Package evaluation to test Turing on Julia 1.14.0-DEV.2043 (b936235316*) started at 2026-04-17T04:41:08.417 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 14.77s ################################################################################ # Installation # Installing Turing... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [fce5fe82] + Turing v0.43.6 Updating `~/.julia/environments/v1.14/Manifest.toml` [47edcb42] + ADTypes v1.21.0 [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 [13072b0f] + AxisAlgorithms v1.1.0 [39de3d68] + AxisArrays v0.4.8 [198e06fe] + BangBang v0.4.9 [76274a88] + Bijectors v0.15.20 [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 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.19.4 [e2d170a0] + DataValueInterfaces v1.0.0 [b429d917] + DensityInterface v0.4.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [a0c0ee7d] + DifferentiationInterface v0.7.16 [31c24e10] + Distributions v0.25.124 [ffbed154] + DocStringExtensions v0.9.5 [366bfd00] + DynamicPPL v0.40.23 [cad2338a] + EllipticalSliceSampling v2.0.0 [4e289a0a] + EnumX v1.0.7 [f151be2c] + EnzymeCore v0.8.19 [e2ba6199] + ExprTools v0.1.10 [55351af7] + ExproniconLite v0.10.14 [b86e33f2] + FFTA v0.3.1 [9aa1b823] + FastClosures v0.3.2 [1a297f60] + FillArrays v1.16.0 [6a86dc24] + FiniteDiff v2.30.0 [f6369f11] + ForwardDiff v1.3.3 [069b7b12] + FunctionWrappers v1.1.3 [77dc65aa] + FunctionWrappersWrappers v1.4.0 [d9f16b24] + Functors v0.5.2 [46192b85] + GPUArraysCore v0.2.0 [34004b35] + HypergeometricFunctions v0.3.28 [22cec73e] + InitialValues v0.3.1 [18e54dd8] + IntegerMathUtils v0.1.3 [a98d9a8b] + Interpolations v0.16.2 [8197267c] + IntervalSets v0.7.14 [3587e190] + InverseFunctions v0.1.17 [92d709cd] + IrrationalConstants v0.2.6 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.1 [682c06a0] + JSON v1.5.0 [ae98c720] + Jieko v0.2.1 [5ab0869b] + KernelDensity v0.6.11 [b964fa9f] + LaTeXStrings v1.4.0 [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 [c7f686f2] + MCMCChains v7.7.0 [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 [2e0e35c7] + Moshi v0.3.7 [46d2c3a1] + MuladdMacro v0.2.4 [d41bc354] + NLSolversBase v8.0.0 [77ba4419] + NaNMath v1.1.3 [c020b1a1] + NaturalSort v1.0.0 [6fe1bfb0] + OffsetArrays v1.17.0 [429524aa] + Optim v2.0.1 [3bd65402] + Optimisers v0.4.7 [7f7a1694] + Optimization v5.5.0 [bca83a33] + OptimizationBase v5.1.0 [36348300] + OptimizationOptimJL v0.4.11 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.37 [69de0a69] + Parsers v2.8.3 [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 [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 [b3c3ace0] + RangeArrays v0.3.2 [c84ed2f1] + Ratios v0.4.5 [3cdcf5f2] + RecipesBase v1.3.4 ⌅ [731186ca] + RecursiveArrayTools v3.54.0 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.9.0 ⌅ [f2b01f46] + Roots v2.3.0 [7e49a35a] + RuntimeGeneratedFunctions v0.5.18 [26aad666] + SSMProblems v0.6.1 ⌅ [0bca4576] + SciMLBase v2.155.0 [a6db7da4] + SciMLLogging v1.9.1 [c0aeaf25] + SciMLOperators v1.16.0 [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 [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 [892a3eda] + StringManipulation v0.4.4 [ec057cc2] + StructUtils v2.7.2 [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 v0.43.6 [efce3f68] + WoodburyMatrices v1.1.0 [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 [1a1011a3] + SharedArrays 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 v1.3.0+1 [4536629a] + OpenBLAS_jll v0.3.30+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 6.73s ################################################################################ # 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/jHjuM/src/interpreter/abstract_interpretation.jl:89  [3] include(mapexpr::Function, mod::Module, _path::String)  @ Base ./Base.jl:327  [4] top-level scope  @ ~/.julia/packages/Mooncake/jHjuM/src/Mooncake.jl:126  [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:3265  [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:3107  [10] include_string  @ ./loading.jl:3117 [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/jHjuM/src/interpreter/abstract_interpretation.jl:89 in expression starting at /home/pkgeval/.julia/packages/Mooncake/jHjuM/src/Mooncake.jl:1 in expression starting at stdin:5 ✗ Mooncake 15.7 s ✓ AdvancedVI → AdvancedVIReverseDiffExt 18.4 s ✓ DynamicPPL → DynamicPPLReverseDiffExt 16.8 s ✓ Turing → TuringDynamicHMCExt 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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./module.jl:36 [inlined]  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)  @ Base ./module.jl:60  [10] _eval_using  @ ./module.jl:137 [inlined]  [11] _eval_using(to::Module, path::Expr)  @ Base ./module.jl:137  [12] top-level scope  @ ~/.julia/packages/Mooncake/jHjuM/ext/MooncakeDistributionsExt.jl:3  [13] include(mod::Module, _path::String)  @ Base ./Base.jl:326  [14] 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:3265  [15] top-level scope  @ stdin:5  [16] eval(m::Module, e::Any)  @ Core ./boot.jl:517  [17] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)  @ Base ./loading.jl:3107  [18] include_string  @ ./loading.jl:3117 [inlined]  [19] exec_options(opts::Base.JLOptions)  @ Base ./client.jl:350  [20] _start()  @ Base ./client.jl:593 in expression starting at /home/pkgeval/.julia/packages/Mooncake/jHjuM/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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./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/jHjuM/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:3265  [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:3107  [17] include_string  @ ./loading.jl:3117 [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/jHjuM/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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./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/jHjuM/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:3265  [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:3107  [17] include_string  @ ./loading.jl:3117 [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/jHjuM/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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./module.jl:36 [inlined]  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)  @ Base ./module.jl:60  [10] _eval_using  @ ./module.jl:137 [inlined]  [11] _eval_using(to::Module, path::Expr)  @ Base ./module.jl:137  [12] top-level scope  @ ~/.julia/packages/Mooncake/jHjuM/ext/MooncakeSpecialFunctionsExt.jl:3  [13] include(mod::Module, _path::String)  @ Base ./Base.jl:326  [14] 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:3265  [15] top-level scope  @ stdin:5  [16] eval(m::Module, e::Any)  @ Core ./boot.jl:517  [17] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)  @ Base ./loading.jl:3107  [18] include_string  @ ./loading.jl:3117 [inlined]  [19] exec_options(opts::Base.JLOptions)  @ Base ./client.jl:350  [20] _start()  @ Base ./client.jl:593 in expression starting at /home/pkgeval/.julia/packages/Mooncake/jHjuM/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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./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/afUhd/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:3265  [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:3107  [17] include_string  @ ./loading.jl:3117 [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/afUhd/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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./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/CStqc/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:3265  [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:3107  [16] include_string  @ ./loading.jl:3117 [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/CStqc/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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./module.jl:36 [inlined]  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)  @ Base ./module.jl:60  [10] _eval_using  @ ./module.jl:137 [inlined]  [11] _eval_using(to::Module, path::Expr)  @ Base ./module.jl:137  [12] top-level scope  @ ~/.julia/packages/SciMLBase/Ag5zT/ext/SciMLBaseMooncakeExt.jl:3  [13] include(mod::Module, _path::String)  @ Base ./Base.jl:326  [14] 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:3265  [15] top-level scope  @ stdin:5  [16] eval(m::Module, e::Any)  @ Core ./boot.jl:517  [17] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)  @ Base ./loading.jl:3107  [18] include_string  @ ./loading.jl:3117 [inlined]  [19] exec_options(opts::Base.JLOptions)  @ Base ./client.jl:350  [20] _start()  @ Base ./client.jl:593 in expression starting at /home/pkgeval/.julia/packages/SciMLBase/Ag5zT/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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./module.jl:36 [inlined]  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)  @ Base ./module.jl:60  [10] _eval_using  @ ./module.jl:137 [inlined]  [11] _eval_using(to::Module, path::Expr)  @ Base ./module.jl:137  [12] top-level scope  @ ~/.julia/packages/OptimizationBase/y7Tug/ext/OptimizationMooncakeExt.jl:3  [13] include(mod::Module, _path::String)  @ Base ./Base.jl:326  [14] 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:3265  [15] top-level scope  @ stdin:5  [16] eval(m::Module, e::Any)  @ Core ./boot.jl:517  [17] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)  @ Base ./loading.jl:3107  [18] include_string  @ ./loading.jl:3117 [inlined]  [19] exec_options(opts::Base.JLOptions)  @ Base ./client.jl:350  [20] _start()  @ Base ./client.jl:593 in expression starting at /home/pkgeval/.julia/packages/OptimizationBase/y7Tug/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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./module.jl:36 [inlined]  [9] eval_import_path_all(at::Module, path::Expr, keyword::String)  @ Base ./module.jl:60  [10] _eval_using  @ ./module.jl:137 [inlined]  [11] _eval_using(to::Module, path::Expr)  @ Base ./module.jl:137  [12] top-level scope  @ ~/.julia/packages/AdvancedVI/2WrpF/ext/AdvancedVIMooncakeExt.jl:5  [13] include(mod::Module, _path::String)  @ Base ./Base.jl:326  [14] 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:3265  [15] top-level scope  @ stdin:5  [16] eval(m::Module, e::Any)  @ Core ./boot.jl:517  [17] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)  @ Base ./loading.jl:3107  [18] include_string  @ ./loading.jl:3117 [inlined]  [19] exec_options(opts::Base.JLOptions)  @ Base ./client.jl:350  [20] _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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./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/Bzm8Z/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:3265  [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:3107  [17] include_string  @ ./loading.jl:3117 [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/Bzm8Z/ext/BijectorsMooncakeExt.jl:1 in expression starting at stdin:5 ✗ Bijectors → BijectorsMooncakeExt 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:2812  [3] _require_prelocked(uuidkey::Base.PkgId, env::String)  @ Base ./loading.jl:2666  [4] macro expansion  @ ./loading.jl:2593 [inlined]  [5] macro expansion  @ ./lock.jl:376 [inlined]  [6] __require(into::Module, mod::Symbol)  @ Base ./loading.jl:2557  [7] require  @ ./loading.jl:2533 [inlined]  [8] eval_import_path  @ ./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/Xldpn/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:3265  [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:3107  [17] include_string  @ ./loading.jl:3117 [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/Xldpn/ext/DynamicPPLMooncakeExt.jl:1 in expression starting at stdin:5 ✗ DynamicPPL → DynamicPPLMooncakeExt 3 dependencies successfully precompiled in 121 seconds. 