Package evaluation of ConformalPrediction on Julia 1.12.0-DEV.1805 (a080deafdd*) started at 2025-03-25T02:16:45.471


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# Set-up
#

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 9.12s


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# Installation
#

Installing ConformalPrediction...
   Resolving package versions...
    Updating `~/.julia/environments/v1.12/Project.toml`
  [98bfc277] + ConformalPrediction v0.1.13
    Updating `~/.julia/environments/v1.12/Manifest.toml`
  [47edcb42] + ADTypes v1.14.0
  [621f4979] + AbstractFFTs v1.5.0
  [7d9f7c33] + Accessors v0.1.42
  [79e6a3ab] + Adapt v4.3.0
  [66dad0bd] + AliasTables v1.1.3
  [dce04be8] + ArgCheck v2.5.0
  [4fba245c] + ArrayInterface v7.18.0
  [a9b6321e] + Atomix v1.1.1
  [fbb218c0] + BSON v0.3.9
  [198e06fe] + BangBang v0.4.4
  [9718e550] + Baselet v0.1.1
  [fa961155] + CEnum v0.5.0
  [324d7699] + CategoricalArrays v0.10.8
  [af321ab8] + CategoricalDistributions v0.1.15
  [082447d4] + ChainRules v1.72.3
  [d360d2e6] + ChainRulesCore v1.25.1
⌅ [3da002f7] + ColorTypes v0.11.5
  [bbf7d656] + CommonSubexpressions v0.3.1
  [34da2185] + Compat v4.16.0
  [a33af91c] + CompositionsBase v0.1.2
  [ed09eef8] + ComputationalResources v0.3.2
  [98bfc277] + ConformalPrediction v0.1.13
  [187b0558] + ConstructionBase v1.5.8
  [6add18c4] + ContextVariablesX v0.1.3
  [a8cc5b0e] + Crayons v4.1.1
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.18.22
  [e2d170a0] + DataValueInterfaces v1.0.0
  [244e2a9f] + DefineSingletons v0.1.2
  [8bb1440f] + DelimitedFiles v1.9.1
  [b429d917] + DensityInterface v0.4.0
  [163ba53b] + DiffResults v1.1.0
  [b552c78f] + DiffRules v1.15.1
  [a0c0ee7d] + DifferentiationInterface v0.6.48
  [31c24e10] + Distributions v0.25.118
  [ffbed154] + DocStringExtensions v0.9.3
  [cc61a311] + FLoops v0.2.2
  [b9860ae5] + FLoopsBase v0.1.1
  [5789e2e9] + FileIO v1.17.0
  [1a297f60] + FillArrays v1.13.0
  [6a86dc24] + FiniteDiff v2.27.0
  [53c48c17] + FixedPointNumbers v0.8.5
⌅ [587475ba] + Flux v0.14.25
  [f6369f11] + ForwardDiff v0.10.38
⌅ [d9f16b24] + Functors v0.4.12
  [0c68f7d7] + GPUArrays v11.2.2
  [46192b85] + GPUArraysCore v0.2.0
  [076d061b] + HashArrayMappedTries v0.2.0
