Package evaluation to test Latte on Julia 1.14.0-DEV.2637 (b1f508acef*) started at 2026-07-13T03:37:00.849


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

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

Set-up completed after 15.14s


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# Installation
#

Installing Latte...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [d585094e] + Latte v0.1.1
    Updating `~/.julia/environments/v1.14/Manifest.toml`
  [47edcb42] + ADTypes v1.22.2
  [14f7f29c] + AMD v0.5.3
  [621f4979] + AbstractFFTs v1.5.0
  [80f14c24] + AbstractMCMC v5.15.1
⌅ [7a57a42e] + AbstractPPL v0.14.2
  [1520ce14] + AbstractTrees v0.4.5
  [7d9f7c33] + Accessors v0.1.45
  [79e6a3ab] + Adapt v4.7.0
  [0bf59076] + AdvancedHMC v0.8.6
  [66dad0bd] + AliasTables v1.1.3
  [dce04be8] + ArgCheck v2.5.0
  [ec485272] + ArnoldiMethod v0.4.0
  [4fba245c] + ArrayInterface v7.27.0
  [13072b0f] + AxisAlgorithms v1.1.0
  [39de3d68] + AxisArrays v0.4.8
  [198e06fe] + BangBang v0.4.9
⌅ [76274a88] + Bijectors v0.15.24
  [d360d2e6] + ChainRulesCore v1.26.1
  [0ca39b1e] + Chairmarks v1.3.1
  [9e997f8a] + ChangesOfVariables v0.1.10
  [60701a23] + CliqueTrees v1.19.4
  [08986516] + Collects v1.1.0
  [861a8166] + Combinatorics v1.1.0
  [38540f10] + CommonSolve v0.2.11
  [bbf7d656] + CommonSubexpressions v0.3.1
  [34da2185] + Compat v4.18.1
  [a33af91c] + CompositionsBase v0.1.2
  [2569d6c7] + ConcreteStructs v0.2.6
  [88cd18e8] + ConsoleProgressMonitor v0.1.2
  [187b0558] + ConstructionBase v1.6.0
  [a8cc5b0e] + Crayons v4.1.1
  [9a962f9c] + DataAPI v1.16.0
  [a93c6f00] + DataFrames v1.8.2
⌅ [82cc6244] + DataInterpolations v8.10.0
  [864edb3b] + DataStructures v0.19.5
  [e2d170a0] + DataValueInterfaces v1.0.0
  [b429d917] + DensityInterface v0.4.0
  [163ba53b] + DiffResults v1.1.0
  [b552c78f] + DiffRules v1.16.0
  [a0c0ee7d] + DifferentiationInterface v0.7.20
  [b4f34e82] + Distances v0.10.12
⌃ [31c24e10] + Distributions v0.25.127
  [ffbed154] + DocStringExtensions v0.9.5
⌅ [366bfd00] + DynamicPPL v0.40.24
  [4e289a0a] + EnumX v1.0.7
  [f151be2c] + EnzymeCore v0.8.21
  [e2ba6199] + ExprTools v0.1.10
  [b86e33f2] + FFTA v0.3.1
  [442a2c76] + FastGaussQuadrature v1.3.0
  [1a297f60] + FillArrays v1.16.0
⌅ [64ca27bc] + FindFirstFunctions v1.8.0
  [6a86dc24] + FiniteDiff v2.32.0
  [3821ddf9] + FixedSizeArrays v1.3.0
⌅ [f6369f11] + ForwardDiff v0.10.39
  [069b7b12] + FunctionWrappers v1.1.3
  [77dc65aa] + FunctionWrappersWrappers v1.10.1
  [d9f16b24] + Functors v0.5.2
  [46192b85] + GPUArraysCore v0.2.0
  [a0844989] + Gamma v1.1.0
  [d5f06795] + GaussianMarkovRandomFields v0.12.3
  [86223c79] + Graphs v1.14.0
  [19dc6840] + HCubature v1.8.0
  [34004b35] + HypergeometricFunctions v0.3.29
  [d25df0c9] + Inflate v0.1.5
  [22cec73e] + InitialValues v0.3.1
  [842dd82b] + InlineStrings v1.4.5
  [18e54dd8] + IntegerMathUtils v0.1.3
  [a98d9a8b] + Interpolations v0.16.3
  [8197267c] + IntervalSets v0.7.14
  [3587e190] + InverseFunctions v0.1.17
  [41ab1584] + InvertedIndices v1.3.1
  [92d709cd] + IrrationalConstants v0.2.6
  [c8e1da08] + IterTools v1.10.0
  [82899510] + IteratorInterfaceExtensions v1.0.0
  [692b3bcd] + JLLWrappers v1.8.0
  [682c06a0] + JSON v1.6.1
  [5ab0869b] + KernelDensity v0.6.12
  [ba0b0d4f] + Krylov v0.10.8
  [b964fa9f] + LaTeXStrings v1.4.0
  [d585094e] + Latte v0.1.1
⌅ [1d6d02ad] + LeftChildRightSiblingTrees v0.2.1
⌃ [d3d80556] + LineSearches v7.5.1
  [7a12625a] + LinearMaps v3.11.4
⌅ [7ed4a6bd] + LinearSolve v3.87.0
  [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 v0.3.19
  [e80e1ace] + MLJModelInterface v1.12.1
  [1914dd2f] + MacroTools v0.5.16
  [dbb5928d] + MappedArrays v0.4.3
  [e1d29d7a] + Missings v1.2.0
  [46d2c3a1] + MuladdMacro v0.2.6
⌅ [d41bc354] + NLSolversBase v7.10.0
  [77ba4419] + NaNMath v1.1.4
  [c020b1a1] + NaturalSort v1.0.0
  [b8a86587] + NearestNeighbors v0.4.28
  [6fe1bfb0] + OffsetArrays v1.17.0
⌅ [429524aa] + Optim v1.13.3
⌅ [bac558e1] + OrderedCollections v1.8.2
  [90014a1f] + PDMats v0.11.40
  [69de0a69] + Parsers v2.8.6
  [2dfb63ee] + PooledArrays v1.4.3
  [85a6dd25] + PositiveFactorizations v0.2.4
  [d236fae5] + PreallocationTools v1.3.0
  [aea7be01] + PrecompileTools v1.3.4
  [21216c6a] + Preferences v1.5.2
  [08abe8d2] + PrettyTables v3.4.0
  [27ebfcd6] + Primes v0.5.7
  [33c8b6b6] + ProgressLogging v0.1.6
  [92933f4c] + ProgressMeter v1.11.0
  [43287f4e] + PtrArrays v1.4.0
⌃ [0c0d3e7f] + PureKLU v1.0.2
  [1fd47b50] + QuadGK v2.11.3
  [b3c3ace0] + RangeArrays v0.3.2
  [c84ed2f1] + Ratios v0.4.5
  [3cdcf5f2] + RecipesBase v1.3.4
  [731186ca] + RecursiveArrayTools v4.3.3
  [189a3867] + Reexport v1.2.2
  [ae029012] + Requires v1.3.1
  [37e2e3b7] + ReverseDiff v1.17.0
  [79098fc4] + Rmath v0.9.0
⌅ [f2b01f46] + Roots v2.3.0
  [7e49a35a] + RuntimeGeneratedFunctions v0.5.22
⌃ [0bca4576] + SciMLBase v3.34.0
  [a6db7da4] + SciMLLogging v2.0.3
  [c0aeaf25] + SciMLOperators v1.24.0
  [431bcebd] + SciMLPublic v1.2.2
  [53ae85a6] + SciMLStructures v1.10.2
  [30f210dd] + ScientificTypesBase v3.1.0
  [043bf095] + SelectedInversion v0.2.1
  [91c51154] + SentinelArrays v1.4.10
  [efcf1570] + Setfield v1.1.2
  [1277b4bf] + ShiftedArrays v2.0.0
  [699a6c99] + SimpleTraits v0.9.6
  [a2af1166] + SortingAlgorithms v1.2.3
  [a57abbd0] + SparseColumnPivotedQR v2.1.4
  [9f842d2f] + SparseConnectivityTracer v1.2.2
  [0a514795] + SparseMatrixColorings v0.4.27
  [276daf66] + SpecialFunctions v2.8.0
  [860ef19b] + StableRNGs v1.0.4
  [90137ffa] + StaticArrays v1.9.18
  [1e83bf80] + StaticArraysCore v1.4.4
  [64bff920] + StatisticalTraits v3.5.0
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.8.0
  [2913bbd2] + StatsBase v0.34.12
⌅ [4c63d2b9] + StatsFuns v1.5.2
  [3eaba693] + StatsModels v0.7.10
  [892a3eda] + StringManipulation v0.4.4
  [ec057cc2] + StructUtils v2.8.2
  [2efcf032] + SymbolicIndexingInterface v0.3.51
  [3783bdb8] + TableTraits v1.0.1
  [bd369af6] + Tables v1.13.0
  [5d786b92] + TerminalLoggers v0.1.7
  [781d530d] + TruncatedStacktraces v1.4.0
  [efce3f68] + WoodburyMatrices v1.1.0
  [1d5cc7b8] + IntelOpenMP_jll v2025.2.0+0
  [856f044c] + MKL_jll v2025.2.0+0
  [efe28fd5] + OpenSpecFun_jll v0.5.6+0
  [f50d1b31] + Rmath_jll v0.5.1+0
  [1317d2d5] + oneTBB_jll v2022.3.0+0
  [0dad84c5] + ArgTools v1.2.0
  [56f22d72] + Artifacts v1.11.0
  [2a0f44e3] + Base64 v1.11.0
  [ade2ca70] + Dates v1.11.0
  [8ba89e20] + Distributed v1.11.0
  [f43a241f] + Downloads v1.7.0
  [7b1f6079] + FileWatching v1.11.0
  [9fa8497b] + Future v1.11.0
  [b77e0a4c] + InteractiveUtils v1.11.0
  [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0
  [4af54fe1] + LazyArtifacts v1.11.0
  [b27032c2] + LibCURL v1.0.0
  [76f85450] + LibGit2 v1.11.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.14.0
  [56ddb016] + Logging v1.11.0
  [d6f4376e] + Markdown v1.11.0
  [a63ad114] + Mmap v1.11.0
  [ca575930] + NetworkOptions v1.3.0
  [44cfe95a] + Pkg v1.14.0
  [de0858da] + Printf v1.11.0
  [3fa0cd96] + REPL v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v1.13.0
  [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
  [a4e569a6] + Tar v1.10.0
  [8dfed614] + Test v1.11.0
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.5.5+2
  [deac9b47] + LibCURL_jll v8.21.0+0
  [e37daf67] + LibGit2_jll v1.9.4+0
  [29816b5a] + LibSSH2_jll v1.11.101+0
  [14a3606d] + MozillaCACerts_jll v2026.5.14
  [4536629a] + OpenBLAS_jll v0.3.33+0
  [05823500] + OpenLibm_jll v0.8.7+0
  [458c3c95] + OpenSSL_jll v3.5.7+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 v1.69.0+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. To see why use `status --outdated -m`