349 already precompiled. Precompilation completed after 144.81s ################################################################################ # Testing # Testing Turing Status `/tmp/jl_IYJJkE/Project.toml` [47edcb42] ADTypes v1.21.0 [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 v0.15.20 [aaaa29a8] Clustering v0.15.8 [861a8166] Combinatorics v1.1.0 [a0c0ee7d] DifferentiationInterface v0.7.16 [31c24e10] Distributions v0.25.124 [bbc10e6e] DynamicHMC v3.6.0 [366bfd00] DynamicPPL v0.40.23 [26cc04aa] FiniteDifferences v0.12.33 [f6369f11] ForwardDiff v1.3.3 ⌃ [09f84164] HypothesisTests v0.11.6 [6f1fad26] Libtask v0.9.17 [6fdf6af0] LogDensityProblems v2.2.0 [996a588d] LogDensityProblemsAD v1.13.1 [c7f686f2] MCMCChains v7.7.0 ⌃ [da2b9cff] Mooncake v0.5.24 [7f7a1694] Optimization v5.5.0 [3e6eede4] OptimizationBBO v0.4.6 [4e6fcdb7] OptimizationNLopt v0.3.10 [36348300] OptimizationOptimJL v0.4.11 [90014a1f] PDMats v0.11.37 [37e2e3b7] ReverseDiff v1.16.2 [276daf66] SpecialFunctions v2.7.2 [860ef19b] StableRNGs v1.0.4 [2913bbd2] StatsBase v0.34.10 [4c63d2b9] StatsFuns v1.5.2 [a759f4b9] TimerOutputs v0.5.29 [fce5fe82] Turing v0.43.6 [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_IYJJkE/Manifest.toml` [47edcb42] ADTypes v1.21.0 [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 v0.15.20 [a134a8b2] BlackBoxOptim v0.6.4 [fa961155] CEnum v0.5.0 [082447d4] ChainRules v1.73.0 [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 [b429d917] DensityInterface v0.4.0 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [a0c0ee7d] DifferentiationInterface v0.7.16 [8d63f2c5] DispatchDoctor v0.4.28 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.124 [ffbed154] DocStringExtensions v0.9.5 [bbc10e6e] DynamicHMC v3.6.0 [366bfd00] DynamicPPL v0.40.23 [cad2338a] EllipticalSliceSampling v2.0.0 [4e289a0a] EnumX v1.0.7 [f151be2c] EnzymeCore v0.8.19 [e2ba6199] ExprTools v0.1.10 [55351af7] ExproniconLite v0.10.14 [b86e33f2] FFTA v0.3.1 [9aa1b823] FastClosures v0.3.2 [1a297f60] FillArrays v1.16.0 [6a86dc24] FiniteDiff v2.30.0 [26cc04aa] FiniteDifferences v0.12.33 [f6369f11] ForwardDiff v1.3.3 [069b7b12] FunctionWrappers v1.1.3 [77dc65aa] FunctionWrappersWrappers v1.4.0 [d9f16b24] Functors v0.5.2 [46192b85] GPUArraysCore v0.2.0 [86223c79] Graphs v1.14.0 [34004b35] HypergeometricFunctions v0.3.28 ⌃ [09f84164] HypothesisTests v0.11.6 [d25df0c9] Inflate v0.1.5 [22cec73e] InitialValues v0.3.1 [18e54dd8] IntegerMathUtils v0.1.3 [a98d9a8b] Interpolations v0.16.2 [8197267c] IntervalSets v0.7.14 [3587e190] InverseFunctions v0.1.17 [92d709cd] IrrationalConstants v0.2.6 [c8e1da08] IterTools v1.10.0 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.1 [682c06a0] JSON v1.5.0 [ae98c720] Jieko v0.2.1 [5ab0869b] KernelDensity v0.6.11 [b964fa9f] LaTeXStrings v1.4.0 [1fad7336] LazyStack v0.1.3 [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 [c7f686f2] MCMCChains v7.7.0 [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 ⌃ [da2b9cff] Mooncake v0.5.24 [2e0e35c7] Moshi v0.3.7 [46d2c3a1] MuladdMacro v0.2.4 [d41bc354] NLSolversBase v8.0.0 [76087f3c] NLopt v1.2.1 [77ba4419] NaNMath v1.1.3 [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 [7f7a1694] Optimization v5.5.0 [3e6eede4] OptimizationBBO v0.4.6 [bca83a33] OptimizationBase v5.1.0 [4e6fcdb7] OptimizationNLopt v0.3.10 [36348300] OptimizationOptimJL v0.4.11 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.37 [65ce6f38] PackageExtensionCompat v1.0.2 [69de0a69] Parsers v2.8.3 [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 [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 [b3c3ace0] RangeArrays v0.3.2 [c84ed2f1] Ratios v0.4.5 [c1ae055f] RealDot v0.1.0 [3cdcf5f2] RecipesBase v1.3.4 ⌅ [731186ca] RecursiveArrayTools v3.54.0 [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 v2.3.0 [7e49a35a] RuntimeGeneratedFunctions v0.5.18 [26aad666] SSMProblems v0.6.1 ⌅ [0bca4576] SciMLBase v2.155.0 [a6db7da4] SciMLLogging v1.9.1 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[6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [f489334b] StyledStrings v1.13.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.19.0+0 [e37daf67] LibGit2_jll v1.9.2+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2026.3.19 [4536629a] OpenBLAS_jll v0.3.30+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.6+0 [efcefdf7] PCRE2_jll v10.47.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.2+0 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.68.1+0 [3f19e933] p7zip_jll v17.8.0+0 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints 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/jHjuM/src/interpreter/abstract_interpretation.jl:89  [3] include(mapexpr::Function, mod::Module, _path::String)  @ Base ./Base.jl:327  [4] top-level scope  @ ~/.julia/packages/Mooncake/jHjuM/src/Mooncake.jl:126  [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:3265  [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:3107  [10] include_string  @ ./loading.jl:3117 [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/jHjuM/src/interpreter/abstract_interpretation.jl:89 in expression starting at /home/pkgeval/.julia/packages/Mooncake/jHjuM/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/lLiHA/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_AqiokP" (ProcessExited(1)). in expression starting at /home/pkgeval/.julia/packages/Turing/lLiHA/test/ad.jl:1 constructor: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.ContainerTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/test/essential/container.jl:25 [inlined] [16] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [17] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/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/lLiHA/test/essential/container.jl:38 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.ContainerTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/essential/container.jl:39 [inlined] [14] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [15] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/essential/container.jl:51 [inlined] [16] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [17] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/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 = 2.4000000000000004 ┌ Info: Found initial step size └ ϵ = 3.2 ┌ Info: Found initial step size └ ϵ = 3.2 ┌ Info: Found initial step size └ ϵ = 1.625 ┌ 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 = 6.4 ┌ 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/lLiHA/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/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x, :y), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.TypedIdentity}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x, :y), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.TypedIdentity}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x, :y), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.TypedIdentity}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x, :y), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.TypedIdentity}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x, :y), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.TypedIdentity}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.CallbacksTests.test_normals), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x, :y), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.TypedIdentity}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x, :y), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.TypedIdentity}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior}, ::typeof(AbstractMCMC.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}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [18] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/callbacks.jl:11 [19] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [20] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/callbacks.jl:25 [inlined] [21] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [22] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/callbacks.jl:25 [inlined] [23] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [24] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [25] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [26] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:46 [inlined] [27] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [28] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [29] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [30] top-level scope @ none:6 [31] eval(m::Module, e::Any) @ Core ./boot.jl:517 [32] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [33] _start() @ Base ./client.jl:593 ┌ Info: Found initial step size └ ϵ = 1.6 ┌ 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/Xldpn/src/compiler.jl:357 models: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:27 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#51#52"{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"#51#52"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#normal#normal##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :b), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; nparticles::Int64, discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:173 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:159 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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 [28] kwcall(::@NamedTuple{chain_type::UnionAll, initial_params::DynamicPPL.InitFromPrior, progress::Bool, nparticles::Int64}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:146 [30] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:125 [inlined] [31] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [32] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [33] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:13 [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:28 [inlined] [36] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [37] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:36 [inlined] [38] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [39] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [40] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [41] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:46 [inlined] [42] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [43] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [44] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [45] top-level scope @ none:6 [46] eval(m::Module, e::Any) @ Core ./boot.jl:517 [47] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [48] _start() @ Base ./client.jl:593 chain log-density metadata: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#51#52"{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"#51#52"{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; nparticles::Int64, discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:173 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:159 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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 [28] kwcall(::@NamedTuple{chain_type::UnionAll, initial_params::DynamicPPL.InitFromPrior, progress::Bool, nparticles::Int64}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:146 [30] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:125 [inlined] [31] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [32] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [33] test_chain_logp_metadata(spl::Turing.Inference.SMC{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ Main.SamplerTestUtils ~/.julia/packages/Turing/lLiHA/test/test_utils/sampler.jl:22 [34] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:13 [35] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [36] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:54 [inlined] [37] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [38] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:54 [inlined] [39] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [40] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/runtests.jl:46 [inlined] [43] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [44] macro expansion @ ~/.julia/packages/Turing/lLiHA/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 logevidence: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#51#52"{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"#51#52"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :x, :b, :c), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Bool}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; nparticles::Int64, discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:173 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:159 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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 [28] kwcall(::@NamedTuple{chain_type::UnionAll, initial_params::DynamicPPL.InitFromPrior, progress::Bool, nparticles::Int64}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:146 [30] 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/lLiHA/src/mcmc/particle_mcmc.jl:125 [31] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:13 [32] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [33] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:58 [inlined] [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:68 [inlined] [36] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [37] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/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 discard_initial and thinning are ignored: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#51#52"{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"#51#52"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :b), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; nparticles::Int64, discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:173 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:159 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::TestLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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 [28] kwcall(::@NamedTuple{chain_type::UnionAll, initial_params::DynamicPPL.InitFromPrior, progress::Bool, nparticles::Int64}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:146 [30] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:125 [inlined] [31] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [32] kwcall(::@NamedTuple{discard_initial::Int64}, ::typeof(StatsBase.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) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:76 [33] (::Main.ParticleMCMCTests.var"#6#7")() @ Main.ParticleMCMCTests ./none:-1 [34] with_logstate(f::Main.ParticleMCMCTests.var"#6#7", logstate::Base.CoreLogging.LogState) @ Base.CoreLogging ./logging/logging.jl:542 [35] with_logger(f::Function, logger::TestLogger) @ Base.CoreLogging ./logging/logging.jl:653 [36] #collect_test_logs#63 @ /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:126 [inlined] [37] collect_test_logs @ /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:124 [inlined] [38] #match_logs#64 @ /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:307 [inlined] [39] match_logs(f::Function, patterns::Tuple{Symbol, Regex}) @ Test /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:306 [40] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:13 [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:94 [inlined] [43] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [44] macro expansion @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/src/mcmc/particle_mcmc.jl:144 discard_initial and thinning are ignored: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(), Tuple{}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#51#52"{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"#51#52"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#4#5", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :b), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; nparticles::Int64, discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:173 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:159 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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 [28] kwcall(::@NamedTuple{chain_type::UnionAll, initial_params::DynamicPPL.InitFromPrior, progress::Bool, nparticles::Int64}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:146 [30] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:125 [inlined] [31] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [32] kwcall(::@NamedTuple{discard_initial::Int64}, ::typeof(StatsBase.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) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:76 [33] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:13 [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:94 [inlined] [36] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [37] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:103 [inlined] [38] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [39] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [40] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [41] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:46 [inlined] [42] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [43] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [44] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [45] top-level scope @ none:6 [46] eval(m::Module, e::Any) @ Core ./boot.jl:517 [47] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [48] _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/Xldpn/src/compiler.jl:357 chain log-density metadata: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.SamplerTestUtils.var"#f#test_chain_logp_metadata##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [28] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [30] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [31] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [32] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [33] test_chain_logp_metadata(spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ Main.SamplerTestUtils ~/.julia/packages/Turing/lLiHA/test/test_utils/sampler.jl:22 [34] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:122 [35] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [36] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:141 [inlined] [37] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [38] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:141 [inlined] [39] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [40] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/runtests.jl:46 [inlined] [43] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [44] macro expansion @ ~/.julia/packages/Turing/lLiHA/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 logevidence: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :x, :b, :c), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Bool}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :x, :b, :c), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Bool}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :x, :b, :c), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Bool}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :x, :b, :c), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Bool}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :x, :b, :c), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Bool}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#test#test##1", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :x, :b, :c), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Bool}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a, :x, :b, :c), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Bool}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [28] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [30] 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/lLiHA/src/mcmc/abstractmcmc.jl:82 [31] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/mcmc/particle_mcmc.jl:145 [inlined] [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:155 [inlined] [36] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [37] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/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 