  [34004b35] + HypergeometricFunctions v0.3.28
  [7869d1d1] + IRTools v0.4.14
  [4846b161] + InferOpt v0.6.1
  [22cec73e] + InitialValues v0.3.1
  [3587e190] + InverseFunctions v0.1.17
  [41ab1584] + InvertedIndices v1.3.1
  [92d709cd] + IrrationalConstants v0.2.4
  [42fd0dbc] + IterativeSolvers v0.9.4
  [82899510] + IteratorInterfaceExtensions v1.0.0
  [033835bb] + JLD2 v0.5.12
  [692b3bcd] + JLLWrappers v1.7.0
  [b14d175d] + JuliaVariables v0.2.4
  [63c18a36] + KernelAbstractions v0.9.34
  [929cbde3] + LLVM v9.2.0
  [b964fa9f] + LaTeXStrings v1.4.0
⌅ [92ad9a40] + LearnAPI v0.1.0
  [d3d80556] + LineSearches v7.3.0
  [7a12625a] + LinearMaps v3.11.4
  [2ab3a3ac] + LogExpFunctions v0.3.29
  [c2834f40] + MLCore v1.0.0
⌃ [7e8f7934] + MLDataDevices v1.5.3
  [a7f614a8] + MLJBase v1.7.0
  [50ed68f4] + MLJEnsembles v0.4.3
⌅ [094fc8d1] + MLJFlux v0.5.1
  [6ee0df7b] + MLJLinearModels v0.10.0
  [e80e1ace] + MLJModelInterface v1.11.0
  [d8e11817] + MLStyle v0.4.17
  [f1d291b0] + MLUtils v0.4.8
  [1914dd2f] + MacroTools v0.5.15
  [dbeba491] + Metalhead v0.9.5
  [128add7d] + MicroCollections v0.2.0
  [e1d29d7a] + Missings v1.2.0
  [d41bc354] + NLSolversBase v7.9.0
  [872c559c] + NNlib v0.9.29
  [77ba4419] + NaNMath v1.1.2
  [71a1bf82] + NameResolution v0.1.5
  [0b1bfda6] + OneHotArrays v0.2.6
  [429524aa] + Optim v1.11.0
⌅ [3bd65402] + Optimisers v0.3.4
  [bac558e1] + OrderedCollections v1.8.0
  [90014a1f] + PDMats v0.11.32
  [d96e819e] + Parameters v0.12.3
  [570af359] + PartialFunctions v1.2.0
  [85a6dd25] + PositiveFactorizations v0.2.4
  [aea7be01] + PrecompileTools v1.2.1
  [21216c6a] + Preferences v1.4.3
  [8162dcfd] + PrettyPrint v0.2.0
  [08abe8d2] + PrettyTables v2.4.0
  [33c8b6b6] + ProgressLogging v0.1.4
  [92933f4c] + ProgressMeter v1.10.2
  [43287f4e] + PtrArrays v1.3.0
  [1fd47b50] + QuadGK v2.11.2
  [c1ae055f] + RealDot v0.1.0
  [3cdcf5f2] + RecipesBase v1.3.4
  [189a3867] + Reexport v1.2.2
  [42d2dcc6] + Referenceables v0.1.3
  [97f35ef4] + RequiredInterfaces v0.1.7
  [ae029012] + Requires v1.3.1
  [79098fc4] + Rmath v0.8.0
  [321657f4] + ScientificTypes v3.1.0
  [30f210dd] + ScientificTypesBase v3.0.0
  [7e506255] + ScopedValues v1.3.0
  [efcf1570] + Setfield v1.1.2
  [605ecd9f] + ShowCases v0.1.0