Installation completed after 4.9s


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# Precompilation
#

Precompiling PkgEval dependencies...

┌ Warning: Could not use exact versions of packages in manifest, re-resolving
└ @ TestEnv ~/.julia/packages/TestEnv/RUPmD/src/julia-1.13/activate_set.jl:78
Precompiling package dependencies...
Precompiling project...
   3.6 s  ✓ SelectedInversion → SelectedInversionLDLFactorizations
  11.6 s  ✓ Ferrite
   5.8 s  ✓ DataInterpolations → DataInterpolationsSparseConnectivityTracerExt
  24.1 s  ✓ Bijectors → BijectorsReverseDiffExt
   7.1 s  ✓ Bijectors → BijectorsForwardDiffExt
  19.8 s  ✓ DynamicPPL
  23.2 s  ✓ AdvancedVI → AdvancedVIReverseDiffExt
  16.1 s  ✓ LinearSolve → LinearSolveCliqueTreesExt
  40.4 s  ✓ OptimizationOptimJL
   5.7 s  ✓ FerriteGmsh
  10.1 s  ✓ DynamicPPL → DynamicPPLMCMCChainsExt
   6.4 s  ✓ DynamicPPL → DynamicPPLForwardDiffExt
   6.3 s  ✓ DynamicPPL → DynamicPPLEnzymeCoreExt
  24.4 s  ✓ DynamicPPL → DynamicPPLReverseDiffExt
  16.0 s  ✓ GaussianMarkovRandomFields
  14.9 s  ✓ Turing
  11.9 s  ✓ GaussianMarkovRandomFields → GaussianMarkovRandomFieldsSparseADLikelihoods
  12.8 s  ✓ GaussianMarkovRandomFields → GaussianMarkovRandomFieldsFormula
  13.6 s  ✓ GaussianMarkovRandomFields → GaussianMarkovRandomFieldsForwardDiff
  12.5 s  ✓ GaussianMarkovRandomFields → GaussianMarkovRandomFieldsLibGEOS
ERROR: LoadError: MethodError: no method matching (::Latte.var"#create_progress_callback##0#create_progress_callback##1"{Latte.ProgressState, String})(; start_index::Int64, n_starts::Int64, iteration::Int64, objective::Float64, gradient_norm::Float64)
This method does not support all of the given keyword arguments (and may not support any).

Closest candidates are:
  (::Latte.var"#create_progress_callback##0#create_progress_callback##1")(Any...) got unsupported keyword arguments "start_index", "n_starts", "iteration", "objective", "gradient_norm"
   @ Latte ~/.julia/packages/Latte/6Zhta/src/inference/inla/progress.jl:108

