Package evaluation to test DiffEqBayes on Julia 1.13.0-DEV.1296 (e8025198af*) started at 2025-10-13T02:20:20.494 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 8.93s ################################################################################ # Installation # Installing DiffEqBayes... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [ebbdde9d] + DiffEqBayes v3.9.0 Updating `~/.julia/environments/v1.13/Manifest.toml` [47edcb42] + ADTypes v1.18.0 [621f4979] + AbstractFFTs v1.5.0 [80f14c24] + AbstractMCMC v5.8.2 ⌅ [7a57a42e] + AbstractPPL v0.12.0 [1520ce14] + AbstractTrees v0.4.5 [7d9f7c33] + Accessors v0.1.42 [79e6a3ab] + Adapt v4.4.0 [0bf59076] + AdvancedHMC v0.8.2 [5b7e9947] + AdvancedMH v0.8.8 [576499cb] + AdvancedPS v0.7.0 [b5ca4192] + AdvancedVI v0.4.1 [66dad0bd] + AliasTables v1.1.3 [dce04be8] + ArgCheck v2.5.0 [ec485272] + ArnoldiMethod v0.4.0 [4fba245c] + ArrayInterface v7.20.0 [4c555306] + ArrayLayouts v1.12.0 [13072b0f] + AxisAlgorithms v1.1.0 [39de3d68] + AxisArrays v0.4.8 [198e06fe] + BangBang v0.4.4 [9718e550] + Baselet v0.1.1 [e2ed5e7c] + Bijections v0.2.2 [76274a88] + Bijectors v0.15.10 [62783981] + BitTwiddlingConvenienceFunctions v0.1.6 [8e7c35d0] + BlockArrays v1.7.2 [70df07ce] + BracketingNonlinearSolve v1.5.0 [2a0fbf3d] + CPUSummary v0.2.7 [336ed68f] + CSV v0.10.15 [082447d4] + ChainRules v1.72.6 [d360d2e6] + ChainRulesCore v1.26.0 [0ca39b1e] + Chairmarks v1.3.1 [9e997f8a] + ChangesOfVariables v0.1.10 [fb6a15b2] + CloseOpenIntervals v0.1.13 [944b1d66] + CodecZlib v0.7.8 ⌅ [861a8166] + Combinatorics v1.0.2 [a80b9123] + CommonMark v0.9.1 [38540f10] + CommonSolve v0.2.4 [bbf7d656] + CommonSubexpressions v0.3.1 [f70d9fcc] + CommonWorldInvalidations v1.0.0 [34da2185] + Compat v4.18.1 [5224ae11] + CompatHelperLocal v0.1.27 [b152e2b5] + CompositeTypes v0.1.4 [a33af91c] + CompositionsBase v0.1.2 [2569d6c7] + ConcreteStructs v0.2.3 [88cd18e8] + ConsoleProgressMonitor v0.1.2 [187b0558] + ConstructionBase v1.6.0 [adafc99b] + CpuId v0.3.1 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.8.0 [864edb3b] + DataStructures v0.19.1 [e2d170a0] + DataValueInterfaces v1.0.0 [244e2a9f] + DefineSingletons v0.1.2 [8bb1440f] + DelimitedFiles v1.9.1 [b429d917] + DensityInterface v0.4.0 [2b5f629d] + DiffEqBase v6.190.2 [ebbdde9d] + DiffEqBayes v3.9.0 [459566f4] + DiffEqCallbacks v4.10.1 [77a26b50] + DiffEqNoiseProcess v5.24.1 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [a0c0ee7d] + DifferentiationInterface v0.7.9 [8d63f2c5] + DispatchDoctor v0.4.26 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.122 [ced4e74d] + DistributionsAD v0.6.58 [ffbed154] + DocStringExtensions v0.9.5 [5b8099bc] + DomainSets v0.7.16 [bbc10e6e] + DynamicHMC v3.5.1 ⌅ [366bfd00] + DynamicPPL v0.36.15 [7c1d4256] + DynamicPolynomials v0.6.4 [06fc5a27] + DynamicQuantities v1.10.0 [cad2338a] + EllipticalSliceSampling v2.0.0 [4e289a0a] + EnumX v1.0.5 [f151be2c] + EnzymeCore v0.8.14 [e2ba6199] + ExprTools v0.1.10 [55351af7] + ExproniconLite v0.10.14 [7a1cc6ca] + FFTW v1.10.0 [7034ab61] + FastBroadcast v0.3.5 [9aa1b823] + FastClosures v0.3.2 [a4df4552] + FastPower v1.1.3 [48062228] + FilePathsBase v0.9.24 [1a297f60] + FillArrays v1.14.0 [64ca27bc] + FindFirstFunctions v1.4.2 [6a86dc24] + FiniteDiff v2.28.1 [1fa38f19] + Format v1.3.7 [f6369f11] + ForwardDiff v1.2.1 [069b7b12] + FunctionWrappers v1.1.3 [77dc65aa] + FunctionWrappersWrappers v0.1.3 [d9f16b24] + Functors v0.5.2 [46192b85] + GPUArraysCore v0.2.0 [c27321d9] + Glob v1.3.1 [86223c79] + Graphs v1.13.1 [34004b35] + HypergeometricFunctions v0.3.28 [615f187c] + IfElse v0.1.1 [3263718b] + ImplicitDiscreteSolve v1.2.0 [d25df0c9] + Inflate v0.1.5 [22cec73e] + InitialValues v0.3.1 [842dd82b] + InlineStrings v1.4.5 [18e54dd8] + IntegerMathUtils v0.1.3 [a98d9a8b] + Interpolations v0.16.2 [8197267c] + IntervalSets v0.7.11 [3587e190] + InverseFunctions v0.1.17 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.4 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.1 ⌅ [682c06a0] + JSON v0.21.4 [ae98c720] + Jieko v0.2.1 [98e50ef6] + JuliaFormatter v2.1.6 ⌅ [70703baa] + JuliaSyntax v0.4.10 [ccbc3e58] + JumpProcesses v9.19.1 [5ab0869b] + KernelDensity v0.6.10 [5be7bae1] + LBFGSB v0.4.1 [b964fa9f] + LaTeXStrings v1.4.0 [2ee39098] + LabelledArrays v1.16.1 [23fbe1c1] + Latexify v0.16.10 [10f19ff3] + LayoutPointers v0.1.17 [1fad7336] + LazyStack v0.1.3 [1d6d02ad] + LeftChildRightSiblingTrees v0.2.1 [6f1fad26] + Libtask v0.9.5 [87fe0de2] + LineSearch v0.1.4 [d3d80556] + LineSearches v7.4.0 [6fdf6af0] + LogDensityProblems v2.1.2 [996a588d] + LogDensityProblemsAD v1.13.1 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [c7f686f2] + MCMCChains v7.5.0 [be115224] + MCMCDiagnosticTools v0.3.15 [e80e1ace] + MLJModelInterface v1.12.0 [d8e11817] + MLStyle v0.4.17 [1914dd2f] + MacroTools v0.5.16 [d125e4d3] + ManualMemory v0.1.8 [dbb5928d] + MappedArrays v0.4.2 [bb5d69b7] + MaybeInplace v0.1.4 [128add7d] + MicroCollections v0.2.0 [e1d29d7a] + Missings v1.2.0 [dbe65cb8] + MistyClosures v2.1.0 [961ee093] + ModelingToolkit v10.25.0 [2e0e35c7] + Moshi v0.3.7 [46d2c3a1] + MuladdMacro v0.2.4 [102ac46a] + MultivariatePolynomials v0.5.13 [d8a4904e] + MutableArithmetics v1.6.6 [d41bc354] + NLSolversBase v7.10.0 [77ba4419] + NaNMath v1.1.3 [86f7a689] + NamedArrays v0.10.5 [d9ec5142] + NamedTupleTools v0.14.3 [c020b1a1] + NaturalSort v1.0.0 [be0214bd] + NonlinearSolveBase v2.0.0 [6fe1bfb0] + OffsetArrays v1.17.0 [429524aa] + Optim v1.13.2 [3bd65402] + Optimisers v0.4.6 [7f7a1694] + Optimization v4.8.0 ⌅ [bca83a33] + OptimizationBase v2.12.0 ⌃ [36348300] + OptimizationOptimJL v0.4.5 [bac558e1] + OrderedCollections v1.8.1 [bbf590c4] + OrdinaryDiffEqCore v1.36.0 [90014a1f] + PDMats v0.11.35 [65ce6f38] + PackageExtensionCompat v1.0.2 [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.3 [e409e4f3] + PoissonRandom v0.4.7 [f517fe37] + Polyester v0.7.18 [1d0040c9] + PolyesterWeave v0.2.2 [2dfb63ee] + PooledArrays v1.4.3 [85a6dd25] + PositiveFactorizations