  [699a6c99] + SimpleTraits v0.9.4
  [a2af1166] + SortingAlgorithms v1.2.1
  [dc90abb0] + SparseInverseSubset v0.1.2
  [276daf66] + SpecialFunctions v2.5.0
  [171d559e] + SplittablesBase v0.1.15
  [90137ffa] + StaticArrays v1.9.13
  [1e83bf80] + StaticArraysCore v1.4.3
  [c062fc1d] + StatisticalMeasuresBase v0.1.2
  [64bff920] + StatisticalTraits v3.4.0
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.7.0
  [2913bbd2] + StatsBase v0.34.4
  [4c63d2b9] + StatsFuns v1.3.2
  [892a3eda] + StringManipulation v0.4.1
  [09ab397b] + StructArrays v0.7.0
  [3783bdb8] + TableTraits v1.0.1
  [bd369af6] + Tables v1.12.0
  [ac1d9e8a] + ThreadsX v0.1.12
  [3bb67fe8] + TranscodingStreams v0.11.3
  [28d57a85] + Transducers v0.4.84
  [3a884ed6] + UnPack v1.0.2
  [013be700] + UnsafeAtomics v0.3.0
⌅ [e88e6eb3] + Zygote v0.6.75
  [700de1a5] + ZygoteRules v0.2.7
  [dad2f222] + LLVMExtra_jll v0.0.35+0
  [efe28fd5] + OpenSpecFun_jll v0.5.6+0
  [f50d1b31] + Rmath_jll v0.5.1+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 v1.6.0
  [7b1f6079] + FileWatching v1.11.0
  [9fa8497b] + Future v1.11.0
  [b77e0a4c] + InteractiveUtils v1.11.0
  [dc6e5ff7] + 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 v1.11.0
  [56ddb016] + Logging v1.11.0
  [d6f4376e] + Markdown v1.11.0
  [a63ad114] + Mmap v1.11.0
  [ca575930] + NetworkOptions v1.2.0
  [44cfe95a] + Pkg v1.12.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v0.7.0
  [9e88b42a] + Serialization v1.11.0
  [6462fe0b] + Sockets v1.11.0
  [2f01184e] + SparseArrays v1.12.0
  [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 v1.2.0+0
  [deac9b47] + LibCURL_jll v8.6.0+0
  [e37daf67] + LibGit2_jll v1.8.0+0
  [29816b5a] + LibSSH2_jll v1.11.0+1
  [c8ffd9c3] + MbedTLS_jll v2.28.6+1
  [14a3606d] + MozillaCACerts_jll v2024.11.26
  [4536629a] + OpenBLAS_jll v0.3.28+3
  [05823500] + OpenLibm_jll v0.8.1+3
  [bea87d4a] + SuiteSparse_jll v7.8.0+1
  [83775a58] + Zlib_jll v1.3.1+1
  [8e850b90] + libblastrampoline_jll v5.11.2+0
  [8e850ede] + nghttp2_jll v1.63.0+1
  [3f19e933] + p7zip_jll v17.5.0+1
        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 6.03s


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# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 1340.6s