reference particle: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [28] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [30] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [31] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [32] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [33] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:122 [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:166 [inlined] [36] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [37] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:166 [inlined] [38] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [39] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [40] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [41] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:46 [inlined] [42] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [43] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [44] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [45] top-level scope @ none:6 [46] eval(m::Module, e::Any) @ Core ./boot.jl:517 [47] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [48] _start() @ Base ./client.jl:593 addlogprob leads to reweighting: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#addlogprob_demo#addlogprob_demo##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [28] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [30] 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/lLiHA/src/mcmc/abstractmcmc.jl:82 [31] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/mcmc/particle_mcmc.jl:174 [inlined] [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:184 [inlined] [36] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [37] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/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 keyword argument handling: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{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}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{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}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [28] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [30] 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/lLiHA/src/mcmc/abstractmcmc.jl:82 [31] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/mcmc/particle_mcmc.jl:190 [inlined] [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:195 [inlined] [36] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [37] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/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 submodels without kwargs: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#nested#nested##0", (:y,), (), (), Tuple{Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(Turing.Inference.initialstep), 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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [16] 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}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, discard_sample::Bool}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [28] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [30] 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/lLiHA/src/mcmc/abstractmcmc.jl:82 [31] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/mcmc/particle_mcmc.jl:205 [inlined] [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:217 [inlined] [36] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [37] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/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 submodels with kwargs: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.ParticleMCMCTests.var"#outer_kwarg1#outer_kwarg1##0", (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(Turing.Inference.initialstep), 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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VarNamedTuples.VarNamedTuple{(:x,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [16] 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}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64, discard_sample::Bool}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [28] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [30] 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/lLiHA/src/mcmc/abstractmcmc.jl:82 [31] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/mcmc/particle_mcmc.jl:222 [inlined] [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/particle_mcmc.jl:231 [inlined] [36] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [37] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/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/lLiHA/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 [ Info: (symbol = :s, exact = 2.0416666666666665, evaluated = 2.0703723323764933) [ Info: (symbol = :m, exact = 1.1666666666666667, evaluated = 1.159950127444649) [ Info: Testing emcee with large number of iterations [ Info: (symbol = :s, exact = 2.0416666666666665, evaluated = 2.041349397195655) [ Info: (symbol = :m, exact = 1.1666666666666667, evaluated = 1.1787532039447761) [ Info: Starting ESS tests [ Info: Starting ESS inference tests [ Info: (symbol = :m, exact = 0.8, evaluated = 0.8172942592919593) [ Info: (symbol = "m[1]", exact = 0.0, evaluated = -0.02456171083886478) [ Info: (symbol = "m[2]", exact = 0.8, evaluated = 0.8075869528540663) gdemo with CSMC + ESS: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [19] 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}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌[20] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [inlined] ╰──── repeated 2 times [22] 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [23] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [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{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [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::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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [33] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [34] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [35] 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/lLiHA/src/mcmc/abstractmcmc.jl:82 [36] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/ess.jl:14 [37] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [38] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/ess.jl:48 [inlined] [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [40] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/ess.jl:62 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/ess.jl:63 [inlined] [43] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [44] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [45] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [46] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:46 [inlined] [47] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [48] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [49] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [50] top-level scope @ none:6 [51] eval(m::Module, e::Any) @ Core ./boot.jl:517 [52] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [53] _start() @ Base ./client.jl:593 MoGtest_default with CSMC + ESS: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [19] 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}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌[20] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [inlined] ╰──── repeated 2 times [22] 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [23] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [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{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [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::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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [33] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [34] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [35] 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/lLiHA/src/mcmc/abstractmcmc.jl:82 [36] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/ess.jl:14 [37] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [38] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/ess.jl:48 [inlined] [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [40] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/ess.jl:68 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/ess.jl:73 [inlined] [43] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [44] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [45] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [46] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:46 [inlined] [47] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [48] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [49] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [50] top-level scope @ none:6 [51] eval(m::Module, e::Any) @ Core ./boot.jl:517 [52] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [53] _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/lLiHA/test/mcmc/gibbs.jl:34 overwritten at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:208. WARNING: Method definition (::Type{GibbsTests.Wrapper{T<:Real}})(Any) in module GibbsTests at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:34 overwritten at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:208. Sampler call order: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:150 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#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [inlined] [8] AdvancedPS.LibtaskModel(::Turing.Inference.TracedModel{DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, 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#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, 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#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step(::Random.TaskLocalRNG, ::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, 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, discard_sample::Bool}) @ Main.GibbsTests ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:193 [19] step @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:185 [inlined] [20] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.step_warmup), rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Main.GibbsTests.AlgWrapper{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [21] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}, states::Tuple{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, 