v0.2.4 [d236fae5] + PreallocationTools v0.4.34 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.0 ⌅ [08abe8d2] + PrettyTables v2.4.0 [27ebfcd6] + Primes v0.5.7 [33c8b6b6] + ProgressLogging v0.1.5 [92933f4c] + ProgressMeter v1.11.0 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [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 v3.37.1 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [ae5879a3] + ResettableStacks v1.1.1 [79098fc4] + Rmath v0.8.0 [f2b01f46] + Roots v2.2.10 [7e49a35a] + RuntimeGeneratedFunctions v0.5.15 [9dfe8606] + SCCNonlinearSolve v1.6.0 [94e857df] + SIMDTypes v0.1.0 ⌅ [26aad666] + SSMProblems v0.5.2 [0bca4576] + SciMLBase v2.120.0 [19f34311] + SciMLJacobianOperators v0.1.11 [c0aeaf25] + SciMLOperators v1.9.0 [431bcebd] + SciMLPublic v1.0.0 [53ae85a6] + SciMLStructures v1.7.0 [30f210dd] + ScientificTypesBase v3.0.0 [91c51154] + SentinelArrays v1.4.8 [efcf1570] + Setfield v1.1.2 [727e6d20] + SimpleNonlinearSolve v2.9.0 [699a6c99] + SimpleTraits v0.9.5 [ce78b400] + SimpleUnPack v1.1.0 [a2af1166] + SortingAlgorithms v1.2.2 [9f842d2f] + SparseConnectivityTracer v1.1.1 [dc90abb0] + SparseInverseSubset v0.1.2 [0a514795] + SparseMatrixColorings v0.4.21 [276daf66] + SpecialFunctions v2.6.1 [171d559e] + SplittablesBase v0.1.15 [d0ee94f6] + StanBase v4.12.2 ⌃ [c1514b29] + StanSample v7.1.1 [aedffcd0] + Static v1.3.0 [0d7ed370] + StaticArrayInterface v1.8.0 [90137ffa] + StaticArrays v1.9.15 [1e83bf80] + StaticArraysCore v1.4.3 [64bff920] + StatisticalTraits v3.5.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.6 [4c63d2b9] + StatsFuns v1.5.0 [7792a7ef] + StrideArraysCore v0.5.8 [5e0ebb24] + Strided v2.3.2 [4db3bf67] + StridedViews v0.4.1 [892a3eda] + StringManipulation v0.4.1 [09ab397b] + StructArrays v0.7.1 ⌃ [2efcf032] + SymbolicIndexingInterface v0.3.44 ⌃ [19f23fe9] + SymbolicLimits v0.2.3 ⌅ [d1185830] + SymbolicUtils v3.32.0 [0c5d862f] + Symbolics v6.55.0 [ab02a1b2] + TableOperations v1.2.0 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [ed4db957] + TaskLocalValues v0.1.3 [02d47bb6] + TensorCast v0.4.9 [8ea1fca8] + TermInterface v2.0.0 [5d786b92] + TerminalLoggers v0.1.7 [1c621080] + TestItems v1.0.0 [8290d209] + ThreadingUtilities v0.5.5 [a759f4b9] + TimerOutputs v0.5.29 [3bb67fe8] + TranscodingStreams v0.11.3 [28d57a85] + Transducers v0.4.85 [84d833dd] + TransformVariables v0.8.17 [f9bc47f6] + TransformedLogDensities v1.1.1 [24ddb15e] + TransmuteDims v0.1.17 [410a4b4d] + Tricks v0.1.12 [781d530d] + TruncatedStacktraces v1.4.0 [9d95972d] + TupleTools v1.6.0 ⌅ [fce5fe82] + Turing v0.39.10 [5c2747f8] + URIs v1.6.1 [3a884ed6] + UnPack v1.0.2 [1986cc42] + Unitful v1.25.0 [a7c27f48] + Unityper v0.1.6 [ea10d353] + WeakRefStrings v1.4.2 [efce3f68] + WoodburyMatrices v1.0.0 [76eceee3] + WorkerUtilities v1.6.1 [700de1a5] + ZygoteRules v0.2.7 [f5851436] + FFTW_jll v3.3.11+0 [61579ee1] + Ghostscript_jll v9.55.1+0 [1d5cc7b8] + IntelOpenMP_jll v2025.2.0+0 [aacddb02] + JpegTurbo_jll v3.1.3+0 [81d17ec3] + L_BFGS_B_jll v3.0.1+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 v2022.0.0+0 [0dad84c5] + ArgTools v1.1.2 [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 v1.12.0 [4af54fe1] + LazyArtifacts v1.11.0 [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 v1.11.0 [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 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.13.0 [de0858da] + Printf v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [1a1011a3] + SharedArrays v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.11.0 [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 v8.16.0+0 [e37daf67] + LibGit2_jll v1.9.1+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.9.9 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.4+0 [efcefdf7] + PCRE2_jll v10.46.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.67.1+0 [3f19e933] + p7zip_jll v17.6.0+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 8.74s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 1863.58s ################################################################################ # Testing # Testing DiffEqBayes Status `/tmp/jl_wcoevy/Project.toml` [2b5f629d] DiffEqBase v6.190.2 [ebbdde9d] DiffEqBayes v3.9.0 [163ba53b] DiffResults v1.1.0 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.122 [ffbed154] DocStringExtensions v0.9.5 [bbc10e6e] DynamicHMC v3.5.1 [f6369f11] ForwardDiff v1.2.1 [2ee39098] LabelledArrays v1.16.1 [996a588d] LogDensityProblemsAD v1.13.1 [1914dd2f] MacroTools v0.5.16 [e1d29d7a] Missings v1.2.0 [961ee093] ModelingToolkit v10.25.0 [429524aa] Optim v1.13.2 [1dea7af3] OrdinaryDiffEq v6.102.1 [90014a1f] PDMats v0.11.35 [65888b18] ParameterizedFunctions v5.19.0 [d96e819e] Parameters v0.12.3 [731186ca] RecursiveArrayTools v3.37.1 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [1bc83da4] SafeTestsets v0.1.0 [53ae85a6] SciMLStructures v1.7.0 ⌃ [c1514b29] StanSample v7.1.1 [2913bbd2] StatsBase v0.34.6 [9672c7b4] SteadyStateDiffEq v2.7.0 [09ab397b] StructArrays v0.7.1 [84d833dd] TransformVariables v0.8.17 [f9bc47f6] TransformedLogDensities v1.1.1 ⌅ [fce5fe82] Turing v0.39.10 [8ba89e20] Distributed v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [44cfe95a] Pkg v1.13.