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# Testing
#

     Testing ConformalPrediction
        Test Could not use exact versions of packages in manifest. Re-resolving dependencies
    Updating `/tmp/jl_3hwX4h/Project.toml`
  [4c88cf16] ↑ Aqua v0.8.4 ⇒ v0.8.11
  [5224ae11] ↑ CompatHelperLocal v0.1.26 ⇒ v0.1.27
  [98bfc277] + ConformalPrediction v0.1.13
  [e30172f5] ↑ Documenter v1.3.0 ⇒ v1.9.0
⌅ [f6006082] ↑ EvoTrees v0.16.6 ⇒ v0.16.9
⌅ [7acf609c] ↑ LightGBM v0.6.1 ⇒ v0.7.2
  [add582a8] ↑ MLJ v0.19.5 ⇒ v0.20.7
  [c6f25543] ↑ MLJDecisionTreeInterface v0.4.1 ⇒ v0.4.2
⌅ [094fc8d1] ↑ MLJFlux v0.4.0 ⇒ v0.5.1
  [e80e1ace] ↑ MLJModelInterface v1.9.5 ⇒ v1.11.0
  [91a5bcdd] ↑ Plots v1.40.2 ⇒ v1.40.11
  [bd7198b4] ↑ TaijaPlotting v1.0.7 ⇒ v1.3.0
  [8dfed614] ~ Test ⇒ v1.11.0
    Updating `/tmp/jl_3hwX4h/Manifest.toml`
  [47edcb42] + ADTypes v1.14.0
  [da404889] ↑ ARFFFiles v1.4.1 ⇒ v1.5.0
  [7d9f7c33] + Accessors v0.1.42
  [79e6a3ab] ↑ Adapt v4.0.3 ⇒ v4.3.0
  [66dad0bd] + AliasTables v1.1.3
  [4c88cf16] ↑ Aqua v0.8.4 ⇒ v0.8.11
  [dce04be8] ↑ ArgCheck v2.3.0 ⇒ v2.5.0
  [ec485272] ↑ ArnoldiMethod v0.2.0 ⇒ v0.4.0
  [4fba245c] ↑ ArrayInterface v7.9.0 ⇒ v7.18.0
  [a9b6321e] ↑ Atomix v0.1.0 ⇒ v1.1.1
  [a963bdd2] - AtomsBase v0.3.5
  [ab4f0b2a] - BFloat16s v0.4.2
  [198e06fe] ↑ BangBang v0.3.40 ⇒ v0.4.4
  [6e4b80f9] - BenchmarkTools v1.5.0
  [d1d4a3ce] ↑ BitFlags v0.1.8 ⇒ v0.1.9
  [e1450e63] - BufferedStreams v1.2.1
  [336ed68f] - CSV v0.10.13
  [052768ef] - CUDA v5.2.0
  [1af6417a] - CUDA_Runtime_Discovery v0.2.3
  [49dc2e85] - Calculus v0.5.1
  [af321ab8] ↑ CategoricalDistributions v0.1.14 ⇒ v0.1.15
⌅ [8e462317] + CausalInference v0.18.0
  [082447d4] ↑ ChainRules v1.63.0 ⇒ v1.72.3
  [d360d2e6] ↑ ChainRulesCore v1.23.0 ⇒ v1.25.1
  [46823bd8] - Chemfiles v0.10.41
  [523fee87] - CodecBzip2 v0.8.2
  [944b1d66] ↑ CodecZlib v0.7.4 ⇒ v0.7.8
  [35d6a980] ↑ ColorSchemes v3.24.0 ⇒ v3.29.0
⌅ [3da002f7] ↑ ColorTypes v0.11.4 ⇒ v0.11.5
  [5ae59095] ↑ Colors v0.12.10 ⇒ v0.13.0
  [bbf7d656] ↑ CommonSubexpressions v0.3.0 ⇒ v0.3.1
  [34da2185] ↑ Compat v4.14.0 ⇒ v4.16.0
  [5224ae11] ↑ CompatHelperLocal v0.1.26 ⇒ v0.1.27
  [f0e56b4a] ↑ ConcurrentUtilities v2.4.1 ⇒ v2.5.0