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,), Tuple{Float64}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌ [22] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}, ::typeof(Turing.Inference.gibbs_initialstep_recursive), rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::Function, 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}, states::Tuple{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, 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,), Tuple{Float64}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, 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), 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, :m), Tuple{Distributions.Normal{Float64}, Distributions.Poisson{Float64}}}}}}}}) │ @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 ├ [23] gibbs_initialstep_recursive(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, 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,), Tuple{Float64}}}, 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}}}}}}}, states::Tuple{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, 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,), Tuple{Float64}}}, 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}) │ @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:438 ╰───── repeated 2 times [26] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}, ::typeof(Turing.Inference.gibbs_initialstep_recursive), rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), Tuple{Int64, DynamicPPL.TypeWrap{Vector{Float64}}}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::Function, 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m, :xs, :ys, :q, :r), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:a,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.VarNamedTuples.PartialArray{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 1, Vector{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}, Vector{Bool}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [27] step_warmup(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [28] kwcall(::@NamedTuple{num_warmup::Int64, discard_sample::Bool, initial_params::DynamicPPL.InitFromPrior}, ::typeof(AbstractMCMC.step_warmup), rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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}}}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [29] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [30] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [31] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [32] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, Random.TaskLocalRNG, DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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 [33] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, Random.TaskLocalRNG, DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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 [34] 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 [35] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [36] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [37] mcmcsample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [38] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.mcmcsample), rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [39] sample(rng::Random.TaskLocalRNG, model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [40] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [41] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [42] sample(model::DynamicPPL.Model{Main.GibbsTests.var"#test_model#test_model##1", (:val, Symbol("##arg#1022")), (), (), 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [43] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:153 [44] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [45] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:254 [inlined] [46] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [47] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [48] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [49] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:55 [inlined] [50] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [51] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [52] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [53] top-level scope @ none:6 [54] eval(m::Module, e::Any) @ Core ./boot.jl:517 [55] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [56] _start() @ Base ./client.jl:593 [ Info: Starting Gibbs tests Gibbs constructors: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:401 Test threw exception Expression: sample(gdemo_default, s2, N) isa MCMCChains.Chains 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}, AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [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{sym, AbstractPPL.Iden} where sym}}, samplers::Tuple{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌[20] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [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{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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [23] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [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{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [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{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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [33] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [34] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [35] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [36] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [37] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [38] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [40] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:379 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:401 [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/lLiHA/test/mcmc/gibbs.jl:402 Test threw exception Expression: sample(gdemo_default, s3, N) isa MCMCChains.Chains 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [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.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, Turing.Inference.HMCDA{ADTypes.AutoForwardDiff{nothing, Nothing}, AdvancedHMC.UnitEuclideanMetric}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌[20] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [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.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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [23] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [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{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [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.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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [33] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [34] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [35] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [36] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [37] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [38] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [40] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:379 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:402 [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/lLiHA/test/mcmc/gibbs.jl:404 Test threw exception Expression: sample(gdemo_default, s5, N) isa MCMCChains.Chains 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [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{: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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{Turing.Inference.HMCState{DynamicPPL.VarInfo{DynamicPPL.LinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}, Turing.Inference.HMCState{DynamicPPL.VarInfo{DynamicPPL.LinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, 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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}}}}}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, 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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}}}}}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [21] 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{Turing.Inference.HMCState{DynamicPPL.VarInfo{DynamicPPL.LinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, 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@NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, 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@NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, 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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}}}}}, Turing.Inference.HMCState{DynamicPPL.VarInfo{DynamicPPL.LinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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}}, 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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}}}}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, 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@NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:438 [22] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}, ::typeof(Turing.Inference.gibbs_initialstep_recursive), rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::Function, 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, 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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}}}}}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [23] 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{Turing.Inference.HMCState{DynamicPPL.VarInfo{DynamicPPL.LinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:438 [24] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}, ::typeof(Turing.Inference.gibbs_initialstep_recursive), rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::Function, 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{Turing.Inference.HMCState{DynamicPPL.VarInfo{DynamicPPL.LinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [25] 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:438 ┌[26] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [inlined] ╰──── repeated 2 times [28] 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [29] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [inlined] [30] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [31] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [32] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [33] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [34] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [35] 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 [36] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [37] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [38] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [39] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [40] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [41] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [42] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [43] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [44] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [45] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [46] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:379 [inlined] [47] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [48] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:404 [inlined] [49] 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/lLiHA/test/mcmc/gibbs.jl:405 Test threw exception Expression: sample(gdemo_default, s6, N) isa MCMCChains.Chains 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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{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_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:m, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:m,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #step_warmup#10 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/repeat_sampler.jl:80 [inlined] [20] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/repeat_sampler.jl:74 [21] 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}}}}, vi::DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{Turing.Inference.HMCState{DynamicPPL.VarInfo{DynamicPPL.LinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 [22] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}, ::typeof(Turing.Inference.gibbs_initialstep_recursive), rng::Random.TaskLocalRNG, model::DynamicPPL.Model{typeof(Main.Models.gdemo_d), (), (), (), Tuple{}, Tuple{}, DynamicPPL.DefaultContext, false}, step_function::Function, varname_vecs::Tuple{Vector{AbstractPPL.VarName{:m, AbstractPPL.Iden}}}, samplers::Tuple{Turing.Inference.RepeatSampler{Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}}}, vi::DynamicPPL.VarInfo{DynamicPPL.LinkSome{Set{AbstractPPL.VarName}, DynamicPPL.UnlinkSome{Set{AbstractPPL.VarName}, DynamicPPL.LinkAll}}, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{Turing.Inference.HMCState{DynamicPPL.VarInfo{DynamicPPL.LinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.LinkedVectorValue{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.Exp{Float64}}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, ADTypes.AutoForwardDiff{1, ForwardDiff.Tag{DynamicPPL.DynamicPPLTag, Float64}}, DynamicPPL.LinkAll, typeof(DynamicPPL.getlogjoint_internal), DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}}, DifferentiationInterface.Constant{typeof(DynamicPPL.getlogjoint_internal)}, DifferentiationInterface.Constant{DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.RangeAndLinked}}}, 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}}}}}}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [23] 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}}}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:438 ┌[24] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [inlined] ╰──── repeated 2 times [26] 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [27] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [inlined] [28] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [29] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [30] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [31] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [32] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [33] 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 [34] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [35] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [36] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [37] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [38] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [39] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [40] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [41] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [42] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [43] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [44] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:379 [inlined] [45] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [46] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:405 [inlined] [47] 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/lLiHA/test/mcmc/gibbs.jl:411 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [19] 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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌[20] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [inlined] ╰──── repeated 2 times [22] 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [23] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [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{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [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), (: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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [33] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [34] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [35] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [36] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [37] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [38] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [40] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:411 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:412 [inlined] [43] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [44] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:413 [inlined] [45] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [46] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [47] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [48] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:55 [inlined] [49] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [50] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [51] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [52] top-level scope @ none:6 [53] eval(m::Module, e::Any) @ Core ./boot.jl:517 [54] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [55] _start() @ Base ./client.jl:593 ┌ Info: Found initial step size └ ϵ = 1.6 [ Info: (symbol = :s, exact = 2.0416666666666665, evaluated = 2.085062534977996) [ Info: (symbol = :m, exact = 1.1666666666666667, evaluated = 1.185959852246637) CSMC and ESS on gdemo: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:425 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, Turing.Inference.GibbsContext{Tuple{AbstractPPL.VarName{:s, AbstractPPL.Iden}}, Base.RefValue{DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s,), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [19] 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}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌[20] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [inlined] ╰──── repeated 2 times [22] 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [23] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [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{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [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), (: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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [33] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [34] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [35] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [36] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [37] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [38] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [40] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:411 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:426 [inlined] [43] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [44] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:427 [inlined] [45] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [46] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [47] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [48] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:55 [inlined] [49] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [50] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [51] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [52] top-level scope @ none:6 [53] eval(m::Module, e::Any) @ Core ./boot.jl:517 [54] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [55] _start() @ Base ./client.jl:593 CSMC on gdemo: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:432 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{DynamicPPL.Model{typeof(Main.Models.gdemo), (:x, :y), (), (), Tuple{Float64, Float64}, Tuple{}, DynamicPPL.DefaultContext, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:s, :m), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [inlined] [19] #_step_or_step_warmup#25 @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:126 [inlined] [20] _step_or_step_warmup @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] [21] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:223 [inlined] [22] (::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [23] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [24] 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 [25] with_progresslogger(f::Function, _module::Module, logger::Base.CoreLogging.ConsoleLogger) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:157 [26] macro expansion @ ~/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:133 [inlined] [27] 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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [28] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [29] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [30] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [31] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [32] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [33] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [34] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [35] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:411 [inlined] [36] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [37] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:433 [inlined] [38] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [39] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:434 [inlined] [40] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [41] top-level scope @ ~/.julia/packages/Turing/lLiHA/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/lLiHA/test/runtests.jl:55 [inlined] [44] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [45] macro expansion @ ~/.julia/packages/Turing/lLiHA/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 PG and HMC on MoGtest_default: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:438 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [19] 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}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌[20] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [inlined] ╰──── repeated 2 times [22] 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [23] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [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{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [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.