  ╎    ╎    ╎    ╎    ╎   1  @Base/array.jl:369  setindex!(A::Vector{Int64}, x:…
  ╎    ╎    ╎    ╎    ╎    1  @Base/range.jl:928  _setindex!(A::Vector{Int64}, …
  ╎    ╎    ╎    ╎    ╎     1  @Base/…tion.jl:637  checkbounds(A::Vector{Int64}…
 1╎    ╎    ╎    ╎  1  @Compiler/…ses.jl:1478  sroa_pass!(ir::Compiler.IRCode, …
  ╎    ╎    ╎    ╎  1  @Compiler/…ses.jl:1530  sroa_pass!(ir::Compiler.IRCode, …
  ╎    ╎    ╎    ╎   1  @Compiler/…ses.jl:412  lift_leaves(compact::Compiler.In…
 1╎    ╎    ╎    ╎    1  @Base/iddict.jl:31  IdDict{Any, Union{Nothing, Compile…
  ╎    ╎    ╎    ╎  1  @Compiler/…ses.jl:1540  sroa_pass!(ir::Compiler.IRCode, …
  ╎    ╎    ╎    ╎   1  @Compiler/…ses.jl:787  perform_lifting!
  ╎    ╎    ╎    ╎    1  @Compiler/…es.jl:824  perform_lifting!(compact::Compil…
  ╎    ╎    ╎    ╎     1  @Compiler/…te.jl:191  setindex!(d::IdDict{Union{Compi…
  ╎    ╎    ╎    ╎    ╎ 1  @Compiler/…ir.jl:476  max(x::UInt64, y::Int64)
  ╎    ╎    ╎    ╎    ╎  1  @Compiler/…r.jl:477  construct_domtree
  ╎    ╎    ╎    ╎    ╎   1  @Compiler/…e.jl:242  construct_domtree(blocks::Vec…
  ╎    ╎    ╎    ╎    ╎    1  @Compiler/….jl:260  Compiler.GenericDomTree{false…
  ╎    ╎    ╎    ╎    ╎     1  @Compiler/….jl:266  compute_domtree_nodes!(domtr…
  ╎    ╎    ╎    ╎    ╎    ╎ 1  @Base/…rray.jl:924  copy!(dst::Vector{Compiler.…
  ╎    ╎    ╎    ╎    ╎    ╎  1  @Base/…ray.jl:1568  resize!(a::Vector{Compiler…
  ╎    ╎    ╎    ╎    ╎    ╎   1  @Base/…ay.jl:1233  _growend!(a::Vector{Compil…
  ╎    ╎    ╎    ╎    ╎    ╎    1  @Base/…ay.jl:1209  _growend_internal!(a::Vec…
  ╎    ╎    ╎    ╎    ╎    ╎     1  @Base/…ay.jl:1129  array_new_memory
 1╎    ╎    ╎    ╎    ╎    ╎    ╎ 1  @Base/…ot.jl:654  GenericMemory
  ╎    ╎    ╎   27 @Compiler/…infer.jl:285  finish_nocycle(interp::Compiler.Nat…
  ╎    ╎    ╎    1  @Compiler/…nfer.jl:153  finish!(interp::Compiler.NativeInte…
  ╎    ╎    ╎     1  @Compiler/…mize.jl:295  is_result_constabi_eligible(result…
  ╎    ╎    ╎    ╎ 1  @Compiler/…mize.jl:304  is_foldable_nothrow(effects::Comp…
 1╎    ╎    ╎    ╎  1  @Compiler/…ize.jl:312  widen_all_consts!(src::Core.CodeI…
  ╎    ╎    ╎    26 @Compiler/…nfer.jl:165  finish!(interp::Compiler.NativeInte…
26╎    ╎    ╎     26 @Compiler/…nfer.jl:507  maybe_compress_codeinfo

┌ Warning: There were 1 divergent transitions. Consider reparameterising your model or using a smaller step size. For adaptive samplers such as NUTS and HMCDA, consider increasing `target_accept`.
└ @ Turing.Inference ~/.julia/packages/Turing/4hMHm/src/mcmc/hmc.jl:483