Stacktrace:
  [1] (::Latte.var"#164#165"{Int64, Bool, Int64})(state::Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/laplace/mode_finding.jl:375
  [2] update!(tr::Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}}}, iteration::Int64, f_x::Float64, grnorm::Float64, dt::Dict{Any, Any}, store_trace::Bool, show_trace::Bool, show_every::Int64, callback::Latte.var"#164#165"{Int64, Bool, Int64}, trace_simplex::Bool)
    @ Optim ~/.julia/packages/Optim/gmigl/src/utilities/update.jl:27
  [3] update!(tr::Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}}}, iteration::Int64, f_x::Float64, grnorm::Float64, dt::Dict{Any, Any}, store_trace::Bool, show_trace::Bool, show_every::Int64, callback::Latte.var"#164#165"{Int64, Bool, Int64})
    @ Optim ~/.julia/packages/Optim/gmigl/src/utilities/update.jl:13 [inlined]
  [4] trace!(tr::Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}}}, d::NLSolversBase.OnceDifferentiable{Float64, Vector{Float64}, Vector{Float64}}, state::Optim.BFGSState{Vector{Float64}, Matrix{Float64}, Float64, Vector{Float64}}, iteration::Int64, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}}, curr_time::Float64)
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/solvers/first_order/bfgs.jl:201
  [5] optimize(d::NLSolversBase.OnceDifferentiable{Float64, Vector{Float64}, Vector{Float64}}, initial_x::Vector{Float64}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}}, state::Optim.BFGSState{Vector{Float64}, Matrix{Float64}, Float64, Vector{Float64}})
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/optimize/optimize.jl:61
  [6] optimize(d::NLSolversBase.OnceDifferentiable{Float64, Vector{Float64}, Vector{Float64}}, initial_x::Vector{Float64}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}})
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/optimize/optimize.jl:43 [inlined]
  [7] optimize(f::Latte.var"#162#163"{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Vector{Latte.WorkingHyperparameters}, Vector{Float64}, Bool, Bool, Base.RefValue{Union{Nothing, Vector{Float64}}}, Base.RefValue{Vector{Float64}}}, g::Latte.var"#gradient!#_run_optimization##1"{Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.var"#objective_clean#_run_optimization##0"{Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Base.RefValue{Union{Nothing, Vector{Float64}}}, Bool}}, initial_x::Vector{Float64}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}}; inplace::Bool, autodiff::Symbol)
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/optimize/interface.jl:301 [inlined]
  [8] optimize(f::Latte.var"#162#163"{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Vector{Latte.WorkingHyperparameters}, Vector{Float64}, Bool, Bool, Base.RefValue{Union{Nothing, Vector{Float64}}}, Base.RefValue{Vector{Float64}}}, g::Latte.var"#gradient!#_run_optimization##1"{Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.var"#objective_clean#_run_optimization##0"{Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Base.RefValue{Union{Nothing, Vector{Float64}}}, Bool}}, initial_x::Vector{Float64}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}})
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/optimize/interface.jl:289 [inlined]
  [9] _run_optimization(strategy::Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, objective::Latte.var"#162#163"{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Vector{Latte.WorkingHyperparameters}, Vector{Float64}, Bool, Bool, Base.RefValue{Union{Nothing, Vector{Float64}}}, Base.RefValue{Vector{Float64}}}, model::Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, y::GaussianMarkovRandomFields.PoissonObservations, spec::Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, θ_init::Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}, ws::GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}}, last_mode::Base.RefValue{Union{Nothing, Vector{Float64}}}, do_warm::Bool)
    @ Latte ~/.julia/packages/Latte/6Zhta/src/laplace/mode_finding.jl:492 [inlined]
 [10] (::Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}})(::Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}, ws::GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/laplace/mode_finding.jl:396
 [11] (::Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}})(x::Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/parallel/executors.jl:126 [inlined]
 [12] iterate(::Base.Generator{Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}})
    @ Base generator.jl:49 [inlined]
 [13] _collect(c::Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, itr::Base.Generator{Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, ::Base.EltypeUnknown, isz::Base.HasShape{1})
    @ Base array.jl:853
 [14] collect_similar(cont::Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, itr::Base.Generator{Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}})
    @ Base array.jl:768 [inlined]
 [15] map(f::Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}, A::Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}})
    @ Base abstractarray.jl:3468 [inlined]
 [16] (::Latte.var"#20#21"{Nothing, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}, Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}})(ws::GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/parallel/executors.jl:126 [inlined]
 [17] with_workspace(f::Latte.var"#20#21"{Nothing, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}, Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}}, pool::GaussianMarkovRandomFields.WorkspacePool{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}})
    @ GaussianMarkovRandomFields ~/.julia/packages/GaussianMarkovRandomFields/I3Mdk/src/workspace/workspace_pool.jl:110
 [18] pmap_executor(f::Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}, xs::Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, ::Latte.SequentialExecutor, pool::GaussianMarkovRandomFields.WorkspacePool{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}; on_complete::Nothing)
    @ Latte ~/.julia/packages/Latte/6Zhta/src/parallel/executors.jl:125
 [19] find_hyperparameter_mode(model::Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, y::GaussianMarkovRandomFields.PoissonObservations; method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, iterations::Int64, collect_points::Bool, progress_callback::Latte.var"#create_progress_callback##0#create_progress_callback##1"{Latte.ProgressState, String}, diff_strategy::Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, mode_init::Latte.PriorModeStart, latent_init::Latte.ZeroLatentStart, executor::Latte.SequentialExecutor, warm_start::Nothing)
    @ Latte ~/.julia/packages/Latte/6Zhta/src/laplace/mode_finding.jl:420
 [20] inla(model::Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, y::Vector{Int64}; latent_marginalization_method::Latte.SimplifiedLaplace, hyperparameter_marginalization_method::Latte.AutoHyperparameterMarginal, latent_indices::Nothing, exploration_strategy::Latte.GridExplorationStrategy, mode_method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, mode_iterations::Int64, mode_init::Latte.PriorModeStart, latent_init::Latte.ZeroLatentStart, mode_diagnostic::Symbol, mode_diagnostic_tol::Float64, progress::Bool, accumulators::Tuple{}, executor::Latte.SequentialExecutor, diff_strategy::Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/inference/inla/inference.jl:123
 [21] macro expansion
    @ ~/.julia/packages/Latte/6Zhta/src/precompile_workloads.jl:102 [inlined]
 [22] macro expansion
    @ ~/.julia/packages/PrecompileTools/QUxvR/src/workloads.jl:70 [inlined]
 [23] macro expansion
    @ ~/.julia/packages/Latte/6Zhta/src/precompile_workloads.jl:97 [inlined]
 [24] macro expansion
    @ ~/.julia/packages/PrecompileTools/QUxvR/src/workloads.jl:118 [inlined]
 [25] top-level scope
    @ ~/.julia/packages/Latte/6Zhta/src/precompile_workloads.jl:115
 [26] include(mapexpr::Function, mod::Module, _path::String)
    @ Base Base.jl:326
 [27] top-level scope
    @ ~/.julia/packages/Latte/6Zhta/src/Latte.jl:178
 [28] include(mod::Module, _path::String)
    @ Base Base.jl:325
 [29] 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:3359
 [30] top-level scope
    @ stdin:5
 [31] eval(m::Module, e::Any)
    @ Core boot.jl:545
 [32] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base loading.jl:3186
 [33] include_string(m::Module, txt::String, fname::String)
    @ Base loading.jl:3196 [inlined]
 [34] exec_options(opts::Base.JLOptions)
    @ Base client.jl:353
 [35] _start()
    @ Base client.jl:596
in expression starting at /home/pkgeval/.julia/packages/Latte/6Zhta/src/precompile_workloads.jl:30
in expression starting at /home/pkgeval/.julia/packages/Latte/6Zhta/src/Latte.jl:1
in expression starting at stdin:5
              ✗ Latte
WARNING: Constructor for type "FEMDiscretization" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
  NOTE: Assumed "FEMDiscretization" refers to `GaussianMarkovRandomFields.FEMDiscretization`. This behavior is deprecated and may differ in future versions.
  NOTE: This behavior may have differed in Julia versions prior to 1.12.
  Hint: If you intended to create a new generic function of the same name, use `function FEMDiscretization end`.