  [98bfc277] ↑ ConformalPrediction v0.1.6 ⇒ v0.1.13
  [187b0558] ↑ ConstructionBase v1.5.5 ⇒ v1.5.8
  [d38c429a] ↑ Contour v0.6.2 ⇒ v0.6.3
  [2f13d31b] ↑ CounterfactualExplanations v0.1.31 ⇒ v1.4.5
  [124859b0] - DataDeps v0.7.13
  [a93c6f00] ↑ DataFrames v1.6.1 ⇒ v1.7.0
  [864edb3b] ↑ DataStructures v0.18.18 ⇒ v0.18.22
  [b429d917] + DensityInterface v0.4.0
  [a0c0ee7d] + DifferentiationInterface v0.6.48
  [b4f34e82] ↑ Distances v0.10.11 ⇒ v0.10.12
  [31c24e10] ↑ Distributions v0.25.107 ⇒ v0.25.118
  [e30172f5] ↑ Documenter v1.3.0 ⇒ v1.9.0
  [fa6b7ba4] - DualNumbers v0.6.8
  [f446124b] + EnergySamplers v1.0.3
⌅ [f6006082] ↑ EvoTrees v0.16.6 ⇒ v0.16.9
  [460bff9d] ↑ ExceptionUnwrapping v0.1.10 ⇒ v0.1.11
  [e2ba6199] - ExprTools v0.1.10
  [411431e0] ↑ Extents v0.1.2 ⇒ v0.1.5
  [c87230d0] ↑ FFMPEG v0.4.1 ⇒ v0.4.2
  [cc61a311] ↑ FLoops v0.2.1 ⇒ v0.2.2
  [33837fe5] + FeatureSelection v0.2.2
  [5789e2e9] ↑ FileIO v1.16.3 ⇒ v1.17.0
  [48062228] ↑ FilePathsBase v0.9.21 ⇒ v0.9.24
  [1a297f60] ↑ FillArrays v1.9.3 ⇒ v1.13.0
  [6a86dc24] ↑ FiniteDiff v2.23.0 ⇒ v2.27.0
  [53c48c17] ↑ FixedPointNumbers v0.8.4 ⇒ v0.8.5
⌅ [587475ba] ↑ Flux v0.14.14 ⇒ v0.14.25
  [1fa38f19] ↑ Format v1.3.6 ⇒ v1.3.7
  [f6369f11] ↑ ForwardDiff v0.10.36 ⇒ v0.10.38
⌅ [d9f16b24] ↑ Functors v0.4.8 ⇒ v0.4.12
  [0c68f7d7] ↑ GPUArrays v10.0.2 ⇒ v11.2.2
  [46192b85] ↑ GPUArraysCore v0.1.6 ⇒ v0.2.0
  [61eb1bfa] - GPUCompiler v0.25.0
  [28b8d3ca] ↑ GR v0.73.3 ⇒ v0.73.13
  [92fee26a] - GZip v0.6.2
  [68eda718] + GeoFormatTypes v0.4.4
  [cf35fbd7] ↑ GeoInterface v1.3.3 ⇒ v1.4.1
  [5c1252a2] ↑ GeometryBasics v0.4.10 ⇒ v0.5.5
  [c27321d9] - Glob v1.3.1
  [86223c79] ↑ Graphs v1.9.0 ⇒ v1.12.0
  [f67ccb44] - HDF5 v0.17.1
  [cd3eb016] ↑ HTTP v1.10.4 ⇒ v1.10.15
  [076d061b] + HashArrayMappedTries v0.2.0
  [34004b35] ↑ HypergeometricFunctions v0.3.23 ⇒ v0.3.28
  [b5f81e59] ↑ IOCapture v0.2.4 ⇒ v0.2.5
  [7869d1d1] ↑ IRTools v0.4.12 ⇒ v0.4.14
  [c817782e] - ImageBase v0.1.7
  [a09fc81d] - ImageCore v0.10.2
  [4e3cecfd] - ImageShow v0.3.8
  [4846b161] + InferOpt v0.6.1
  [d25df0c9] ↑ Inflate v0.1.4 ⇒ v0.1.5
  [842dd82b] ↑ InlineStrings v1.4.0 ⇒ v1.4.3
  [7d512f48] - InternedStrings v0.7.0
  [3587e190] + InverseFunctions v0.1.17
  [41ab1584] ↑ InvertedIndices v1.3.0 ⇒ v1.3.1