[97] signal 15: Terminated
in expression starting at /home/pkgeval/.julia/packages/Turing/4hMHm/test/mcmc/gibbs.jl:351
jl_to_typeof at /source/src/julia.h:1040:12 [inlined]
ijl_types_equal at /source/src/subtype.c:2414:9
jl_specializations_get_linfo_ at /source/src/gf.c:236:17
#specialize_method#6 at ./runtime_internals.jl:1796:40 [inlined]
specialize_method at ./runtime_internals.jl:1783:4 [inlined]
typeinf_edge at ./../usr/share/julia/Compiler/src/typeinfer.jl:1147:14
abstract_call_method at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:769:296
infercalls at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:178:51
abstract_call_gf_by_type at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:340:173
abstract_call_known at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:2999:1211
abstract_call at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3107:51
abstract_call at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3100:4 [inlined]
abstract_call at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3260:21
abstract_eval_call at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3278:28 [inlined]
abstract_eval_statement_expr at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3642:11
abstract_eval_basic_statement at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:4049:142 [inlined]
abstract_eval_basic_statement at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:4006:4 [inlined]
typeinf_local at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:4590:703
jfptr_typeinf_local_1.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
typeinf at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:4868:151
typeinf_ext at ./../usr/share/julia/Compiler/src/typeinfer.jl:1537:141
typeinf_ext_toplevel at ./../usr/share/julia/Compiler/src/typeinfer.jl:1723:2 [inlined]
typeinf_ext_toplevel at ./../usr/share/julia/Compiler/src/typeinfer.jl:1732:19
jfptr_typeinf_ext_toplevel_2.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
jl_apply at /source/src/julia.h:2327:12 [inlined]
jl_type_infer at /source/src/gf.c:463:35
jl_compile_method_internal at /source/src/gf.c:3638:24
_jl_invoke at /source/src/gf.c:4103:16 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
jl_apply at /source/src/julia.h:2327:12 [inlined]
do_call at /source/src/interpreter.c:123:26
eval_value at /source/src/interpreter.c:243:16
eval_stmt_value at /source/src/interpreter.c:194:23 [inlined]
eval_body at /source/src/interpreter.c:693:13
eval_body at /source/src/interpreter.c:550:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:550:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:550:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:550:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
jl_interpret_toplevel_thunk at /source/src/interpreter.c:884:21
ijl_eval_thunk at /source/src/toplevel.c:768:18
jl_toplevel_eval_flex at /source/src/toplevel.c:712:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15
jl_eval_module_expr at /source/src/toplevel.c:263:5 [inlined]
jl_toplevel_eval_flex at /source/src/toplevel.c:665:27
jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15
jl_toplevel_eval_flex at /source/src/toplevel.c:684:27
ijl_toplevel_eval at /source/src/toplevel.c:782:12
ijl_toplevel_eval_in at /source/src/toplevel.c:827:13
eval at ./boot.jl:517:3
include_string at ./loading.jl:3113:145
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
_include at ./loading.jl:3173:45
include at ./Base.jl:327:3
IncludeInto at ./Base.jl:328:4
jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
jl_apply at /source/src/julia.h:2327:12 [inlined]
do_call at /source/src/interpreter.c:123:26
eval_value at /source/src/interpreter.c:243:16
eval_stmt_value at /source/src/interpreter.c:194:23 [inlined]
eval_body at /source/src/interpreter.c:693:13
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:550:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:550:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
eval_body at /source/src/interpreter.c:558:21
jl_interpret_toplevel_thunk at /source/src/interpreter.c:884:21
ijl_eval_thunk at /source/src/toplevel.c:768:18
jl_toplevel_eval_flex at /source/src/toplevel.c:712:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15
jl_toplevel_eval_flex at /source/src/toplevel.c:684:27
ijl_toplevel_eval at /source/src/toplevel.c:782:12
ijl_toplevel_eval_in at /source/src/toplevel.c:827:13
eval at ./boot.jl:517:3
include_string at ./loading.jl:3113:145
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
_include at ./loading.jl:3173:45
include at ./Base.jl:327:3
IncludeInto at ./Base.jl:328:4
jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
jl_apply at /source/src/julia.h:2327:12 [inlined]
do_call at /source/src/interpreter.c:123:26
eval_value at /source/src/interpreter.c:243:16
eval_stmt_value at /source/src/interpreter.c:194:23 [inlined]
eval_body at /source/src/interpreter.c:693:13
jl_interpret_toplevel_thunk at /source/src/interpreter.c:884:21
ijl_eval_thunk at /source/src/toplevel.c:768:18
jl_toplevel_eval_flex at /source/src/toplevel.c:712:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15
jl_toplevel_eval_flex at /source/src/toplevel.c:684:27
ijl_toplevel_eval at /source/src/toplevel.c:782:12
ijl_toplevel_eval_in at /source/src/toplevel.c:827:13
eval at ./boot.jl:517:3
exec_options at ./client.jl:318:410
_start at ./client.jl:593:36
jfptr__start_0.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4111:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4337:12
jl_apply at /source/src/julia.h:2327:12 [inlined]
true_main at /source/src/jlapi.c:971:29
jl_repl_entrypoint at /source/src/jlapi.c:1138:15
main at /source/cli/loader_exe.c:58:15
unknown function (ip: 0x7e98176ac249) at /lib/x86_64-linux-gnu/libc.so.6
__libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S
unknown function (ip: (nil)) at (unknown file)
Allocations: 3582145089 (Pool: 3582138278; Big: 6811); GC: 562

PkgEval terminated after 2729.85s: test duration exceeded the time limit