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_wcoevy/Manifest.toml` [47edcb42] ADTypes v1.18.0 [621f4979] AbstractFFTs v1.5.0 [80f14c24] AbstractMCMC v5.8.2 ⌅ [7a57a42e] AbstractPPL v0.12.0 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.42 [79e6a3ab] Adapt v4.4.0 [0bf59076] AdvancedHMC v0.8.2 [5b7e9947] AdvancedMH v0.8.8 [576499cb] AdvancedPS v0.7.0 [b5ca4192] AdvancedVI v0.4.1 [66dad0bd] AliasTables v1.1.3 [dce04be8] ArgCheck v2.5.0 [ec485272] ArnoldiMethod v0.4.0 [4fba245c] ArrayInterface v7.20.0 [4c555306] ArrayLayouts v1.12.0 [13072b0f] AxisAlgorithms v1.1.0 [39de3d68] AxisArrays v0.4.8 [198e06fe] BangBang v0.4.4 [9718e550] Baselet v0.1.1 [e2ed5e7c] Bijections v0.2.2 [76274a88] Bijectors v0.15.10 [62783981] BitTwiddlingConvenienceFunctions v0.1.6 [8e7c35d0] BlockArrays v1.7.2 [70df07ce] BracketingNonlinearSolve v1.5.0 [2a0fbf3d] CPUSummary v0.2.7 [336ed68f] CSV v0.10.15 [082447d4] ChainRules v1.72.6 [d360d2e6] ChainRulesCore v1.26.0 [0ca39b1e] Chairmarks v1.3.1 [9e997f8a] ChangesOfVariables v0.1.10 [fb6a15b2] CloseOpenIntervals v0.1.13 [944b1d66] CodecZlib v0.7.8 ⌅ [861a8166] Combinatorics v1.0.2 [a80b9123] CommonMark v0.9.1 [38540f10] CommonSolve v0.2.4 [bbf7d656] CommonSubexpressions v0.3.1 [f70d9fcc] CommonWorldInvalidations v1.0.0 [34da2185] Compat v4.18.1 [5224ae11] CompatHelperLocal v0.1.27 [b152e2b5] CompositeTypes v0.1.4 [a33af91c] CompositionsBase v0.1.2 [2569d6c7] ConcreteStructs v0.2.3 [88cd18e8] ConsoleProgressMonitor v0.1.2 [187b0558] ConstructionBase v1.6.0 [adafc99b] CpuId v0.3.1 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.0 [864edb3b] DataStructures v0.19.1 [e2d170a0] DataValueInterfaces v1.0.0 [244e2a9f] DefineSingletons v0.1.2 [8bb1440f] DelimitedFiles v1.9.1 [b429d917] DensityInterface v0.4.0 [2b5f629d] DiffEqBase v6.190.2 [ebbdde9d] DiffEqBayes v3.9.0 [459566f4] DiffEqCallbacks v4.10.1 [77a26b50] DiffEqNoiseProcess v5.24.1 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [a0c0ee7d] DifferentiationInterface v0.7.9 [8d63f2c5] DispatchDoctor v0.4.26 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.122 [ced4e74d] DistributionsAD v0.6.58 [ffbed154] DocStringExtensions v0.9.5 [5b8099bc] DomainSets v0.7.16 [bbc10e6e] DynamicHMC v3.5.1 ⌅ [366bfd00] DynamicPPL v0.36.15 [7c1d4256] DynamicPolynomials v0.6.4 [06fc5a27] DynamicQuantities v1.10.0 [cad2338a] EllipticalSliceSampling v2.0.0 [4e289a0a] EnumX v1.0.5 [f151be2c] EnzymeCore v0.8.14 [d4d017d3] ExponentialUtilities v1.27.0 [e2ba6199] ExprTools v0.1.10 [55351af7] ExproniconLite v0.10.14 [7a1cc6ca] FFTW v1.10.0 [7034ab61] FastBroadcast v0.3.5 [9aa1b823] FastClosures v0.3.2 [442a2c76] FastGaussQuadrature v1.0.2 [a4df4552] FastPower 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[83775a58] Zlib_jll v1.3.1+2 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.67.1+0 [3f19e933] p7zip_jll v17.6.0+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... ┌ Warning: Environment variable CMDSTAN_HOME not set. Use set_cmdstan_home!. └ @ StanBase ~/.julia/packages/StanBase/IgV1g/src/StanBase.jl:52 ┌ Warning: Independent variable t should be defined with @independent_variables t. └ @ ModelingToolkit ~/.julia/packages/ModelingToolkit/IdXTK/src/utils.jl:121 ┌ Info: found initial stepsize └ ϵ = 0.025 ┌ Info: Starting MCMC │ total_steps = 75 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00025 │ estimated_seconds_left = 0.019 └ ϵ = 0.025 ┌ Info: Starting MCMC │ total_steps = 25 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00011 │ estimated_seconds_left = 0.0025 └ ϵ = 0.000654 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.00027759603906948616, 0.09882982028436807, 0.0865415677260979] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.028 │ estimated_seconds_left = 1.4 └ ϵ = 0.000203 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0002369211344124613, 0.28889849501327647, 0.20925269573679312] ┌ Info: Starting MCMC │ total_steps = 100 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00022 │ estimated_seconds_left = 0.022 └ ϵ = 0.42 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0001939484146690694, 0.3478515726970992, 0.22928451999232494] ┌ Info: Starting MCMC │ total_steps = 200 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00019 │ estimated_seconds_left = 0.037 └ ϵ = 0.564 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00035 │ estimated_seconds_left = 0.034 └ ϵ = 0.508 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.00018551991262898346, 0.2835214020191335, 0.22536449834113909] ┌ Info: Starting MCMC │ total_steps = 400 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00028 │ estimated_seconds_left = 0.11 └ ϵ = 0.602 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00034 │ estimated_seconds_left = 0.1 └ ϵ = 0.877 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.00029 │ estimated_seconds_left = 0.057 └ ϵ = 1.14 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.00063 │ estimated_seconds_left = 0.062 └ ϵ = 0.803 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.00018672515647743967, 0.26853200528886556, 0.2631183630134361] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 8.8e-5 │ estimated_seconds_left = 0.0043 └ ϵ = 0.804 ┌ Info: Starting MCMC └ total_steps = 1000 ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00025 └ estimated_seconds_left = 0.25 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00049 └ estimated_seconds_left = 0.44 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.00032 └ estimated_seconds_left = 0.25 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.00032 └ estimated_seconds_left = 0.22 ┌ Info: MCMC progress │ step = 401 │ seconds_per_step = 0.00028 └ estimated_seconds_left = 0.17 ┌ Info: MCMC progress │ step = 501 │ seconds_per_step = 0.00031 └ estimated_seconds_left = 0.15 ┌ Info: MCMC progress │ step = 601 │ seconds_per_step = 0.00031 └ estimated_seconds_left = 0.12 ┌ Info: MCMC progress │ step = 701 │ seconds_per_step = 0.00032 └ estimated_seconds_left = 0.097 ┌ Info: MCMC progress │ step = 801 │ seconds_per_step = 0.0003 └ estimated_seconds_left = 0.06 ┌ Info: MCMC progress │ step = 901 │ seconds_per_step = 0.0003 └ estimated_seconds_left = 0.03 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Info: found initial stepsize └ ϵ = 0.0125 ┌ Info: Starting MCMC │ total_steps = 75 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 4.0e-5 │ estimated_seconds_left = 0.0029 └ ϵ = 0.0125 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Info: Starting MCMC │ total_steps = 25 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.012 │ estimated_seconds_left = 0.28 └ ϵ = 0.000285 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0011035522985069386, 0.0033244249009640424, 