  Hint: To silence the warning, qualify `FEMDiscretization` as `GaussianMarkovRandomFields.FEMDiscretization` in the method signature or explicitly `import GaussianMarkovRandomFields: FEMDiscretization`.
WARNING: Constructor for type "ImplicitEulerSSM" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
  NOTE: Assumed "ImplicitEulerSSM" refers to `GaussianMarkovRandomFields.ImplicitEulerSSM`. This behavior is deprecated and may differ in future versions.
  NOTE: This behavior may have differed in Julia versions prior to 1.12.
  Hint: If you intended to create a new generic function of the same name, use `function ImplicitEulerSSM end`.
  Hint: To silence the warning, qualify `ImplicitEulerSSM` as `GaussianMarkovRandomFields.ImplicitEulerSSM` in the method signature or explicitly `import GaussianMarkovRandomFields: ImplicitEulerSSM`.
WARNING: Constructor for type "ImplicitEulerJointSSMMatrices" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
  NOTE: Assumed "ImplicitEulerJointSSMMatrices" refers to `GaussianMarkovRandomFields.ImplicitEulerJointSSMMatrices`. This behavior is deprecated and may differ in future versions.
  NOTE: This behavior may have differed in Julia versions prior to 1.12.
  Hint: If you intended to create a new generic function of the same name, use `function ImplicitEulerJointSSMMatrices end`.
  Hint: To silence the warning, qualify `ImplicitEulerJointSSMMatrices` as `GaussianMarkovRandomFields.ImplicitEulerJointSSMMatrices` in the method signature or explicitly `import GaussianMarkovRandomFields: ImplicitEulerJointSSMMatrices`.
WARNING: Constructor for type "ImplicitEulerConstantMeshSTGMRF" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
  NOTE: Assumed "ImplicitEulerConstantMeshSTGMRF" refers to `GaussianMarkovRandomFields.ImplicitEulerConstantMeshSTGMRF`. This behavior is deprecated and may differ in future versions.
  NOTE: This behavior may have differed in Julia versions prior to 1.12.
  Hint: If you intended to create a new generic function of the same name, use `function ImplicitEulerConstantMeshSTGMRF end`.
  Hint: To silence the warning, qualify `ImplicitEulerConstantMeshSTGMRF` as `GaussianMarkovRandomFields.ImplicitEulerConstantMeshSTGMRF` in the method signature or explicitly `import GaussianMarkovRandomFields: ImplicitEulerConstantMeshSTGMRF`.
WARNING: Constructor for type "ConcreteConstantMeshSTGMRF" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
  NOTE: Assumed "ConcreteConstantMeshSTGMRF" refers to `GaussianMarkovRandomFields.ConcreteConstantMeshSTGMRF`. This behavior is deprecated and may differ in future versions.
  NOTE: This behavior may have differed in Julia versions prior to 1.12.
  Hint: If you intended to create a new generic function of the same name, use `function ConcreteConstantMeshSTGMRF end`.
  Hint: To silence the warning, qualify `ConcreteConstantMeshSTGMRF` as `GaussianMarkovRandomFields.ConcreteConstantMeshSTGMRF` in the method signature or explicitly `import GaussianMarkovRandomFields: ConcreteConstantMeshSTGMRF`.
WARNING: Constructor for type "MaternModel" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
  NOTE: Assumed "MaternModel" refers to `GaussianMarkovRandomFields.MaternModel`. This behavior is deprecated and may differ in future versions.
  NOTE: This behavior may have differed in Julia versions prior to 1.12.
  Hint: If you intended to create a new generic function of the same name, use `function MaternModel end`.
  Hint: To silence the warning, qualify `MaternModel` as `GaussianMarkovRandomFields.MaternModel` in the method signature or explicitly `import GaussianMarkovRandomFields: MaternModel`.
WARNING: Constructor for type "BarrierModel" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
  NOTE: Assumed "BarrierModel" refers to `GaussianMarkovRandomFields.BarrierModel`. This behavior is deprecated and may differ in future versions.
  NOTE: This behavior may have differed in Julia versions prior to 1.12.
  Hint: If you intended to create a new generic function of the same name, use `function BarrierModel end`.
  Hint: To silence the warning, qualify `BarrierModel` as `GaussianMarkovRandomFields.BarrierModel` in the method signature or explicitly `import GaussianMarkovRandomFields: BarrierModel`.
  15.4 s  ✓ GaussianMarkovRandomFields → GaussianMarkovRandomFieldsFEM
  21 dependencies successfully precompiled in 436 seconds. 426 already precompiled.
  1 dependency had output during precompilation:
┌ GaussianMarkovRandomFields → GaussianMarkovRandomFieldsFEM
│  WARNING: Constructor for type "FEMDiscretization" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
│    NOTE: Assumed "FEMDiscretization" refers to `GaussianMarkovRandomFields.FEMDiscretization`. This behavior is deprecated and may differ in future versions.
│    NOTE: This behavior may have differed in Julia versions prior to 1.12.
│    Hint: If you intended to create a new generic function of the same name, use `function FEMDiscretization end`.
│    Hint: To silence the warning, qualify `FEMDiscretization` as `GaussianMarkovRandomFields.FEMDiscretization` in the method signature or explicitly `import GaussianMarkovRandomFields: FEMDiscretization`.
│  WARNING: Constructor for type "ImplicitEulerSSM" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
│    NOTE: Assumed "ImplicitEulerSSM" refers to `GaussianMarkovRandomFields.ImplicitEulerSSM`. This behavior is deprecated and may differ in future versions.
│    NOTE: This behavior may have differed in Julia versions prior to 1.12.
│    Hint: If you intended to create a new generic function of the same name, use `function ImplicitEulerSSM end`.
│    Hint: To silence the warning, qualify `ImplicitEulerSSM` as `GaussianMarkovRandomFields.ImplicitEulerSSM` in the method signature or explicitly `import GaussianMarkovRandomFields: ImplicitEulerSSM`.
│  WARNING: Constructor for type "ImplicitEulerJointSSMMatrices" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
│    NOTE: Assumed "ImplicitEulerJointSSMMatrices" refers to `GaussianMarkovRandomFields.ImplicitEulerJointSSMMatrices`. This behavior is deprecated and may differ in future versions.
│    NOTE: This behavior may have differed in Julia versions prior to 1.12.
│    Hint: If you intended to create a new generic function of the same name, use `function ImplicitEulerJointSSMMatrices end`.
│    Hint: To silence the warning, qualify `ImplicitEulerJointSSMMatrices` as `GaussianMarkovRandomFields.ImplicitEulerJointSSMMatrices` in the method signature or explicitly `import GaussianMarkovRandomFields: ImplicitEulerJointSSMMatrices`.
│  WARNING: Constructor for type "ImplicitEulerConstantMeshSTGMRF" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
│    NOTE: Assumed "ImplicitEulerConstantMeshSTGMRF" refers to `GaussianMarkovRandomFields.ImplicitEulerConstantMeshSTGMRF`. This behavior is deprecated and may differ in future versions.
│    NOTE: This behavior may have differed in Julia versions prior to 1.12.
│    Hint: If you intended to create a new generic function of the same name, use `function ImplicitEulerConstantMeshSTGMRF end`.
│    Hint: To silence the warning, qualify `ImplicitEulerConstantMeshSTGMRF` as `GaussianMarkovRandomFields.ImplicitEulerConstantMeshSTGMRF` in the method signature or explicitly `import GaussianMarkovRandomFields: ImplicitEulerConstantMeshSTGMRF`.
│  WARNING: Constructor for type "ConcreteConstantMeshSTGMRF" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
│    NOTE: Assumed "ConcreteConstantMeshSTGMRF" refers to `GaussianMarkovRandomFields.ConcreteConstantMeshSTGMRF`. This behavior is deprecated and may differ in future versions.
│    NOTE: This behavior may have differed in Julia versions prior to 1.12.
│    Hint: If you intended to create a new generic function of the same name, use `function ConcreteConstantMeshSTGMRF end`.
│    Hint: To silence the warning, qualify `ConcreteConstantMeshSTGMRF` as `GaussianMarkovRandomFields.ConcreteConstantMeshSTGMRF` in the method signature or explicitly `import GaussianMarkovRandomFields: ConcreteConstantMeshSTGMRF`.
│  WARNING: Constructor for type "MaternModel" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
│    NOTE: Assumed "MaternModel" refers to `GaussianMarkovRandomFields.MaternModel`. This behavior is deprecated and may differ in future versions.
│    NOTE: This behavior may have differed in Julia versions prior to 1.12.
│    Hint: If you intended to create a new generic function of the same name, use `function MaternModel end`.
│    Hint: To silence the warning, qualify `MaternModel` as `GaussianMarkovRandomFields.MaternModel` in the method signature or explicitly `import GaussianMarkovRandomFields: MaternModel`.
│  WARNING: Constructor for type "BarrierModel" was extended in `GaussianMarkovRandomFieldsFEM` without explicit qualification or import.
│    NOTE: Assumed "BarrierModel" refers to `GaussianMarkovRandomFields.BarrierModel`. This behavior is deprecated and may differ in future versions.
│    NOTE: This behavior may have differed in Julia versions prior to 1.12.
│    Hint: If you intended to create a new generic function of the same name, use `function BarrierModel end`.
│    Hint: To silence the warning, qualify `BarrierModel` as `GaussianMarkovRandomFields.BarrierModel` in the method signature or explicitly `import GaussianMarkovRandomFields: BarrierModel`.
└  