  [92d709cd] ↑ IrrationalConstants v0.2.2 ⇒ v0.2.4
  [033835bb] ↑ JLD2 v0.4.46 ⇒ v0.5.12
  [1019f520] ↑ JLFzf v0.1.7 ⇒ v0.1.10
  [692b3bcd] ↑ JLLWrappers v1.5.0 ⇒ v1.7.0
  [0f8b85d8] - JSON3 v1.14.0
  [63c18a36] ↑ KernelAbstractions v0.9.18 ⇒ v0.9.34
  [ec8451be] + KernelFunctions v0.10.65
  [929cbde3] ↑ LLVM v6.6.1 ⇒ v9.2.0
  [8b046642] - LLVMLoopInfo v1.0.0
  [8ac3fa9e] + LRUCache v1.6.2
  [b964fa9f] ↑ LaTeXStrings v1.3.1 ⇒ v1.4.0
  [c52c1a26] ↑ LaplaceRedux v0.1.4 ⇒ v1.2.0
  [23fbe1c1] ↑ Latexify v0.16.2 ⇒ v0.16.6
  [0e77f7df] ↑ LazilyInitializedFields v1.2.2 ⇒ v1.3.0
  [8cdb02fc] - LazyModules v0.3.1
⌅ [92ad9a40] + LearnAPI v0.1.0
⌅ [7acf609c] ↑ LightGBM v0.6.1 ⇒ v0.7.2
  [d3d80556] ↑ LineSearches v7.2.0 ⇒ v7.3.0
  [7a12625a] ↑ LinearMaps v3.11.2 ⇒ v3.11.4
  [70f5e60a] + LinkedLists v0.1.1
  [2ab3a3ac] ↑ LogExpFunctions v0.3.27 ⇒ v0.3.29
  [aa2f6b4e] + LogarithmicNumbers v1.4.0
  [e6f89c97] ↑ LoggingExtras v1.0.3 ⇒ v1.1.0
  [30fc2ffe] - LossFunctions v0.11.1
  [23992714] - MAT v0.10.6
  [c2834f40] + MLCore v1.0.0
⌃ [7e8f7934] + MLDataDevices v1.5.3
  [eb30cadb] - MLDatasets v0.7.14
⌅ [64a0f543] ↑ MLFlowClient v0.4.6 ⇒ v0.5.1
  [add582a8] ↑ MLJ v0.19.5 ⇒ v0.20.7
  [45f359ea] + MLJBalancing v0.1.5
  [a7f614a8] ↑ MLJBase v0.21.14 ⇒ v1.7.0
  [c6f25543] ↑ MLJDecisionTreeInterface v0.4.1 ⇒ v0.4.2
  [50ed68f4] ↑ MLJEnsembles v0.3.3 ⇒ v0.4.3
  [7b7b8358] ↑ MLJFlow v0.1.1 ⇒ v0.5.0
⌅ [094fc8d1] ↑ MLJFlux v0.4.0 ⇒ v0.5.1
  [614be32b] ↑ MLJIteration v0.5.1 ⇒ v0.6.3
  [e80e1ace] ↑ MLJModelInterface v1.9.5 ⇒ v1.11.0
  [d491faf4] ↑ MLJModels v0.16.16 ⇒ v0.17.9
  [03970b2e] ↑ MLJTuning v0.7.4 ⇒ v0.8.8
  [f1d291b0] ↑ MLUtils v0.4.4 ⇒ v0.4.8
  [3da0fdf6] - MPIPreferences v0.1.10
  [1914dd2f] ↑ MacroTools v0.5.13 ⇒ v0.5.15
  [06eb3307] - ManifoldLearning v0.9.0
  [dbb5928d] - MappedArrays v0.4.2
  [b8f27783] - MathOptInterface v1.27.0
  [6fafb56a] + Memoization v0.2.2
  [626554b9] + MetaGraphs v0.8.0
  [dbeba491] ↑ Metalhead v0.9.3 ⇒ v0.9.5
  [128add7d] ↑ MicroCollections v0.1.4 ⇒ v0.2.0
  [e1d29d7a] ↑ Missings v1.1.0 ⇒ v1.2.0
  [e94cdb99] - MosaicViews v0.3.4
  [6f286f6a] ↑ MultivariateStats v0.9.0 ⇒ v0.10.3
  [d8a4904e] - MutableArithmetics v1.4.1
  [d41bc354] ↑ NLSolversBase v7.8.3 ⇒ v7.9.0