0.0003872576938283311, 0.24600942497875752, 0.1248253369590345] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.025 │ estimated_seconds_left = 1.2 └ ϵ = 0.000132 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0011742968409230686, 0.0030097327617909864, 0.0003694699454281459, 0.2916698489693679, 0.30287505643268525] ┌ Info: Starting MCMC │ total_steps = 100 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00018 │ estimated_seconds_left = 0.017 └ ϵ = 0.205 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0012353329975623379, 0.0029974461937909117, 0.0004492012470425823, 0.2594562296799282, 0.2549383127628679] ┌ Info: Starting MCMC │ total_steps = 200 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.0004 │ estimated_seconds_left = 0.08 └ ϵ = 0.214 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.0011 │ estimated_seconds_left = 0.11 └ ϵ = 0.251 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0012500919119239917, 0.0032050378814448325, 0.0004429870699644311, 0.26055487179772396, 0.2320840628479964] ┌ Info: Starting MCMC │ total_steps = 400 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00031 │ estimated_seconds_left = 0.12 └ ϵ = 0.226 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.0014 │ estimated_seconds_left = 0.41 └ ϵ = 0.0798 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.00071 │ estimated_seconds_left = 0.14 └ ϵ = 0.279 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.00059 │ estimated_seconds_left = 0.058 └ ϵ = 0.256 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0014015968758512626, 0.002975287625873234, 0.0004604844781904932, 0.26038190733674155, 0.2552190026926274] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00037 │ estimated_seconds_left = 0.018 └ ϵ = 0.268 ┌ Info: Starting MCMC └ total_steps = 1000 ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00041 └ estimated_seconds_left = 0.41 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00096 └ estimated_seconds_left = 0.86 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.0012 └ estimated_seconds_left = 0.92 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.0011 └ estimated_seconds_left = 0.78 ┌ Info: MCMC progress │ step = 401 │ seconds_per_step = 0.00085 └ estimated_seconds_left = 0.51 ┌ Info: MCMC progress │ step = 501 │ seconds_per_step = 0.0013 └ estimated_seconds_left = 0.65 ┌ Info: MCMC progress │ step = 601 │ seconds_per_step = 0.0014 └ estimated_seconds_left = 0.55 ┌ Info: MCMC progress │ step = 701 │ seconds_per_step = 0.0011 └ estimated_seconds_left = 0.32 ┌ Info: MCMC progress │ step = 801 │ seconds_per_step = 0.0014 └ estimated_seconds_left = 0.27 ┌ Info: MCMC progress │ step = 901 │ seconds_per_step = 0.0013 └ estimated_seconds_left = 0.13 ┌ Info: found initial stepsize └ ϵ = 0.2 ┌ Info: Starting MCMC │ total_steps = 75 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.0002 │ estimated_seconds_left = 0.015 └ ϵ = 0.2 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Info: Starting MCMC │ total_steps = 25 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00022 │ estimated_seconds_left = 0.0054 └ ϵ = 0.00447 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0012014229745162931, 0.23641767724597812] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.031 │ estimated_seconds_left = 1.5 └ ϵ = 0.00167 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.00022958664973856294, 0.4300108383478044] ┌ Info: Starting MCMC │ total_steps = 100 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00072 │ estimated_seconds_left = 0.071 └ ϵ = 0.16 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.00023051874741359868, 0.23737632765699423] ┌ Info: Starting MCMC │ total_steps = 200 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 4.2e-5 │ estimated_seconds_left = 0.0084 └ ϵ = 0.504 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00043 │ estimated_seconds_left = 0.042 └ ϵ = 0.598 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.00025102075697334904, 0.27708023432256207] ┌ Info: Starting MCMC │ total_steps = 400 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 4.0e-5 │ estimated_seconds_left = 0.016 └ ϵ = 0.826 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00033 │ estimated_seconds_left = 0.1 └ ϵ = 1.14 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.00024 │ estimated_seconds_left = 0.047 └ ϵ = 0.495 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.00021 │ estimated_seconds_left = 0.021 └ ϵ = 0.586 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.00021889995585678076, 0.26237381386434294] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.0001 │ estimated_seconds_left = 0.005 └ ϵ = 0.778 ┌ Info: Starting MCMC └ total_steps = 1000 ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00028 └ estimated_seconds_left = 0.28 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00032 └ estimated_seconds_left = 0.29 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.00029 └ estimated_seconds_left = 0.23 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.00029 └ estimated_seconds_left = 0.2 ┌ Info: MCMC progress │ step = 401 │ seconds_per_step = 0.00032 └ estimated_seconds_left = 0.19 ┌ Info: MCMC progress │ step = 501 │ seconds_per_step = 0.00033 └ estimated_seconds_left = 0.16 ┌ Info: MCMC progress │ step = 601 │ seconds_per_step = 0.00033 └ estimated_seconds_left = 0.13 ┌ Info: MCMC progress │ step = 701 │ seconds_per_step = 0.0003 └ estimated_seconds_left = 0.089 ┌ Info: MCMC progress │ step = 801 │ seconds_per_step = 0.00033 └ estimated_seconds_left = 0.065 ┌ Info: MCMC progress │ step = 901 │ seconds_per_step = 0.00031 └ estimated_seconds_left = 0.03 ┌ Warning: First function call produced NaNs. Exiting. Double check that none of the initial conditions, parameters, or timespan values are NaN. └ @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/GMkz9/src/initdt.jl:132 ┌ Warning: At t=0.0, dt was forced below floating point epsilon 5.0e-324, and step error estimate = NaN. Aborting. There is either an error in your model specification or the true solution is unstable (or the true solution can not be represented in the precision of ForwardDiff.Dual{ForwardDiff.Tag{Base.Fix1{typeof(LogDensityProblems.logdensity), TransformedLogDensities.TransformedLogDensity{TransformVariables.TransformTuple{@NamedTuple{parameters::TransformVariables.ArrayTransformation{TransformVariables.TVExp, 1}, σ::TransformVariables.ArrayTransformation{TransformVariables.TVExp, 1}}}, DiffEqBayes.DynamicHMCPosterior{OrdinaryDiffEqTsit5.Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, Main.var"##DynamicHMC#140".LotkaVolterraTest1{Main.var"##DynamicHMC#140".var"###ParameterizedDiffEqFunction#143", Main.var"##DynamicHMC#140".var"###ParameterizedTGradFunction#144", Main.var"##DynamicHMC#140".var"###ParameterizedJacobianFunction#145", Nothing, Nothing, ModelingToolkit.System}, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Vector{Float64}, Vector{Distributions.Normal{Float64}}, Vector{Distributions.Normal{Float64}}, Tuple{}, Vector{Int64}, typeof(identity)}}}, Float64}, Float64, 3}). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:657 ┌ Warning: At t=2.541700512364984e-270, dt was forced below floating point epsilon 4.2030456845295373e-286, and step error estimate = NaN. Aborting. There is either an error in your model specification or the true solution is unstable (or the true solution can not be represented in the precision of ForwardDiff.Dual{ForwardDiff.Tag{Base.Fix1{typeof(LogDensityProblems.logdensity), TransformedLogDensities.TransformedLogDensity{TransformVariables.TransformTuple{@NamedTuple{parameters::TransformVariables.ArrayTransformation{TransformVariables.TVExp, 1}, σ::TransformVariables.ArrayTransformation{TransformVariables.TVExp, 1}}}, DiffEqBayes.DynamicHMCPosterior{OrdinaryDiffEqTsit5.Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, Main.var"##DynamicHMC#140".LotkaVolterraTest1{Main.var"##DynamicHMC#140".var"###ParameterizedDiffEqFunction#143", Main.var"##DynamicHMC#140".var"###ParameterizedTGradFunction#144", Main.var"##DynamicHMC#140".var"###ParameterizedJacobianFunction#145", Nothing, Nothing, ModelingToolkit.System}, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Vector{Float64}, Vector{Distributions.Normal{Float64}}, Vector{Distributions.Normal{Float64}}, Tuple{}, Vector{Int64}, typeof(identity)}}}, Float64}, Float64, 3}). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:657 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Info: found initial stepsize └ ϵ = 0.00156 ┌ Info: Starting MCMC │ total_steps = 75 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 7.3e-5 │ estimated_seconds_left = 0.0054 └ ϵ = 0.00156 ┌ Info: Starting MCMC │ total_steps = 25 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00027 │ estimated_seconds_left = 0.0065 └ ϵ = 0.00058 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0011351101138699189, 0.000370468598355933, 0.1726089564856122] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.034 │ estimated_seconds_left = 1.7 └ ϵ = 0.000142 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0008979411437962342, 0.0003249746960331196, 0.24608170218109718] ┌ Info: Starting MCMC │ total_steps = 100 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00024 │ estimated_seconds_left = 0.024 └ ϵ = 0.335 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0008429377215987642, 0.00030531071050045615, 0.22291751000819762] ┌ Info: Starting MCMC │ total_steps = 200 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00054 │ estimated_seconds_left = 0.11 └ ϵ = 0.48 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00056 │ estimated_seconds_left = 0.055 └ ϵ = 0.741 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0007186491748263049, 0.0002737780561132483, 0.2262855667030785] ┌ Info: Starting MCMC │ total_steps = 400 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.0003 │ estimated_seconds_left = 0.12 └ ϵ = 0.484 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00065 │ estimated_seconds_left = 0.19 └ ϵ = 0.274 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.0011 │ estimated_seconds_left = 0.21 └ ϵ = 0.857 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.0004 │ estimated_seconds_left = 0.039 └ ϵ = 0.639 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0008644899218363732, 0.00032153064131523295, 0.2687425192350339] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00024 │ estimated_seconds_left = 0.012 └ ϵ = 0.662 ┌ Info: Starting MCMC └ total_steps = 1000 ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00023 └ estimated_seconds_left = 0.23 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.00056 └ estimated_seconds_left = 0.5 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.00047 └ estimated_seconds_left = 0.37 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.0005 └ estimated_seconds_left = 0.35 ┌ Info: MCMC progress │ step = 401 │ seconds_per_step = 0.00047 └ estimated_seconds_left = 0.28 ┌ Info: MCMC progress │ step = 501 │ seconds_per_step = 0.00049 └ estimated_seconds_left = 0.24 ┌ Info: MCMC progress │ step = 601 │ seconds_per_step = 0.00046 └ estimated_seconds_left = 0.18 ┌ Info: MCMC progress │ step = 701 │ seconds_per_step = 0.00046 └ estimated_seconds_left = 0.14 ┌ Info: MCMC progress │ step = 801 │ seconds_per_step = 0.00053 └ estimated_seconds_left = 0.1 ┌ Info: MCMC progress │ step = 901 │ seconds_per_step = 0.00053 └ estimated_seconds_left = 0.053 ┌ Warning: Assignment to `bayesian_result` in soft scope is ambiguous because a global variable by the same name exists: `bayesian_result` will be treated as a new local. Disambiguate by using `local bayesian_result` to suppress this warning or `global bayesian_result` to assign to the existing global variable. └ @ ~/.julia/packages/DiffEqBayes/CpDUh/test/dynamicHMC.jl:69 ┌ Warning: Independent variable t should be defined with @independent_variables t. └ @ ModelingToolkit ~/.julia/packages/ModelingToolkit/IdXTK/src/utils.jl:121 ┌ Info: Starting MCMC │ total_steps = 75 └ tuning = "stepsize" ┌ Warning: First function call produced NaNs. Exiting. Double check that none of the initial conditions, parameters, or timespan values are NaN. └ @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/GMkz9/src/initdt.jl:132 ┌ Warning: At t=0.0, dt was forced below floating point epsilon 5.0e-324, and step error estimate = NaN. Aborting. There is either an error in your model specification or the true solution is unstable (or the true solution can not be represented in the precision of ForwardDiff.Dual{ForwardDiff.Tag{Base.Fix1{typeof(LogDensityProblems.logdensity), TransformedLogDensities.TransformedLogDensity{TransformVariables.TransformTuple{@NamedTuple{parameters::TransformVariables.ArrayTransformation{TransformVariables.TVExp, 1}, σ::TransformVariables.ArrayTransformation{TransformVariables.TVExp, 1}}}, DiffEqBayes.DynamicHMCPosterior{OrdinaryDiffEqTsit5.Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, Main.var"##DynamicHMC#140".LotkaVolterraTest4{Main.var"##DynamicHMC#140".var"###ParameterizedDiffEqFunction#150", Main.var"##DynamicHMC#140".var"###ParameterizedTGradFunction#151", Main.var"##DynamicHMC#140".var"###ParameterizedJacobianFunction#152", Nothing, Nothing, ModelingToolkit.System}, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Vector{Float64}, @NamedTuple{a::Distributions.Truncated{Distributions.Normal{Float64}, Distributions.Continuous, Float64, Float64, Float64}, b::Distributions.Truncated{Distributions.Normal{Float64}, Distributions.Continuous, Float64, Float64, Float64}, c::Distributions.Truncated{Distributions.Normal{Float64}, Distributions.Continuous, Float64, Float64, Float64}, d::Distributions.Truncated{Distributions.Normal{Float64}, Distributions.Continuous, Float64, Float64, Float64}}, Vector{Distributions.Normal{Float64}}, Tuple{}, Nothing, typeof(identity)}}}, Float64}, Float64, 6}). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:657 ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.024 │ estimated_seconds_left = 1.8 └ ϵ = 1.0 ┌ Warning: First function call produced NaNs. Exiting. Double check that none of the initial conditions, parameters, or timespan values are NaN. └ @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/GMkz9/src/initdt.jl:132 ┌ Warning: At t=0.0, dt was forced below floating point epsilon 5.0e-324, and step error estimate = NaN. Aborting. There is either an error in your model specification or the true solution is unstable (or the true solution can not be represented in the precision of ForwardDiff.Dual{ForwardDiff.Tag{Base.Fix1{typeof(LogDensityProblems.logdensity), TransformedLogDensities.TransformedLogDensity{TransformVariables.TransformTuple{@NamedTuple{parameters::TransformVariables.ArrayTransformation{TransformVariables.TVExp, 1}, σ::TransformVariables.ArrayTransformation{TransformVariables.TVExp, 1}}}, DiffEqBayes.DynamicHMCPosterior{OrdinaryDiffEqTsit5.Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, Main.var"##DynamicHMC#140".LotkaVolterraTest4{Main.var"##DynamicHMC#140".var"###ParameterizedDiffEqFunction#150", Main.var"##DynamicHMC#140".var"###ParameterizedTGradFunction#151", Main.var"##DynamicHMC#140".var"###ParameterizedJacobianFunction#152", Nothing, Nothing, ModelingToolkit.System}, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}, SciMLBase.StandardODEProblem}, Matrix{Float64}, Vector{Float64}, @NamedTuple{a::Distributions.Truncated{Distributions.Normal{Float64}, Distributions.Continuous, Float64, Float64, Float64}, b::Distributions.Truncated{Distributions.Normal{Float64}, Distributions.Continuous, Float64, Float64, Float64}, c::Distributions.Truncated{Distributions.Normal{Float64}, Distributions.Continuous, Float64, Float64, Float64}, d::Distributions.Truncated{Distributions.Normal{Float64}, Distributions.Continuous, Float64, Float64, Float64}}, Vector{Distributions.Normal{Float64}}, Tuple{}, Nothing, typeof(identity)}}}, Float64}, Float64, 6}). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:657 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Info: Starting MCMC │ total_steps = 25 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00013 │ estimated_seconds_left = 0.0032 └ ϵ = 0.000803 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0009362435745933733, 0.0013896727122264638, 0.0013243592846918278, 0.0019262769005682246, 0.2107573981235462, 0.2927911396933935] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.042 │ estimated_seconds_left = 2.1 └ ϵ = 0.00017 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0014977635652150454, 0.001871298693384999, 0.0018347759536500791, 0.0026146236215964206, 0.3276394769425561, 0.3029580456750245] ┌ Info: Starting MCMC │ total_steps = 100 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.0013 │ estimated_seconds_left = 0.13 └ ϵ = 0.137 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.001184169885707669, 0.001412434134813278, 0.0015896962850696352, 0.0019974380175110016, 0.30179338731148647, 0.2694687927109264] ┌ Info: Starting MCMC │ total_steps = 200 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.0013 │ estimated_seconds_left = 0.25 └ ϵ = 0.103 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.0024 │ estimated_seconds_left = 0.24 └ ϵ = 0.0741 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0015210857104664543, 0.001924000828579715, 0.001975134378518969, 0.0025955045146590287, 0.29092018449440016, 0.3311650450951156] ┌ Info: Starting MCMC │ total_steps = 400 └ tuning = "stepsize and LinearAlgebra.Diagonal metric" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00063 │ estimated_seconds_left = 0.25 └ ϵ = 0.129 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.0037 │ estimated_seconds_left = 1.1 └ ϵ = 0.196 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.0025 │ estimated_seconds_left = 0.49 └ ϵ = 