Precompilation completed after 467.33s


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

     Testing Latte
        Test Could not use exact versions of packages in manifest, re-resolving. Note: if you do not check your manifest file into source control, then you can probably ignore this message. However, if you do check your manifest file into source control, then you probably want to pass the `allow_reresolve = false` kwarg when calling the `Pkg.test` function.
    Updating `/tmp/jl_JDCkp4/Project.toml`
  [4c88cf16] + Aqua v0.8.16
  [c061ca5d] + Ferrite v1.4.1
  [4f95f4f8] + FerriteGmsh v1.3.0
  [705231aa] + Gmsh v0.3.1
⌅ [033835bb] + JLD2 v0.5.15
  [40e66cde] + LDLFactorizations v0.10.2
  [d585094e] + Latte v0.1.1
  [a90b1aa1] + LibGEOS v0.9.7
⌅ [fce5fe82] + Turing v0.43.7
    Updating `/tmp/jl_JDCkp4/Manifest.toml`
  [5b7e9947] + AdvancedMH v0.8.10
  [576499cb] + AdvancedPS v0.7.2
⌅ [b5ca4192] + AdvancedVI v0.6.2
  [4c88cf16] + Aqua v0.8.16
  [fa961155] + CEnum v0.5.0
  [944b1d66] + CodecZlib v0.7.8
  [cad2338a] + EllipticalSliceSampling v2.0.0
  [55351af7] + ExproniconLite v0.10.14
  [411431e0] + Extents v0.1.6
  [9aa1b823] + FastClosures v0.3.2
  [c061ca5d] + Ferrite v1.4.1
  [4f95f4f8] + FerriteGmsh v1.3.0
  [5789e2e9] + FileIO v1.19.0
  [68eda718] + GeoFormatTypes v0.4.5
  [cf35fbd7] + GeoInterface v1.6.1
  [705231aa] + Gmsh v0.3.1
  [076d061b] + HashArrayMappedTries v0.2.0
⌅ [033835bb] + JLD2 v0.5.15
  [ae98c720] + Jieko v0.2.1
  [40e66cde] + LDLFactorizations v0.10.2
  [d585094e] + Latte v0.1.1
  [a90b1aa1] + LibGEOS v0.9.7
  [6f1fad26] + Libtask v0.9.18
  [9c8b4983] + LightXML v0.9.3
  [3da0fdf6] + MPIPreferences v0.1.12
  [dbe65cb8] + MistyClosures v2.1.0
  [2e0e35c7] + Moshi v0.3.10
  [3bd65402] + Optimisers v0.4.7
⌃ [7f7a1694] + Optimization v5.4.0
⌅ [bca83a33] + OptimizationBase v4.2.0
⌃ [36348300] + OptimizationOptimJL v0.4.8
  [74087812] + Random123 v1.7.1
  [e6cf234a] + RandomNumbers v1.6.0
⌅ [731186ca] ↓ RecursiveArrayTools v4.3.3 ⇒ v3.54.0
  [fdea26ae] + SIMD v3.7.2
  [26aad666] + SSMProblems v0.6.1
⌅ [0bca4576] ↓ SciMLBase v3.34.0 ⇒ v2.155.1
⌅ [a6db7da4] ↓ SciMLLogging v2.0.3 ⇒ v1.10.1
  [7e506255] + ScopedValues v1.6.2
  [48a634ad] + Tensors v1.17.1
  [3bb67fe8] + TranscodingStreams v0.11.3
⌅ [fce5fe82] + Turing v0.43.7
  [4004b06d] + VTKBase v1.0.1
  [64499a7a] + WriteVTK v1.22.0
  [6e34b625] + Bzip2_jll v1.0.9+0
  [83423d85] + Cairo_jll v1.18.7+0
  [2e619515] + Expat_jll v2.8.2+0
  [4fce6fc7] + FLTK_jll v1.3.8+0
  [a3f928ae] + Fontconfig_jll v2.17.1+0
  [d7e528f0] + FreeType2_jll v2.14.3+1
  [d604d12d] + GEOS_jll v3.14.1+0
  [bd17208b] + GLU_jll v9.0.1+0
⌅ [b0724c58] + GettextRuntime_jll v0.22.4+0
  [7746bdde] + Glib_jll v2.86.3+0
  [0234f1f7] + HDF5_jll v2.1.2+0
  [e33a78d0] + Hwloc_jll v2.14.0+0
  [aacddb02] + JpegTurbo_jll v3.2.0+0
  [1d63c593] + LLVMOpenMP_jll v22.1.7+0
⌅ [e9f186c6] + Libffi_jll v3.4.7+0
  [7e76a0d4] + Libglvnd_jll v1.7.1+1
  [94ce4f54] + Libiconv_jll v1.18.0+0
  [4b2f31a3] + Libmount_jll v2.42.0+0
  [38a345b3] + Libuuid_jll v2.42.0+0
  [18c40d15] + LinearElasticity_jll v5.0.0+0
  [d00139f3] + METIS_jll v5.1.3+0
  [86086c02] + MMG_jll v5.6.0+0
  [b5ada748] + MPIABI_jll v0.1.5+0
  [7cb0a576] + MPICH_jll v5.0.1+0
  [f1f71cc9] + MPItrampoline_jll v5.5.6+0
  [9237b28f] + MicrosoftMPI_jll v10.1.4+3
  [baad4e97] + OCCT_jll v7.9.3+0
  [fe0851c0] + OpenMPI_jll v5.0.11+0
  [30392449] + Pixman_jll v0.46.4+0
⌅ [a8d0f55d] + SCOTCH_jll v6.1.3+0
⌅ [02c8fc9c] + XML2_jll v2.13.9+0
  [4f6342f7] + Xorg_libX11_jll v1.8.13+0
  [0c0b7dd1] + Xorg_libXau_jll v1.0.13+0
  [a3789734] + Xorg_libXdmcp_jll v1.1.6+0
  [1082639a] + Xorg_libXext_jll v1.3.8+0
  [d091e8ba] + Xorg_libXfixes_jll v6.0.2+0
  [2c808117] + Xorg_libXft_jll v2.3.9+0
  [d1454406] + Xorg_libXinerama_jll v1.1.7+0
  [ea2f1a96] + Xorg_libXrender_jll v0.9.12+0
  [a65dc6b1] + Xorg_libpciaccess_jll v0.19.0+0
  [c7cfdc94] + Xorg_libxcb_jll v1.17.1+0
  [c5fb5394] + Xorg_xtrans_jll v1.6.0+0
⌅ [2b3700d1] + aws_c_auth_jll v0.9.6+0
  [70f11efc] + aws_c_cal_jll v0.9.13+0
  [73048d1d] + aws_c_common_jll v0.12.6+0
  [73a04cd5] + aws_c_compression_jll v0.3.2+0
  [3254fc65] + aws_c_http_jll v0.10.13+0
  [13c41daa] + aws_c_io_jll v0.26.3+0
⌅ [bd1f34fb] + aws_c_s3_jll v0.11.5+0
  [1282aa60] + aws_c_sdkutils_jll v0.2.4+1
  [b2a88e68] + aws_checksums_jll v0.2.10+0
  [c4b69c83] + dlfcn_win32_jll v1.4.2+0
  [630162c2] + gmsh_jll v4.15.2+0
  [477f73a3] + libaec_jll v1.1.7+0
  [b53b4c65] + libpng_jll v1.6.58+0
  [9aeb927a] + mpif_jll v0.1.7+0
  [cddc5d3d] + s2n_tls_jll v1.7.3+0
  [781609d7] + GMP_jll v6.3.0+2
        Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`
        Test Successfully re-resolved
      Status `/tmp/jl_JDCkp4/Project.toml`
  [47edcb42] ADTypes v1.22.2
  [0bf59076] AdvancedHMC v0.8.6
  [4c88cf16] Aqua v0.8.16
⌅ [76274a88] Bijectors v0.15.24
  [d360d2e6] ChainRulesCore v1.26.1
  [a93c6f00] DataFrames v1.8.2
⌅ [82cc6244] DataInterpolations v8.10.0
  [a0c0ee7d] DifferentiationInterface v0.7.20
⌃ [31c24e10] Distributions v0.25.127
⌅ [366bfd00] DynamicPPL v0.40.24
  [442a2c76] FastGaussQuadrature v1.3.0
  [c061ca5d] Ferrite v1.4.1
  [4f95f4f8] FerriteGmsh v1.3.0
  [6a86dc24] FiniteDiff v2.32.0
⌅ [f6369f11] ForwardDiff v0.10.39
  [d5f06795] GaussianMarkovRandomFields v0.12.3
  [705231aa] Gmsh v0.3.1
  [19dc6840] HCubature v1.8.0
⌅ [033835bb] JLD2 v0.5.15
  [5ab0869b] KernelDensity v0.6.12
  [40e66cde] LDLFactorizations v0.10.2
  [d585094e] Latte v0.1.1
  [a90b1aa1] LibGEOS v0.9.7
⌅ [7ed4a6bd] LinearSolve v3.87.0
  [6fdf6af0] LogDensityProblems v2.2.0
  [c7f686f2] MCMCChains v7.7.0
⌅ [429524aa] Optim v1.13.3
⌅ [bac558e1] OrderedCollections v1.8.2
  [aea7be01] PrecompileTools v1.3.4
  [92933f4c] ProgressMeter v1.11.0
  [37e2e3b7] ReverseDiff v1.17.0
⌅ [f2b01f46] Roots v2.3.0
  [043bf095] SelectedInversion v0.2.1
  [9f842d2f] SparseConnectivityTracer v1.2.2