  [872c559c] ↑ NNlib v0.9.12 ⇒ v0.9.29
  [15e1cf62] - NPZ v0.4.3
  [5da4648a] - NVTX v0.3.4
  [77ba4419] ↑ NaNMath v1.0.2 ⇒ v1.1.2
  [b8a86587] ↑ NearestNeighbors v0.4.16 ⇒ v0.4.21
  [46757867] ↑ NetworkLayout v0.4.6 ⇒ v0.4.9
  [6fe1bfb0] ↑ OffsetArrays v1.13.0 ⇒ v1.16.0
  [0b1bfda6] ↑ OneHotArrays v0.2.5 ⇒ v0.2.6
  [8b6db2d4] ↑ OpenML v0.3.1 ⇒ v0.3.2
  [4d8831e6] ↑ OpenSSL v1.4.2 ⇒ v1.4.3
  [429524aa] ↑ Optim v1.9.2 ⇒ v1.11.0
⌅ [3bd65402] ↑ Optimisers v0.3.2 ⇒ v0.3.4
  [bac558e1] ↑ OrderedCollections v1.6.3 ⇒ v1.8.0
  [90014a1f] ↑ PDMats v0.11.31 ⇒ v0.11.32
  [5432bcbf] - PaddedViews v0.5.12
  [7b2266bf] - PeriodicTable v1.2.1
  [fbb45041] - Pickle v0.3.3
  [b98c9c47] - Pipe v1.3.0
  [ccf2f8ad] ↑ PlotThemes v3.1.0 ⇒ v3.3.0
  [995b91a9] ↑ PlotUtils v1.4.1 ⇒ v1.4.3
  [91a5bcdd] ↑ Plots v1.40.2 ⇒ v1.40.11
  [08abe8d2] ↑ PrettyTables v2.3.1 ⇒ v2.4.0
  [92933f4c] ↑ ProgressMeter v1.10.0 ⇒ v1.10.2
  [43287f4e] + PtrArrays v1.3.0
  [1fd47b50] ↑ QuadGK v2.9.4 ⇒ v2.11.2
  [74087812] - Random123 v1.7.0
  [e6cf234a] - RandomNumbers v1.5.3
  [42d2dcc6] + Referenceables v0.1.3
  [97f35ef4] + RequiredInterfaces v0.1.7
  [ae029012] ↑ Requires v1.3.0 ⇒ v1.3.1
  [79098fc4] ↑ Rmath v0.7.1 ⇒ v0.8.0
  [321657f4] ↑ ScientificTypes v3.0.2 ⇒ v3.1.0
  [7e506255] + ScopedValues v1.3.0
  [91c51154] ↑ SentinelArrays v1.4.1 ⇒ v1.4.8
  [efcf1570] ↑ Setfield v1.1.1 ⇒ v1.1.2
  [777ac1f9] ↑ SimpleBufferStream v1.1.0 ⇒ v1.2.0
  [276daf66] ↑ SpecialFunctions v2.3.1 ⇒ v2.5.0
  [860ef19b] ↑ StableRNGs v1.0.1 ⇒ v1.0.2
  [cae243ae] - StackViews v0.1.1
  [90137ffa] ↑ StaticArrays v1.9.3 ⇒ v1.9.13
  [1e83bf80] ↑ StaticArraysCore v1.4.2 ⇒ v1.4.3
⌅ [a19d573c] + StatisticalMeasures v0.1.7
  [c062fc1d] + StatisticalMeasuresBase v0.1.2
  [64bff920] ↑ StatisticalTraits v3.2.0 ⇒ v3.4.0
  [10745b16] ↑ Statistics v1.10.0 ⇒ v1.11.1
  [2913bbd2] ↑ StatsBase v0.33.21 ⇒ v0.34.4
  [4c63d2b9] ↑ StatsFuns v1.3.1 ⇒ v1.3.2
  [5e0ebb24] - Strided v1.2.3
  [69024149] - StringEncodings v0.3.7
  [892a3eda] ↑ StringManipulation v0.3.4 ⇒ v0.4.1
  [09ab397b] ↑ StructArrays v0.6.18 ⇒ v0.7.0
  [856f2bd8] - StructTypes v1.10.0
  [bd369af6] ↑ Tables v1.11.1 ⇒ v1.12.0
  [3eeacb1d] + TabularDisplay v1.3.0
  [10284c91] + TaijaBase v1.2.3
  [bd7198b4] ↑ TaijaPlotting v1.0.7 ⇒ v1.3.0