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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [33] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [34] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [35] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [36] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [37] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [38] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [40] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:411 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:439 [inlined] [43] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [44] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:443 [inlined] [45] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [46] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [47] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [48] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:55 [inlined] [49] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [50] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [51] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [52] top-level scope @ none:6 [53] eval(m::Module, e::Any) @ Core ./boot.jl:517 [54] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [55] _start() @ Base ./client.jl:593 [ Info: (symbol = :s, exact = 2.0416666666666665, evaluated = 2.132660079820084) [ Info: (symbol = :m, exact = 1.1666666666666667, evaluated = 1.1717223959335714) Multiple overlapping samplers on MoGtest_default: Error During Test at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:461 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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] TapedTask @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:75 [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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, Turing.Inference.ParticleMCMCContext{AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}}}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, 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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, varinfo::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}, rng::AdvancedPS.TracedRNG{UInt64, 1, Random123.Philox2x{UInt64, 10}}, resample::Bool) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:462 [11] (::Turing.Inference.var"#56#57"{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}})(::Int64) @ Turing.Inference ./none:-1 [12] iterate @ ./generator.jl:48 [inlined] [13] collect(itr::Base.Generator{UnitRange{Int64}, Turing.Inference.var"#56#57"{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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::Turing.Inference.ProduceLogLikelihoodAccumulator{Float64}}}}}}) @ Base ./array.jl:828 [14] initialstep(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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, spl::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:z1, :z2, :z3, :z4), NTuple{4, DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}; discard_sample::Bool, kwargs::@Kwargs{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:295 [15] initialstep @ ~/.julia/packages/Turing/lLiHA/src/mcmc/particle_mcmc.jl:282 [inlined] [16] #step#6 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:183 [inlined] [17] step @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:170 [inlined] [18] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, num_warmup::Int64, discard_sample::Bool}, ::typeof(AbstractMCMC.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.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}}, DynamicPPL.DefaultContext}, false}, sampler::Turing.Inference.PG{AdvancedPS.ResampleWithESSThreshold{typeof(AdvancedPS.resample_systematic), Float64}}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/interface.jl:118 [19] 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}}}, vi::DynamicPPL.VarInfo{DynamicPPL.UnlinkAll, DynamicPPL.VarNamedTuples.VarNamedTuple{(:mu1, :mu2, :z1, :z2, :z3, :z4), Tuple{DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, DynamicPPL.VectorValue{Vector{Float64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, Vararg{DynamicPPL.VectorValue{Vector{Int64}, Bijectors.VectorBijectors.OnlyWrap{Bijectors.VectorBijectors.TypedIdentity}}, 4}}}, DynamicPPL.AccumulatorTuple{3, @NamedTuple{LogPrior::DynamicPPL.LogPriorAccumulator{Float64}, LogJacobian::DynamicPPL.LogJacobianAccumulator{Float64}, LogLikelihood::DynamicPPL.LogLikelihoodAccumulator{Float64}}}}, states::Tuple{}; initial_params::DynamicPPL.InitFromPrior, kwargs::@Kwargs{num_warmup::Int64}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:420 ┌[20] gibbs_initialstep_recursive │ @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:397 [inlined] ╰──── repeated 2 times [22] 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}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:375 [23] step_warmup @ ~/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:363 [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{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [28] with_logstate(f::AbstractMCMC.var"#29#30"{Nothing, Int64, Int64, Int64, Type{MCMCChains.Chains}, Nothing, @Kwargs{initial_params::DynamicPPL.InitFromPrior}, 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 [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.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}) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 [33] kwcall(::@NamedTuple{initial_params::DynamicPPL.InitFromPrior, chain_type::UnionAll}, ::typeof(AbstractMCMC.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) @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 [34] 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, kwargs::@Kwargs{}) @ Turing.Inference ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [35] sample @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 [inlined] [36] #sample#2 @ ~/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:79 [inlined] [37] 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/lLiHA/src/mcmc/abstractmcmc.jl:76 [38] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:374 [39] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [40] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:411 [inlined] [41] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [42] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:462 [inlined] [43] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [44] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:471 [inlined] [45] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [46] top-level scope @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:33 [47] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [48] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:55 [inlined] [49] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [50] macro expansion @ ~/.julia/packages/Turing/lLiHA/test/runtests.jl:25 [inlined] [51] include(mapexpr::Function, mod::Module, _path::String) @ Base ./Base.jl:327 [52] top-level scope @ none:6 [53] eval(m::Module, e::Any) @ Core ./boot.jl:517 [54] exec_options(opts::Base.JLOptions) @ Base ./client.jl:318 [55] _start() @ Base ./client.jl:593 ┌ Info: Found initial step size └ ϵ = 1.6 ┌ Info: Found initial step size └ ϵ = 1.7000000000000002 ┌ 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 = 1.7000000000000002 ┌ 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 = 1.7000000000000002 ┌ Info: Found initial step size └ ϵ = 1.6 ┌ 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 58 running 1 of 1 signal (10): User defined signal 1 jl_specializations_get_linfo_ at /source/src/gf.c:236 #specialize_method#6 at ./runtime_internals.jl:1790 [inlined] specialize_method at ./runtime_internals.jl:1777 [inlined] typeinf_edge at ./../usr/share/julia/Compiler/src/typeinfer.jl:1145 abstract_call_method at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:769 infercalls at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:178 abstract_call_gf_by_type at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:340 abstract_call_known at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:2941 abstract_call at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3049 abstract_call at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3042 [inlined] abstract_call at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3206 abstract_eval_call at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3224 [inlined] abstract_eval_statement_expr at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3588 abstract_eval_basic_statement at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3995 [inlined] abstract_eval_basic_statement at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:3952 [inlined] typeinf_local at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:4536 jfptr_typeinf_local_1.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 typeinf at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:4814 typeinf_ext at ./../usr/share/julia/Compiler/src/typeinfer.jl:1535 typeinf_ext_toplevel at ./../usr/share/julia/Compiler/src/typeinfer.jl:1718 [inlined] typeinf_ext_toplevel at ./../usr/share/julia/Compiler/src/typeinfer.jl:1727 jfptr_typeinf_ext_toplevel_2.