  [0a514795] SparseMatrixColorings v0.4.27
  [860ef19b] StableRNGs v1.0.4
  [10745b16] Statistics v1.11.1
  [2913bbd2] StatsBase v0.34.12
⌅ [4c63d2b9] StatsFuns v1.5.2
  [3eaba693] StatsModels v0.7.10
⌅ [fce5fe82] Turing v0.43.7
  [37e2e46d] LinearAlgebra v1.14.0
  [56ddb016] Logging v1.11.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_JDCkp4/Manifest.toml`
  [47edcb42] ADTypes v1.22.2
  [14f7f29c] AMD v0.5.3
  [621f4979] AbstractFFTs v1.5.0
  [80f14c24] AbstractMCMC v5.15.1
⌅ [7a57a42e] AbstractPPL v0.14.2
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.45
  [79e6a3ab] Adapt v4.7.0
  [0bf59076] AdvancedHMC v0.8.6
  [5b7e9947] AdvancedMH v0.8.10
  [576499cb] AdvancedPS v0.7.2
⌅ [b5ca4192] AdvancedVI v0.6.2
  [66dad0bd] AliasTables v1.1.3
  [4c88cf16] Aqua v0.8.16
  [dce04be8] ArgCheck v2.5.0
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.27.0
  [13072b0f] AxisAlgorithms v1.1.0
  [39de3d68] AxisArrays v0.4.8
  [198e06fe] BangBang v0.4.9
⌅ [76274a88] Bijectors v0.15.24
  [fa961155] CEnum v0.5.0
  [d360d2e6] ChainRulesCore v1.26.1
  [0ca39b1e] Chairmarks v1.3.1
  [9e997f8a] ChangesOfVariables v0.1.10
  [60701a23] CliqueTrees v1.19.4
  [944b1d66] CodecZlib v0.7.8
  [08986516] Collects v1.1.0
  [861a8166] Combinatorics v1.1.0
  [38540f10] CommonSolve v0.2.11
  [bbf7d656] CommonSubexpressions v0.3.1
  [34da2185] Compat v4.18.1
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.6
  [88cd18e8] ConsoleProgressMonitor v0.1.2
  [187b0558] ConstructionBase v1.6.0
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
  [a93c6f00] DataFrames v1.8.2
⌅ [82cc6244] DataInterpolations v8.10.0
  [864edb3b] DataStructures v0.19.5
  [e2d170a0] DataValueInterfaces v1.0.0
  [b429d917] DensityInterface v0.4.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.16.0
  [a0c0ee7d] DifferentiationInterface v0.7.20
  [b4f34e82] Distances v0.10.12
⌃ [31c24e10] Distributions v0.25.127
  [ffbed154] DocStringExtensions v0.9.5
⌅ [366bfd00] DynamicPPL v0.40.24
  [cad2338a] EllipticalSliceSampling v2.0.0
  [4e289a0a] EnumX v1.0.7
  [f151be2c] EnzymeCore v0.8.21
  [e2ba6199] ExprTools v0.1.10
  [55351af7] ExproniconLite v0.10.14
  [411431e0] Extents v0.1.6
  [b86e33f2] FFTA v0.3.1
  [9aa1b823] FastClosures v0.3.2
  [442a2c76] FastGaussQuadrature v1.3.0
  [c061ca5d] Ferrite v1.4.1
  [4f95f4f8] FerriteGmsh v1.3.0
  [5789e2e9] FileIO v1.19.0
  [1a297f60] FillArrays v1.16.0
⌅ [64ca27bc] FindFirstFunctions v1.8.0
  [6a86dc24] FiniteDiff v2.32.0
  [3821ddf9] FixedSizeArrays v1.3.0
⌅ [f6369f11] ForwardDiff v0.10.39
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v1.10.1
  [d9f16b24] Functors v0.5.2
  [46192b85] GPUArraysCore v0.2.0
  [a0844989] Gamma v1.1.0
  [d5f06795] GaussianMarkovRandomFields v0.12.3
  [68eda718] GeoFormatTypes v0.4.5
  [cf35fbd7] GeoInterface v1.6.1
  [705231aa] Gmsh v0.3.1
  [86223c79] Graphs v1.14.0
  [19dc6840] HCubature v1.8.0
  [076d061b] HashArrayMappedTries v0.2.0
  [34004b35] HypergeometricFunctions v0.3.29
  [d25df0c9] Inflate v0.1.5
  [22cec73e] InitialValues v0.3.1
  [842dd82b] InlineStrings v1.4.5
  [18e54dd8] IntegerMathUtils v0.1.3
  [a98d9a8b] Interpolations v0.16.3
  [8197267c] IntervalSets v0.7.14
  [3587e190] InverseFunctions v0.1.17
  [41ab1584] InvertedIndices v1.3.1
  [92d709cd] IrrationalConstants v0.2.6
  [c8e1da08] IterTools v1.10.0
  [82899510] IteratorInterfaceExtensions v1.0.0
⌅ [033835bb] JLD2 v0.5.15
  [692b3bcd] JLLWrappers v1.8.0
  [682c06a0] JSON v1.6.1
  [ae98c720] Jieko v0.2.1
  [5ab0869b] KernelDensity v0.6.12
  [ba0b0d4f] Krylov v0.10.8
  [40e66cde] LDLFactorizations v0.10.2
  [b964fa9f] LaTeXStrings v1.4.0
  [d585094e] Latte v0.1.1
⌅ [1d6d02ad] LeftChildRightSiblingTrees v0.2.1
  [a90b1aa1] LibGEOS v0.9.7
  [6f1fad26] Libtask v0.9.18
  [9c8b4983] LightXML v0.9.3
⌃ [d3d80556] LineSearches v7.5.1
  [7a12625a] LinearMaps v3.11.4
⌅ [7ed4a6bd] LinearSolve v3.87.0
  [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 v0.3.19
  [e80e1ace] MLJModelInterface v1.12.1
  [3da0fdf6] MPIPreferences v0.1.12
  [1914dd2f] MacroTools v0.5.16
  [dbb5928d] MappedArrays v0.4.3
  [e1d29d7a] Missings v1.2.0
  [dbe65cb8] MistyClosures v2.1.0
  [2e0e35c7] Moshi v0.3.10
  [46d2c3a1] MuladdMacro v0.2.6
⌅ [d41bc354] NLSolversBase v7.10.0
  [77ba4419] NaNMath v1.1.4
  [c020b1a1] NaturalSort v1.0.0
  [b8a86587] NearestNeighbors v0.4.28
  [6fe1bfb0] OffsetArrays v1.17.0
⌅ [429524aa] Optim v1.13.3
  [3bd65402] Optimisers v0.4.7
⌃ [7f7a1694] Optimization v5.4.0
⌅ [bca83a33] OptimizationBase v4.2.0
⌃ [36348300] OptimizationOptimJL v0.4.8
⌅ [bac558e1] OrderedCollections v1.8.2
  [90014a1f] PDMats v0.11.40
  [69de0a69] Parsers v2.8.6
  [2dfb63ee] PooledArrays v1.4.3
  [85a6dd25] PositiveFactorizations v0.2.4
  [d236fae5] PreallocationTools v1.3.0
  [aea7be01] PrecompileTools v1.3.4
  [21216c6a] Preferences v1.5.2
  [08abe8d2] PrettyTables v3.4.0
  [27ebfcd6] Primes v0.5.7
  [33c8b6b6] ProgressLogging v0.1.6
  [92933f4c] ProgressMeter v1.11.0
  [43287f4e] PtrArrays v1.4.0
⌃ [0c0d3e7f] PureKLU v1.0.2
  [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
  [37e2e3b7] ReverseDiff v1.17.0
  [79098fc4] Rmath v0.9.0
⌅ [f2b01f46] Roots v2.3.0
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        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...
WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead).
You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`.
To make this warning an error, and hence obtain a stack trace, use `julia --depwarn=error`.
ERROR: LoadError: MethodError: no method matching (::Latte.var"#create_progress_callback##0#create_progress_callback##1"{Latte.ProgressState, String})(; start_index::Int64, n_starts::Int64, iteration::Int64, objective::Float64, gradient_norm::Float64)
This method does not support all of the given keyword arguments (and may not support any).