0.092 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.0024 │ estimated_seconds_left = 0.23 └ ϵ = 0.137 ┌ Info: adaptation finished └ adapted_kinetic_energy = Gaussian kinetic energy (Diagonal), √diag(M⁻¹): [0.0015531078348637055, 0.0018268365301808498, 0.002020987750774946, 0.0026577800413894125, 0.30648070397298105, 0.28218820171277625] ┌ Info: Starting MCMC │ total_steps = 50 └ tuning = "stepsize" ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.00029 │ estimated_seconds_left = 0.014 └ ϵ = 0.109 ┌ Info: Starting MCMC └ total_steps = 1000 ┌ Info: MCMC progress │ step = 1 │ seconds_per_step = 0.0015 └ estimated_seconds_left = 1.5 ┌ Info: MCMC progress │ step = 101 │ seconds_per_step = 0.0038 └ estimated_seconds_left = 3.4 ┌ Info: MCMC progress │ step = 201 │ seconds_per_step = 0.0035 └ estimated_seconds_left = 2.8 ┌ Info: MCMC progress │ step = 301 │ seconds_per_step = 0.0038 └ estimated_seconds_left = 2.7 ┌ Info: MCMC progress │ step = 401 │ seconds_per_step = 0.0033 └ estimated_seconds_left = 2.0 ┌ Info: MCMC progress │ step = 501 │ seconds_per_step = 0.0036 └ estimated_seconds_left = 1.8 ┌ Info: MCMC progress │ step = 601 │ seconds_per_step = 0.0035 └ estimated_seconds_left = 1.4 ┌ Info: MCMC progress │ step = 701 │ seconds_per_step = 0.0032 └ estimated_seconds_left = 0.95 ┌ Info: MCMC progress │ step = 801 │ seconds_per_step = 0.0038 └ estimated_seconds_left = 0.75 ┌ Info: MCMC progress │ step = 901 │ seconds_per_step = 0.0041 └ estimated_seconds_left = 0.41 Test Summary: | Pass Broken Total Time DynamicHMC | 8 2 10 5m28.3s 329.500572 seconds (198.49 M allocations: 11.751 GiB, 2.20% gc time, 57.61% compilation time: 3% of which was recompilation) One parameter case ┌ Warning: Independent variable t should be defined with @independent_variables t. └ @ ModelingToolkit ~/.julia/packages/ModelingToolkit/IdXTK/src/utils.jl:121 ┌ Info: Found initial step size └ ϵ = 0.00625 bayesian_result = MCMC chain (500×14×1 Array{Float64, 3}) ┌ Warning: Using a `Bool` for keyword argument `autodiff` is deprecated. Please use an `ADType` specifier. │ caller = _process_AD_choice(ad_alg::Bool, ::Val{0}, ::Val{:forward}) at misc_utils.jl:158 └ @ Core ~/.julia/packages/OrdinaryDiffEqCore/GMkz9/src/misc_utils.jl:158 ┌ Info: Found initial step size └ ϵ = 0.00625 ┌ Info: Found initial step size └ ϵ = 0.00625 Multithreaded case ┌ Warning: Only a single thread available: MCMC chains are not sampled in parallel └ @ AbstractMCMC ~/.julia/packages/AbstractMCMC/z4BsN/src/sample.jl:432 ┌ Info: Found initial step size └ ϵ = 0.00625 ┌ Info: Found initial step size └ ϵ = 0.00625 ┌ Info: Found initial step size └ ϵ = 0.0125 ┌ Warning: Interrupted. Larger maxiters is needed. If you are using an integrator for non-stiff ODEs or an automatic switching algorithm (the default), you may want to consider using a method for stiff equations. See the solver pages for more details (e.g. https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems). └ @ SciMLBase ~/.julia/packages/SciMLBase/YE7xF/src/integrator_interface.jl:623 ┌ Info: Found initial step size └ ϵ = 0.003125 ┌ Info: Found initial step size └ ϵ = 0.00625 Four parameter case ┌ Warning: Independent variable t should be defined with @independent_variables t. └ @ ModelingToolkit ~/.julia/packages/ModelingToolkit/IdXTK/src/utils.jl:121 ┌ Info: Found initial step size └ ϵ = 0.025 bayesian_result = MCMC chain (500×17×1 Array{Float64, 3}) Steady state problem ┌ Warning: The `alias_u0` keyword argument is deprecated. Please use a NonlinearAliasSpecifier, e.g. `alias = NonlinearAliasSpecifier(alias_u0 = true)`. └ @ NonlinearSolveBase ~/.julia/packages/NonlinearSolveBase/2E600/src/solve.jl:57 ====================================================================================== 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 463 running 1 of 1 signal (10): User defined signal 1 _ZN4llvm11ConstantInt3getERNS_11LLVMContextERKNS_5APIntE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) unknown function (ip: 0x7ffc5d5e1e6f) at (unknown file) unknown function (ip: 0x70610000003f) at (unknown file) unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== ┌ Warning: `alias_u0` keyword argument is deprecated, to set `alias_u0`, │ please use an ODEAliasSpecifier, e.g. `solve(prob, alias = ODEAliasSpecifier(alias_u0 = true)) │ caller = ip:0x0 └ @ Core :-1 ┌ Warning: `alias_u0` keyword argument is deprecated, to set `alias_u0`, │ please use an ODEAliasSpecifier, e.g. `solve(prob, alias = ODEAliasSpecifier(alias_u0 = true)) │ caller = __solve(::SciMLBase.SteadyStateProblem{Vector{Float64}, true, Vector{Float64}, SciMLBase.ODEFunction{true, SciMLBase.FullSpecialize, typeof(Main.var"##Turing#141".f), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}}, ::SteadyStateDiffEq.DynamicSS{OrdinaryDiffEqTsit5.Tsit5{typeof(OrdinaryDiffEqCore.trivial_limiter!), typeof(OrdinaryDiffEqCore.trivial_limiter!), Static.False}, Float64}; abstol::Float64, reltol::Float64, odesolve_kwargs::@NamedTuple{}, save_idxs::Nothing, termination_condition::NonlinearSolveBase.NormTerminationMode{typeof(NonlinearSolveBase.Linf_NORM)}, kwargs::Base.Pairs{Symbol, Bool, Nothing, @NamedTuple{alias_u0::Bool}}) at solve.jl:56 └ @ Core ~/.julia/packages/SteadyStateDiffEq/ovRt6/src/solve.jl:56 ====================================================================================== 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:1217 wait_forever at ./task.jl:1139 jfptr_wait_forever_63682.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [inlined] start_task at /source/src/task.c:1281 unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== ┌ Warning: There were no samples collected in one or more groups. │ This may be due to idle threads, or you may need to run your │ program longer (perhaps by running it multiple times), │ or adjust the delay between samples with `Profile.init()`. └ @ Profile /opt/julia/share/julia/stdlib/v1.13/Profile/src/Profile.jl:1362 Overhead ╎ [+additional indent] Count File:Line Function ========================================================= Thread 1 (default) Task 0x00007b63376b2fe0 Total snapshots: 432. Utilization: 0% ╎432 @Base/task.jl:1139 wait_forever() 431╎ 432 @Base/task.jl:1217 wait() [1] signal 15: Terminated in expression starting at /PkgEval.jl/scripts/evaluate.jl:210 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:1217 wait_forever at ./task.jl:1139 jfptr_wait_forever_63682.