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 jl_apply at /source/src/julia.h:2301 [inlined] jl_type_infer at /source/src/gf.c:467 jl_compile_method_internal at /source/src/gf.c:3640 _jl_invoke at /source/src/gf.c:4105 [inlined] ijl_apply_generic at /source/src/gf.c:4339 #gibbs_step_recursive#100 at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:661 unknown function (ip: 0x73dc65eee0e2) at (unknown file) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_invoke at /source/src/gf.c:4120 gibbs_step_recursive at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:611 [inlined] gibbs_step_recursive at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:611 [inlined] #step#98 at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:465 step at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:451 unknown function (ip: 0x73dc65eecb9b) at (unknown file) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 jl_apply at /source/src/julia.h:2301 [inlined] do_call at /source/src/interpreter.c:123 eval_value at /source/src/interpreter.c:243 eval_stmt_value at /source/src/interpreter.c:194 [inlined] eval_body at /source/src/interpreter.c:693 eval_body at /source/src/interpreter.c:550 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:550 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:550 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:550 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 jl_interpret_toplevel_thunk at /source/src/interpreter.c:884 ijl_eval_thunk at /source/src/toplevel.c:768 jl_toplevel_eval_flex at /source/src/toplevel.c:712 jl_eval_toplevel_stmts at /source/src/toplevel.c:602 jl_eval_module_expr at /source/src/toplevel.c:263 [inlined] jl_toplevel_eval_flex at /source/src/toplevel.c:665 jl_eval_toplevel_stmts at /source/src/toplevel.c:602 jl_toplevel_eval_flex at /source/src/toplevel.c:684 ijl_toplevel_eval at /source/src/toplevel.c:782 ijl_toplevel_eval_in at /source/src/toplevel.c:827 eval at ./boot.jl:517 include_string at ./loading.jl:3107 _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 _include at ./loading.jl:3167 include at ./Base.jl:327 IncludeInto at ./Base.jl:328 jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 jl_apply at /source/src/julia.h:2301 [inlined] do_call at /source/src/interpreter.c:123 eval_value at /source/src/interpreter.c:243 eval_stmt_value at /source/src/interpreter.c:194 [inlined] eval_body at /source/src/interpreter.c:693 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:550 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:550 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 eval_body at /source/src/interpreter.c:558 jl_interpret_toplevel_thunk at /source/src/interpreter.c:884 ijl_eval_thunk at /source/src/toplevel.c:768 jl_toplevel_eval_flex at /source/src/toplevel.c:712 jl_eval_toplevel_stmts at /source/src/toplevel.c:602 jl_toplevel_eval_flex at /source/src/toplevel.c:684 ijl_toplevel_eval at /source/src/toplevel.c:782 ijl_toplevel_eval_in at /source/src/toplevel.c:827 eval at ./boot.jl:517 include_string at ./loading.jl:3107 _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 _include at ./loading.jl:3167 include at ./Base.jl:327 IncludeInto at ./Base.jl:328 jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 jl_apply at /source/src/julia.h:2301 [inlined] do_call at /source/src/interpreter.c:123 eval_value at /source/src/interpreter.c:243 eval_stmt_value at /source/src/interpreter.c:194 [inlined] eval_body at /source/src/interpreter.c:693 jl_interpret_toplevel_thunk at /source/src/interpreter.c:884 ijl_eval_thunk at /source/src/toplevel.c:768 jl_toplevel_eval_flex at /source/src/toplevel.c:712 jl_eval_toplevel_stmts at /source/src/toplevel.c:602 jl_toplevel_eval_flex at /source/src/toplevel.c:684 ijl_toplevel_eval at /source/src/toplevel.c:782 ijl_toplevel_eval_in at /source/src/toplevel.c:827 eval at ./boot.jl:517 exec_options at ./client.jl:318 _start at ./client.jl:593 jfptr__start_0.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 jl_apply at /source/src/julia.h:2301 [inlined] true_main at /source/src/jlapi.c:971 jl_repl_entrypoint at /source/src/jlapi.c:1138 main at /source/cli/loader_exe.c:58 unknown function (ip: 0x73dc81e67249) 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) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== ====================================================================================== 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 wait at ./task.jl:1246 wait_forever at ./task.jl:1168 jfptr_wait_forever_0.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 jl_apply at /source/src/julia.h:2301 [inlined] start_task at /source/src/task.c:1275 unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== ┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel └ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:544 ┌ 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 0x000073126e5e03d0 Total snapshots: 426. Utilization: 0% ╎426 @Base/task.jl:1168 wait_forever() 425╎ 426 @Base/task.jl:1246 wait() [58] signal 15: Terminated in expression starting at /home/pkgeval/.julia/packages/Turing/lLiHA/test/mcmc/gibbs.jl:373 < at ./float.jl:622 [inlined] _log at ./special/log.jl:269 [inlined] log at ./special/log.jl:261 log at /home/pkgeval/.julia/packages/ForwardDiff/z3jRk/src/dual.jl:254 [inlined] _mapreduce at ./reduce.jl:439 _mapreduce_dim at ./reducedim.jl:338 [inlined] #mapreduce#755 at ./reducedim.jl:330 [inlined] mapreduce at ./reducedim.jl:330 [inlined] #_sum#765 at ./reducedim.jl:988 [inlined] _sum at ./reducedim.jl:988 [inlined] #sum#763 at ./reducedim.jl:984 [inlined] sum at ./reducedim.jl:984 [inlined] logdet at /home/pkgeval/.julia/packages/PDMats/RK55S/src/pdiagmat.jl:79 [inlined] logdetcov at /home/pkgeval/.julia/packages/Distributions/FD9q6/src/multivariate/mvnormal.jl:258 [inlined] mvnormal_c0 at /home/pkgeval/.julia/packages/Distributions/FD9q6/src/multivariate/mvnormal.jl:101 [inlined] _logpdf at /home/pkgeval/.julia/packages/Distributions/FD9q6/src/multivariate/mvnormal.jl:139 [inlined] logpdf at /home/pkgeval/.julia/packages/Distributions/FD9q6/src/common.jl:269 [inlined] loglikelihood at /home/pkgeval/.julia/packages/Distributions/FD9q6/src/common.jl:465 [inlined] accumulate_observe!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/accumulators/default.jl:177 #accumulate_observe!!##0 at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/abstract_varinfo.jl:335 [inlined] map at ./tuple.jl:359 [inlined] map at ./namedtuple.jl:263 [inlined] map at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/accumulators.jl:244 [inlined] map_accumulators!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/abstract_varinfo.jl:346 [inlined] accumulate_observe!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/abstract_varinfo.jl:334 [inlined] tilde_observe!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/contexts/default.jl:76 [inlined] tilde_observe!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/contexts/init.jl:403 [inlined] tilde_observe!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/contexts.jl:164 [inlined] demo_assume_multivariate_observe at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/test_utils/models.jl:280 _evaluate!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/model.jl:907 [inlined] evaluate_nowarn!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/model.jl:893 [inlined] init!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/model.jl:803 [inlined] init!! at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/model.jl:811 [inlined] logdensity_at at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/logdensityfunction.jl:368 [inlined] FixTail at /home/pkgeval/.julia/packages/DifferentiationInterface/afUhd/src/utils/context.jl:172 [inlined] vector_mode_dual_eval! at /home/pkgeval/.julia/packages/ForwardDiff/z3jRk/src/apiutils.jl:24 [inlined] vector_mode_gradient! at /home/pkgeval/.julia/packages/ForwardDiff/z3jRk/src/gradient.jl:105 gradient! at /home/pkgeval/.julia/packages/ForwardDiff/z3jRk/src/gradient.jl:39 [inlined] value_and_gradient at /home/pkgeval/.julia/packages/DifferentiationInterface/afUhd/ext/DifferentiationInterfaceForwardDiffExt/onearg.jl:419 [inlined] logdensity_and_gradient at /home/pkgeval/.julia/packages/DynamicPPL/Xldpn/src/logdensityfunction.jl:443 [inlined] #_#56 at ./operators.jl:1202 [inlined] Fix at ./operators.jl:1202 [inlined] ∂H∂θ at /home/pkgeval/.julia/packages/AdvancedHMC/kEVkt/src/hamiltonian.jl:46 [inlined] #step#10 at /home/pkgeval/.julia/packages/AdvancedHMC/kEVkt/src/integrator.jl:244 step at /home/pkgeval/.julia/packages/AdvancedHMC/kEVkt/src/integrator.jl:216 [inlined] sample_phasepoint at /home/pkgeval/.julia/packages/AdvancedHMC/kEVkt/src/trajectory.jl:337 [inlined] transition at /home/pkgeval/.julia/packages/AdvancedHMC/kEVkt/src/trajectory.jl:279 transition at /home/pkgeval/.julia/packages/AdvancedHMC/kEVkt/src/sampler.jl:57 [inlined] #step#31 at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/hmc.jl:221 [inlined] step at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/hmc.jl:206 unknown function (ip: 0x73dc625481c4) at (unknown file) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 #gibbs_step_recursive#100 at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:651 unknown function (ip: 0x73dc62552a48) at (unknown file) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_invoke at /source/src/gf.c:4120 gibbs_step_recursive at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:611 [inlined] gibbs_step_recursive at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:611 [inlined] #step#98 at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:465 step at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/gibbs.jl:451 unknown function (ip: 0x73dc62550d06) at (unknown file) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 jl_apply at /source/src/julia.h:2301 [inlined] jl_f__apply_iterate at /source/src/builtins.c:897 #_step_or_step_warmup#25 at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:0 _step_or_step_warmup at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:124 [inlined] macro expansion at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:296 [inlined] macro expansion at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/logging.jl:137 [inlined] #mcmcsample#27 at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:204 mcmcsample at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:164 #sample#3 at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:93 [inlined] sample at /home/pkgeval/.julia/packages/Turing/lLiHA/src/mcmc/abstractmcmc.jl:82 unknown function (ip: 0x73dc62535e7b) at (unknown file) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 #62 at /home/pkgeval/.julia/packages/AbstractMCMC/C1aKp/src/sample.jl:684 unknown function (ip: 0x73dc62535ca8) at (unknown file) _jl_invoke at /source/src/gf.c:4113 [inlined] ijl_apply_generic at /source/src/gf.c:4339 jl_apply at /source/src/julia.h:2301 [inlined] start_task at /source/src/task.c:1275 unknown function (ip: (nil)) at (unknown file) Allocations: 1661851636 (Pool: 1661842097; Big: 9539); GC: 303 PkgEval terminated after 2752.04s: test duration exceeded the time limit