Closest candidates are:
  (::Latte.var"#create_progress_callback##0#create_progress_callback##1")(Any...) got unsupported keyword arguments "start_index", "n_starts", "iteration", "objective", "gradient_norm"
   @ Latte ~/.julia/packages/Latte/6Zhta/src/inference/inla/progress.jl:108

Stacktrace:
  [1] (::Latte.var"#164#165"{Int64, Bool, Int64})(state::Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/laplace/mode_finding.jl:375
  [2] update!(tr::Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}}}, iteration::Int64, f_x::Float64, grnorm::Float64, dt::Dict{Any, Any}, store_trace::Bool, show_trace::Bool, show_every::Int64, callback::Latte.var"#164#165"{Int64, Bool, Int64}, trace_simplex::Bool)
    @ Optim ~/.julia/packages/Optim/gmigl/src/utilities/update.jl:27
  [3] update!(tr::Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}}}, iteration::Int64, f_x::Float64, grnorm::Float64, dt::Dict{Any, Any}, store_trace::Bool, show_trace::Bool, show_every::Int64, callback::Latte.var"#164#165"{Int64, Bool, Int64})
    @ Optim ~/.julia/packages/Optim/gmigl/src/utilities/update.jl:13 [inlined]
  [4] trace!(tr::Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}}}, d::NLSolversBase.OnceDifferentiable{Float64, Vector{Float64}, Vector{Float64}}, state::Optim.BFGSState{Vector{Float64}, Matrix{Float64}, Float64, Vector{Float64}}, iteration::Int64, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}}, curr_time::Float64)
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/solvers/first_order/bfgs.jl:201
  [5] optimize(d::NLSolversBase.OnceDifferentiable{Float64, Vector{Float64}, Vector{Float64}}, initial_x::Vector{Float64}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}}, state::Optim.BFGSState{Vector{Float64}, Matrix{Float64}, Float64, Vector{Float64}})
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/optimize/optimize.jl:61
  [6] optimize(d::NLSolversBase.OnceDifferentiable{Float64, Vector{Float64}, Vector{Float64}}, initial_x::Vector{Float64}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}})
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/optimize/optimize.jl:43 [inlined]
  [7] optimize(f::Latte.var"#162#163"{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Vector{Latte.WorkingHyperparameters}, Vector{Float64}, Bool, Bool, Base.RefValue{Union{Nothing, Vector{Float64}}}, Base.RefValue{Vector{Float64}}}, g::Latte.var"#gradient!#_run_optimization##1"{Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.var"#objective_clean#_run_optimization##0"{Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Base.RefValue{Union{Nothing, Vector{Float64}}}, Bool}}, initial_x::Vector{Float64}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}}; inplace::Bool, autodiff::Symbol)
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/optimize/interface.jl:301 [inlined]
  [8] optimize(f::Latte.var"#162#163"{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Vector{Latte.WorkingHyperparameters}, Vector{Float64}, Bool, Bool, Base.RefValue{Union{Nothing, Vector{Float64}}}, Base.RefValue{Vector{Float64}}}, g::Latte.var"#gradient!#_run_optimization##1"{Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.var"#objective_clean#_run_optimization##0"{Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Base.RefValue{Union{Nothing, Vector{Float64}}}, Bool}}, initial_x::Vector{Float64}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}})
    @ Optim ~/.julia/packages/Optim/gmigl/src/multivariate/optimize/interface.jl:289 [inlined]
  [9] _run_optimization(strategy::Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, objective::Latte.var"#162#163"{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Vector{Latte.WorkingHyperparameters}, Vector{Float64}, Bool, Bool, Base.RefValue{Union{Nothing, Vector{Float64}}}, Base.RefValue{Vector{Float64}}}, model::Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, y::GaussianMarkovRandomFields.PoissonObservations, spec::Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, θ_init::Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}, ws::GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, options::Optim.Options{Float64, Latte.var"#164#165"{Int64, Bool, Int64}}, last_mode::Base.RefValue{Union{Nothing, Vector{Float64}}}, do_warm::Bool)
    @ Latte ~/.julia/packages/Latte/6Zhta/src/laplace/mode_finding.jl:492 [inlined]
 [10] (::Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}})(::Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}, ws::GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/laplace/mode_finding.jl:396
 [11] (::Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}})(x::Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/parallel/executors.jl:126 [inlined]
 [12] iterate(::Base.Generator{Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}})
    @ Base generator.jl:49 [inlined]
 [13] _collect(c::Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, itr::Base.Generator{Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, ::Base.EltypeUnknown, isz::Base.HasShape{1})
    @ Base array.jl:853
 [14] collect_similar(cont::Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, itr::Base.Generator{Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}})
    @ Base array.jl:768 [inlined]
 [15] map(f::Latte.var"#22#23"{GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}, A::Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}})
    @ Base abstractarray.jl:3468 [inlined]
 [16] (::Latte.var"#20#21"{Nothing, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}, Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}})(ws::GaussianMarkovRandomFields.GMRFWorkspace{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/parallel/executors.jl:126 [inlined]
