Package evaluation of SimulatedNeuralMoments on Julia 1.10.8 (92f03a4775*) started at 2025-02-25T18:27:09.818 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 5.16s ################################################################################ # Installation # Installing SimulatedNeuralMoments... Resolving package versions... Installed FFMPEG ─ v0.2.4 Updating `~/.julia/environments/v1.10/Project.toml` [43b7c8c0] + SimulatedNeuralMoments v3.0.0 Updating `~/.julia/environments/v1.10/Manifest.toml` [621f4979] + AbstractFFTs v1.5.0 [80f14c24] + AbstractMCMC v5.6.0 [1520ce14] + AbstractTrees v0.4.5 [7d9f7c33] + Accessors v0.1.41 [79e6a3ab] + Adapt v4.2.0 [66dad0bd] + AliasTables v1.1.3 [dce04be8] + ArgCheck v2.4.0 [7d9fca2a] + Arpack v0.5.4 [a9b6321e] + Atomix v1.1.0 [13072b0f] + AxisAlgorithms v1.1.0 [39de3d68] + AxisArrays v0.4.7 [fbb218c0] + BSON v0.3.9 [198e06fe] + BangBang v0.4.3 [9718e550] + Baselet v0.1.1 [b99e7846] + BinaryProvider v0.5.10 [d1d4a3ce] + BitFlags v0.1.9 [fa961155] + CEnum v0.5.0 [082447d4] + ChainRules v1.72.2 [d360d2e6] + ChainRulesCore v1.25.1 [aaaa29a8] + Clustering v0.15.8 [944b1d66] + CodecZlib v0.7.8 [35d6a980] + ColorSchemes v3.29.0 [3da002f7] + ColorTypes v0.12.0 [c3611d14] + ColorVectorSpace v0.11.0 [5ae59095] + Colors v0.13.0 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.16.0 [a33af91c] + CompositionsBase v0.1.2 [f0e56b4a] + ConcurrentUtilities v2.5.0 [88cd18e8] + ConsoleProgressMonitor v0.1.2 [187b0558] + ConstructionBase v1.5.8 [6add18c4] + ContextVariablesX v0.1.3 [d38c429a] + Contour v0.6.3 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.18.20 [e2d170a0] + DataValueInterfaces v1.0.0 [244e2a9f] + DefineSingletons v0.1.2 [8bb1440f] + DelimitedFiles v1.9.1 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [b4f34e82] + Distances v0.10.12 [31c24e10] + Distributions v0.25.117 [ffbed154] + DocStringExtensions v0.9.3 [460bff9d] + ExceptionUnwrapping v0.1.11 ⌃ [c87230d0] + FFMPEG v0.2.4 [7a1cc6ca] + FFTW v1.8.1 [cc61a311] + FLoops v0.2.2 [b9860ae5] + FLoopsBase v0.1.1 [1a297f60] + FillArrays v1.13.0 [53c48c17] + FixedPointNumbers v0.8.5 ⌅ [587475ba] + Flux v0.14.25 [1fa38f19] + Format v1.3.7 [f6369f11] + ForwardDiff v0.10.38 ⌅ [d9f16b24] + Functors v0.4.12 [0c68f7d7] + GPUArrays v11.2.2 [46192b85] + GPUArraysCore v0.2.0 [28b8d3ca] + GR v0.73.13 [42e2da0e] + Grisu v1.0.2 [cd3eb016] + HTTP v1.10.15 [076d061b] + HashArrayMappedTries v0.2.0 [34004b35] + HypergeometricFunctions v0.3.27 [7869d1d1] + IRTools v0.4.14 [22cec73e] + InitialValues v0.3.1 [a98d9a8b] + Interpolations v0.15.1 [8197267c] + IntervalSets v0.7.10 [3587e190] + InverseFunctions v0.1.17 [92d709cd] + IrrationalConstants v0.2.4 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [1019f520] + JLFzf v0.1.9 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 [b14d175d] + JuliaVariables v0.2.4 [63c18a36] + KernelAbstractions v0.9.34 [5ab0869b] + KernelDensity v0.6.9 [929cbde3] + LLVM v9.2.0 [b964fa9f] + LaTeXStrings v1.4.0 [23fbe1c1] + Latexify v0.16.6 [1d6d02ad] + LeftChildRightSiblingTrees v0.2.0 [6fdf6af0] + LogDensityProblems v2.1.2 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.1.0 [c7f686f2] + MCMCChains v6.0.7 [be115224] + MCMCDiagnosticTools v0.3.14 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[e66e0078] + CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] + LibCURL_jll v8.4.0+0 [e37daf67] + LibGit2_jll v1.6.4+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.2+1 [14a3606d] + MozillaCACerts_jll v2023.1.10 [4536629a] + OpenBLAS_jll v0.3.23+4 [05823500] + OpenLibm_jll