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [inlined] start_task at /source/src/task.c:1281 unknown function (ip: (nil)) at (unknown file) Allocations: 34100025 (Pool: 34099302; Big: 723); GC: 27 [463] signal 15: Terminated in expression starting at /home/pkgeval/.julia/packages/DiffEqBayes/CpDUh/test/turing.jl:110 _ZNK4llvm4SCEV7getTypeEv at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN4llvm15ScalarEvolution10getMulExprERNS_15SmallVectorImplIPKNS_4SCEVEEENS2_11NoWrapFlagsEj at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN4llvm15ScalarEvolution10getMulExprEPKNS_4SCEVES3_NS1_11NoWrapFlagsEj.constprop.0 at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN4llvm15ScalarEvolution10getMulExprERNS_15SmallVectorImplIPKNS_4SCEVEEENS2_11NoWrapFlagsEj at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN4llvm15ScalarEvolution10getMulExprEPKNS_4SCEVES3_NS1_11NoWrapFlagsEj at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN12_GLOBAL__N_111LSRInstance24GenerateAllReuseFormulaeEv at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN12_GLOBAL__N_111LSRInstanceC2EPN4llvm4LoopERNS1_7IVUsersERNS1_15ScalarEvolutionERNS1_13DominatorTreeERNS1_8LoopInfoERKNS1_19TargetTransformInfoERNS1_15AssumptionCacheERNS1_17TargetLibraryInfoEPNS1_16MemorySSAUpdaterE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZL18ReduceLoopStrengthPN4llvm4LoopERNS_7IVUsersERNS_15ScalarEvolutionERNS_13DominatorTreeERNS_8LoopInfoERKNS_19TargetTransformInfoERNS_15AssumptionCacheERNS_17TargetLibraryInfoEPNS_9MemorySSAE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN12_GLOBAL__N_118LoopStrengthReduce9runOnLoopEPN4llvm4LoopERNS1_13LPPassManagerE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN4llvm13LPPassManager13runOnFunctionERNS_8FunctionE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN4llvm13FPPassManager13runOnFunctionERNS_8FunctionE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN4llvm13FPPassManager11runOnModuleERNS_6ModuleE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) _ZN4llvm6legacy15PassManagerImpl3runERNS_6ModuleE at /opt/julia/bin/../lib/julia/libLLVM.so.20.1jl (unknown line) operator() at /source/src/jitlayers.cpp:1628 addModule at /source/src/jitlayers.cpp:2119 jl_compile_codeinst_now at /source/src/jitlayers.cpp:682 jl_compile_codeinst_impl at /source/src/jitlayers.cpp:876 jl_compile_method_internal at /source/src/gf.c:3648 _jl_invoke at /source/src/gf.c:4108 [inlined] ijl_apply_generic at /source/src/gf.c:4313 Dict at ./dict.jl:114 _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [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:679 jl_interpret_toplevel_thunk at /source/src/interpreter.c:884 jl_toplevel_eval_flex at /source/src/toplevel.c:742 jl_eval_toplevel_stmts at /source/src/toplevel.c:585 jl_toplevel_eval_flex at /source/src/toplevel.c:683 ijl_toplevel_eval at /source/src/toplevel.c:754 ijl_toplevel_eval_in at /source/src/toplevel.c:799 eval at ./boot.jl:489 include_string at ./loading.jl:2954 _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 _include at ./loading.jl:3014 include at ./Base.jl:310 IncludeInto at ./Base.jl:311 unknown function (ip: 0x7061edd297c2) at (unknown file) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [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:679 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 jl_toplevel_eval_flex at /source/src/toplevel.c:742 jl_eval_toplevel_stmts at /source/src/toplevel.c:585 jl_eval_module_expr at /source/src/toplevel.c:248 [inlined] jl_toplevel_eval_flex at /source/src/toplevel.c:650 ijl_toplevel_eval at /source/src/toplevel.c:754 ijl_toplevel_eval_in at /source/src/toplevel.c:799 eval at ./boot.jl:489 jfptr_eval_14982.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 macro expansion at /home/pkgeval/.julia/packages/SafeTestsets/raUNr/src/SafeTestsets.jl:28 [inlined] macro expansion at ./timing.jl:689 [inlined] top-level scope at /home/pkgeval/.julia/packages/DiffEqBayes/CpDUh/test/runtests.jl:10 _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_invoke at /source/src/gf.c:4123 jl_toplevel_eval_flex at /source/src/toplevel.c:731 jl_eval_toplevel_stmts at /source/src/toplevel.c:585 jl_toplevel_eval_flex at /source/src/toplevel.c:683 ijl_toplevel_eval at /source/src/toplevel.c:754 ijl_toplevel_eval_in at /source/src/toplevel.c:799 eval at ./boot.jl:489 include_string at ./loading.jl:2954 _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 _include at ./loading.jl:3014 include at ./Base.jl:310 IncludeInto at ./Base.jl:311 jfptr_IncludeInto_55095.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [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:679 jl_interpret_toplevel_thunk at /source/src/interpreter.c:884 jl_toplevel_eval_flex at /source/src/toplevel.c:742 jl_eval_toplevel_stmts at /source/src/toplevel.c:585 jl_toplevel_eval_flex at /source/src/toplevel.c:683 ijl_toplevel_eval at /source/src/toplevel.c:754 ijl_toplevel_eval_in at /source/src/toplevel.c:799 eval at ./boot.jl:489 exec_options at ./client.jl:310 _start at ./client.jl:577 jfptr__start_50137.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [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: 0x7061ef76a249) at /lib/x86_64-linux-gnu/libc.so.6 __libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S unknown function (ip: (nil)) at (unknown file) Allocations: 482133443 (Pool: 482129423; Big: 4020); GC: 110 PkgEval terminated after 2722.4s: test duration exceeded the time limit