 [17] with_workspace(f::Latte.var"#20#21"{Nothing, Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}, Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}}, pool::GaussianMarkovRandomFields.WorkspacePool{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}})
    @ GaussianMarkovRandomFields ~/.julia/packages/GaussianMarkovRandomFields/I3Mdk/src/workspace/workspace_pool.jl:110
 [18] pmap_executor(f::Latte.var"#_one_start#161"{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, Int64, Bool, Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, GaussianMarkovRandomFields.PoissonObservations, Bool, Nothing, Int64, Bool, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}, xs::Vector{Tuple{Int64, Latte.WorkingHyperparameters{Float64, Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}}}}, ::Latte.SequentialExecutor, pool::GaussianMarkovRandomFields.WorkspacePool{Float64, GaussianMarkovRandomFields.CHOLMODBackend{Float64}}; on_complete::Nothing)
    @ Latte ~/.julia/packages/Latte/6Zhta/src/parallel/executors.jl:125
 [19] find_hyperparameter_mode(model::Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, y::GaussianMarkovRandomFields.PoissonObservations; method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, iterations::Int64, collect_points::Bool, progress_callback::Latte.var"#create_progress_callback##0#create_progress_callback##1"{Latte.ProgressState, String}, diff_strategy::Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}}, mode_init::Latte.PriorModeStart, latent_init::Latte.ZeroLatentStart, executor::Latte.SequentialExecutor, warm_start::Nothing)
    @ Latte ~/.julia/packages/Latte/6Zhta/src/laplace/mode_finding.jl:420
 [20] inla(model::Latte.LatentGaussianModel{Latte.HyperparameterSpec{@NamedTuple{τ::Latte.Hyperparameter{Base.Fix1{typeof(broadcast), typeof(log)}, :natural}}, @NamedTuple{}}, Latte.AugmentedLatentModel{GaussianMarkovRandomFields.IIDModel{LinearSolve.DiagonalFactorization, Nothing, Nothing}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, LinearSolve.CHOLMODFactorization{Nothing}}, GaussianMarkovRandomFields.ExponentialFamily{Distributions.Poisson, GaussianMarkovRandomFields.LogLink, UnitRange{Int64}, Nothing}}, y::Vector{Int64}; latent_marginalization_method::Latte.SimplifiedLaplace, hyperparameter_marginalization_method::Latte.AutoHyperparameterMarginal, latent_indices::Nothing, exploration_strategy::Latte.GridExplorationStrategy, mode_method::Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.BackTracking{Float64, Int64}, Nothing, Nothing, Optim.Flat}, mode_iterations::Int64, mode_init::Latte.PriorModeStart, latent_init::Latte.ZeroLatentStart, mode_diagnostic::Symbol, mode_diagnostic_tol::Float64, progress::Bool, accumulators::Tuple{}, executor::Latte.SequentialExecutor, diff_strategy::Latte.ADStrategy{ADTypes.AutoForwardDiff{nothing, Nothing}})
    @ Latte ~/.julia/packages/Latte/6Zhta/src/inference/inla/inference.jl:123
 [21] macro expansion
    @ ~/.julia/packages/Latte/6Zhta/src/precompile_workloads.jl:102 [inlined]
 [22] macro expansion
    @ ~/.julia/packages/PrecompileTools/QUxvR/src/workloads.jl:70 [inlined]
 [23] macro expansion
    @ ~/.julia/packages/Latte/6Zhta/src/precompile_workloads.jl:97 [inlined]
 [24] macro expansion
    @ ~/.julia/packages/PrecompileTools/QUxvR/src/workloads.jl:118 [inlined]
 [25] top-level scope
    @ ~/.julia/packages/Latte/6Zhta/src/precompile_workloads.jl:115
 [26] include(mapexpr::Function, mod::Module, _path::String)
    @ Base Base.jl:326
 [27] top-level scope
    @ ~/.julia/packages/Latte/6Zhta/src/Latte.jl:178
 [28] include(mod::Module, _path::String)
    @ Base Base.jl:325
 [29] 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:3359
 [30] top-level scope
    @ stdin:5
 [31] eval(m::Module, e::Any)
    @ Core boot.jl:545
 [32] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String)
    @ Base loading.jl:3186
 [33] include_string(m::Module, txt::String, fname::String)
    @ Base loading.jl:3196 [inlined]
 [34] exec_options(opts::Base.JLOptions)
    @ Base client.jl:353
 [35] _start()
    @ Base client.jl:596
in expression starting at /home/pkgeval/.julia/packages/Latte/6Zhta/src/precompile_workloads.jl:30
in expression starting at /home/pkgeval/.julia/packages/Latte/6Zhta/src/Latte.jl:1
in expression starting at stdin:5
  1 dependency had output during precompilation:
┌ Latte
│  [Output was shown above]
└  
ERROR: LoadError: The following 1 package failed to precompile:

Latte 
Failed to precompile Latte [d585094e-6273-42a7-8500-34710a148fdc] to "/home/pkgeval/.julia/compiled/v1.14/Latte/jl_FF8jkq" (ProcessExited(1)).

in expression starting at /home/pkgeval/.julia/packages/Latte/6Zhta/test/runtests.jl:1

Testing failed after 145.13s

ERROR: LoadError: Package Latte errored during testing
Stacktrace:
  [1] pkgerror(msg::String)
    @ Pkg.Types /opt/julia/share/julia/stdlib/v1.14/Pkg/src/Types.jl:68
  [2] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool)
    @ Pkg.Operations /opt/julia/share/julia/stdlib/v1.14/Pkg/src/Operations.jl:3247
  [3] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool, kwargs::@Kwargs{io::IOContext{IO}})
    @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:587
  [4] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd})
    @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:172
  [5] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd})
    @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:160
  [6] test(pkg::String; kwargs::@Kwargs{julia_args::Cmd})
    @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:159 [inlined]
  [7] top-level scope
    @ /PkgEval.jl/scripts/evaluate.jl:223
  [8] include(mod::Module, _path::String)
    @ Base Base.jl:325
  [9] exec_options(opts::Base.JLOptions)
    @ Base client.jl:355
 [10] _start()
    @ Base client.jl:596
in expression starting at /PkgEval.jl/scripts/evaluate.jl:214

PkgEval failed after 683.87s: package fails to precompile