v0.8.1+4 [efcefdf7] + PCRE2_jll v10.42.0+1 [bea87d4a] + SuiteSparse_jll v7.2.1+1 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 [8e850ede] + nghttp2_jll v1.52.0+1 [3f19e933] + p7zip_jll v17.4.0+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` Building FFMPEG → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/9143266ba77d3313a4cf61d8333a1970e8c5d8b6/build.log` Installation completed after 46.5s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 293.62s ################################################################################ # Testing # Testing SimulatedNeuralMoments Status `/tmp/jl_VVTImL/Project.toml` [fbb218c0] BSON v0.3.9 [8bb1440f] DelimitedFiles v1.9.1 [31c24e10] Distributions v0.25.117 ⌅ [587475ba] Flux v0.14.25 [c7f686f2] MCMCChains v6.0.7 [43b7c8c0] SimulatedNeuralMoments v3.0.0 [2913bbd2] StatsBase v0.34.4 [f3b207a7] StatsPlots v0.15.7 [37e2e46d] LinearAlgebra [de0858da] Printf [9a3f8284] Random [10745b16] Statistics v1.10.0 [8dfed614] Test Status `/tmp/jl_VVTImL/Manifest.toml` [621f4979] AbstractFFTs v1.5.0 [80f14c24] AbstractMCMC v5.6.0 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.41 [79e6a3ab] Adapt v4.2.0 [66dad0bd] AliasTables v1.1.3 [dce04be8] ArgCheck v2.4.0 [7d9fca2a] Arpack v0.5.4 [a9b6321e] Atomix v1.1.0 [13072b0f] AxisAlgorithms v1.1.0 [39de3d68] AxisArrays v0.4.7 [fbb218c0] BSON v0.3.9 [198e06fe] BangBang v0.4.3 [9718e550] Baselet v0.1.1 [b99e7846] BinaryProvider v0.5.10 [d1d4a3ce] BitFlags v0.1.9 [fa961155] CEnum v0.5.0 [082447d4] ChainRules v1.72.2 [d360d2e6] ChainRulesCore v1.25.1 [aaaa29a8] Clustering v0.15.8 [944b1d66] CodecZlib v0.7.8 [35d6a980] ColorSchemes v3.29.0 [3da002f7] ColorTypes v0.12.0 [c3611d14] ColorVectorSpace v0.11.0 [5ae59095] Colors v0.13.0 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.16.0 [a33af91c] CompositionsBase v0.1.2 [f0e56b4a] ConcurrentUtilities v2.5.0 [88cd18e8] ConsoleProgressMonitor v0.1.2 [187b0558] ConstructionBase v1.5.8 [6add18c4] ContextVariablesX v0.1.3 [d38c429a] Contour v0.6.3 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.18.20 [e2d170a0] DataValueInterfaces v1.0.0 [244e2a9f] DefineSingletons v0.1.2 [8bb1440f] DelimitedFiles v1.9.1 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.117 [ffbed154] DocStringExtensions v0.9.3 [460bff9d] ExceptionUnwrapping v0.1.11 ⌃ 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[14a3606d] MozillaCACerts_jll v2023.1.10 [4536629a] OpenBLAS_jll v0.3.23+4 [05823500] OpenLibm_jll v0.8.1+4 [efcefdf7] PCRE2_jll v10.42.0+1 [bea87d4a] SuiteSparse_jll v7.2.1+1 [83775a58] Zlib_jll v1.2.13+1 [8e850b90] libblastrampoline_jll v5.11.0+0 [8e850ede] nghttp2_jll v1.52.0+1 [3f19e933] p7zip_jll v17.4.0+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. Testing Running tests... [ Info: running SV example with a small sample [ Info: sampling from prior and training the net [ Info: starting training of the net epoch: 10, current loss: 0.03156044 best loss: 0.03156044 relative rmse.: [0.258 0.669 0.515] epoch: 20, current loss: 0.029845357 best loss: 0.029845357 relative rmse.: [0.239 0.659 0.486] epoch: 30, current loss: 0.028516509 best loss: 0.028516509 relative rmse.: [0.221 0.654 0.468] epoch: 40, current loss: 0.028085507 best loss: 0.028085507 relative rmse.: [0.215 0.651 0.462] epoch: 50, current loss: 0.02782176 best loss: 0.02782176 relative rmse.: [0.21 0.649 0.459] epoch: 60, current loss: 0.027640142 best loss: 0.027640142 relative rmse.: [0.208 0.649 0.456] epoch: 70, current loss: 0.027519312 best loss: 0.027519312 relative rmse.: [0.208 0.648 0.454] epoch: 80, current loss: 0.027425433 best loss: 0.027425433 relative rmse.: [0.207 0.647 0.452] epoch: 90, current loss: 0.027342351 best loss: 0.027342351 relative rmse.: [0.207 0.647 0.451] epoch: 100, current loss: 0.027274784 best loss: 0.027274784 relative rmse.: [0.206 0.646 0.449] [ Info: the raw neural net fit is [0.6151415109634399, 0.8989565372467041, 0.4347015619277954] [ Info: running a short chain to allow refining of the tuning [ Info: starting the MCMC run iter 200 of 1100 [0.756, 0.952, 0.414] acc. rate: 0.27 iter 300 of 1100 [0.735, 0.992, 0.18] acc. rate: 0.313 iter 400 of 1100 [0.785, 0.95, 0.246] acc. rate: 0.332 iter 500 of 1100 [0.704, 0.901, 0.378] acc. rate: 0.346 iter 600 of 1100 [0.67, 0.912, 0.384] acc. rate: 0.345 iter 700 of 1100 [0.771, 0.905, 0.42] acc. rate: 0.354 iter 800 of 1100 [0.979, 0.985, 0.191] acc. rate: 0.336 iter 900 of 1100 [0.941, 0.995, 0.158] acc. rate: 0.313 iter 1000 of 1100 [1.066, 0.995, 0.123] acc. rate: 0.294 iter 1100 of 1100 [0.593, 0.979, 0.326] acc. rate: 0.289 [ Info: display the results acceptance rate: 0.292 Chains MCMC chain (1000×4×1 Array{Float64, 3}): Iterations = 1:1:1000 Number of chains = 1 Samples per chain = 1000 parameters = α, ρ, σ, lnℒ Summary Statistics parameters mean std mcse ess_bulk ess_tail rhat ess_per_sec Symbol Float64 Float64 Float64 Float64 Float64 Float64 Missing α 0.7539 0.1540 0.0843 4.0134 24.6507 1.4467 missing ρ 0.9157 0.0908 0.0283 7.8926 46.1393 1.2022 missing σ 0.3320 0.1377 0.0353 14.1353 23.8269 1.1378 missing lnℒ -1.6198 1.1586 0.1602 53.9847 58.0351 1.0080 missing Quantiles parameters 2.5% 25.0% 50.0% 75.0% 97.5% Symbol Float64 Float64 Float64 Float64 Float64 α 0.5234 0.6301 0.7216 0.9166 1.0664 ρ 0.6341 0.8884 0.9435 0.9787 0.9977 σ 0.1233 0.2221 0.3202 0.4209 0.6572 lnℒ -4.8087 -2.0931 -1.3259 -0.8483 -0.2048 For comparison, the true parameters are [0.6921171816887304 0.9 0.363] [ Info: running MN example with a small sample WARNING: Method definition dgp(Any) in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:31 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:5. WARNING: Method definition dgp(Any, Any) in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:31 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:5. WARNING: Method definition auxstat(Any) in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:13 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:17. WARNING: Method definition auxstat(Any, Any) in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:8 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:23. WARNING: Method definition TrueParameters() in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:50 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:27. WARNING: Method definition PriorSupport() in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:54 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:31. WARNING: Method definition PriorDraw() in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:76 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:37. WARNING: Method definition InSupport(Any) in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:66 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:42. WARNING: Method definition GoodData(Any) in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:72 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:48. WARNING: Method definition Prior(Any) in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/SVlib.jl:61 overwritten at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/MNlib.jl:53. [ Info: sampling from prior and training the net [ Info: starting training of the net epoch: 10, current loss: 0.039487176 best loss: 0.039487176 relative rmse.: [0.462 0.75 0.806 0.386 0.483] epoch: 20, current loss: 0.03349715 best loss: 0.03349715 relative rmse.: [0.431 0.663 0.746 0.346 0.451] epoch: 30, current loss: 0.027241973 best loss: 0.027241973 relative rmse.: [0.328 0.558 0.676 0.308 0.426] epoch: 40, current loss: 0.024988664 best loss: 0.024988664 relative rmse.: [0.298 0.501 0.641 0.296 0.412] epoch: 50, current loss: 0.023525873 best loss: 0.023525873 relative rmse.: [0.283 0.461 0.622 0.29 0.398] epoch: 60, current loss: 0.022378486 best loss: 0.022378486 relative rmse.: [0.275 0.436 0.607 0.286 0.383] epoch: 70, current loss: 0.021507386 best loss: 0.021507386 relative rmse.: [0.267 0.42 0.586 0.283 0.373] epoch: 80, current loss: 0.0207194 best loss: 0.0207194 relative rmse.: [0.26 0.41 0.565 0.281 0.365] epoch: 90, current loss: 0.020041106 best loss: 0.020041106 relative rmse.: [0.253 0.403 0.546 0.279 0.357] epoch: 100, current loss: 0.01947767 best loss: 0.01947767 relative rmse.: [0.248 0.396 0.527 0.276 0.352] [ Info: the raw neural net fit is [1.083572268486023, 0.9534660577774048, 0.0772719532251358, 2.0316848754882812, 0.3789811134338379] WARNING: Method definition proposal(Any) in module Main at /home/pkgeval/.julia/packages/SimulatedNeuralMoments/CKRST/examples/Example.jl:75 overwritten on the same line (check for duplicate calls to `include`). [ Info: running a short chain to allow refining of the tuning [ Info: starting the MCMC run iter 200 of 1100 [1.006, 0.964, 0.126, 1.89, 0.385] acc. rate: 0.335 iter 300 of 1100 [1.02, 0.842, 0.151, 2.172, 0.443] acc. rate: 0.323 iter 400 of 1100 [1.007, 0.502, 0.091, 1.956, 0.38] acc. rate: 0.308 iter 500 of 1100 [1.022, 0.643, 0.131, 2.131, 0.408] acc. rate: 0.316 iter 600 of 1100 [1.055, 0.715, 0.078, 1.991, 0.377] acc. rate: 0.318 iter 700 of 1100 [1.034, 0.836, 0.135, 1.84, 0.432] acc. rate: 0.321 iter 800 of 1100 [1.057, 0.879, 0.135, 1.988, 0.377] acc. rate: 0.325 iter 900 of 1100 [0.998, 0.804, 0.159, 1.826, 0.398] acc. rate: 0.333 iter 1000 of 1100 [1.05, 1.018, 0.146, 1.923, 0.394] acc. rate: 0.333 iter 1100 of 1100 [1.03, 1.037, 0.186, 2.01, 0.419] acc. rate: 0.34 [ Info: display the results acceptance rate: 0.339 Chains MCMC chain (1000×6×1 Array{Float64, 3}): Iterations = 1:1:1000 Number of chains = 1 Samples per chain = 1000 parameters = μ1, μ2 , σ1, σ2, prob, lnℒ Summary Statistics parameters mean std mcse ess_bulk ess_tail rhat ess_per_sec Symbol Float64 Float64 Float64 Float64 Float64 Float64 Missing μ1 1.0286 0.0191 0.0033 34.2155 90.7767 1.0336 missing μ2 0.8346 0.1105 0.0202 28.2683 56.1377 1.0944 missing σ1 0.1388 0.0242 0.0090 7.4089 35.3705 1.1702 missing σ2 1.9707 0.0895 0.0334 7.3886 40.3575 1.2351 missing prob 0.3997 0.0291 0.0050 33.8357 56.6431 1.0027 missing lnℒ -2.2625 1.3793 0.1940 52.6034 92.0991 1.0068 missing Quantiles parameters 2.5% 25.0% 50.0% 75.0% 97.5% Symbol Float64 Float64 Float64 Float64 Float64 μ1 0.9926 1.0157 1.0280 1.0419 1.0673 μ2 0.6318 0.7689 0.8322 0.9025 1.0366 σ1 0.0852 0.1212 0.1394 0.1574 0.1857 σ2 1.7807 1.9127 1.9697 2.0245 2.1565 prob 0.3425 0.3808 0.3994 0.4194 0.4582 lnℒ -5.1770 -3.0916 -2.1420 -1.1824 -0.3430 For comparison, the true parameters are [1.0 1.0 0.2 1.8 0.4] Test Summary: | Pass Total Time SimulatedNeuralMoments | 6 6 6m30.8s Testing SimulatedNeuralMoments tests passed Testing completed after 400.27s PkgEval succeeded after 762.73s