  [ac1d9e8a] + ThreadsX v0.1.12
  [a759f4b9] - TimerOutputs v0.5.23
  [3bb67fe8] ↑ TranscodingStreams v0.10.5 ⇒ v0.11.3
  [28d57a85] ↑ Transducers v0.4.80 ⇒ v0.4.84
  [592b5752] + Trapz v2.0.3
  [bc48ee85] ↑ Tullio v0.3.7 ⇒ v0.3.8
  [9d95972d] - TupleTools v1.5.0
  [1986cc42] ↑ Unitful v1.19.0 ⇒ v1.22.0
  [a7773ee8] - UnitfulAtomic v1.0.0
  [45397f5d] ↑ UnitfulLatexify v1.6.3 ⇒ v1.6.4
  [013be700] ↑ UnsafeAtomics v0.2.1 ⇒ v0.3.0
  [d80eeb9a] - UnsafeAtomicsLLVM v0.1.3
  [ea10d353] - WeakRefStrings v1.4.2
  [76eceee3] - WorkerUtilities v1.6.1
  [a5390f91] - ZipFile v0.10.1
⌅ [e88e6eb3] ↑ Zygote v0.6.69 ⇒ v0.6.75
  [700de1a5] ↑ ZygoteRules v0.2.5 ⇒ v0.2.7
  [02a925ec] - cuDNN v1.3.0
  [6e34b625] ↑ Bzip2_jll v1.0.8+1 ⇒ v1.0.9+0
  [4ee394cb] - CUDA_Driver_jll v0.7.0+1
  [76a88914] - CUDA_Runtime_jll v0.11.1+0
  [62b44479] - CUDNN_jll v8.9.4+0
  [83423d85] ↑ Cairo_jll v1.18.0+1 ⇒ v1.18.4+0
  [78a364fa] - Chemfiles_jll v0.10.4+0
  [ee1fde0b] + Dbus_jll v1.14.10+0
  [2702e6a9] ↑ EpollShim_jll v0.0.20230411+0 ⇒ v0.0.20230411+1
  [2e619515] ↑ Expat_jll v2.5.0+0 ⇒ v2.6.5+0
  [a3f928ae] ↑ Fontconfig_jll v2.13.93+0 ⇒ v2.15.0+0
  [d7e528f0] ↑ FreeType2_jll v2.13.1+0 ⇒ v2.13.3+1
  [559328eb] ↑ FriBidi_jll v1.0.10+0 ⇒ v1.0.16+0
  [0656b61e] ↑ GLFW_jll v3.3.9+0 ⇒ v3.4.0+2
  [d2c73de3] ↑ GR_jll v0.73.3+0 ⇒ v0.73.13+0
  [f8c6e375] ↑ Git_jll v2.44.0+1 ⇒ v2.47.1+0
⌃ [7746bdde] ↑ Glib_jll v2.80.0+0 ⇒ v2.82.4+0
  [3b182d85] ↑ Graphite2_jll v1.3.14+0 ⇒ v1.3.14+1
  [0234f1f7] - HDF5_jll v1.14.2+1
  [2e76f6c2] ↑ HarfBuzz_jll v2.8.1+1 ⇒ v8.5.0+0
  [e33a78d0] - Hwloc_jll v2.10.0+0
  [aacddb02] ↑ JpegTurbo_jll v3.0.2+0 ⇒ v3.1.1+0
  [9c1d0b0a] - JuliaNVTXCallbacks_jll v0.2.1+0
  [c1c5ebd0] ↑ LAME_jll v3.100.1+0 ⇒ v3.100.2+0
  [88015f11] ↑ LERC_jll v3.0.0+1 ⇒ v4.0.1+0
  [dad2f222] ↑ LLVMExtra_jll v0.0.29+0 ⇒ v0.0.35+0
  [1d63c593] ↑ LLVMOpenMP_jll v15.0.7+0 ⇒ v18.1.7+0
  [dd4b983a] ↑ LZO_jll v2.10.1+0 ⇒ v2.10.3+0
⌅ [e9f186c6] ↑ Libffi_jll v3.2.2+1 ⇒ v3.2.2+2
  [d4300ac3] ↑ Libgcrypt_jll v1.8.7+0 ⇒ v1.11.0+0
  [7e76a0d4] ↑ Libglvnd_jll v1.6.0+0 ⇒ v1.7.0+0
  [7add5ba3] ↑ Libgpg_error_jll v1.42.0+0 ⇒ v1.51.1+0
  [94ce4f54] ↑ Libiconv_jll v1.17.0+0 ⇒ v1.18.0+0
  [4b2f31a3] ↑ Libmount_jll v2.39.3+0 ⇒ v2.40.3+0
  [89763e89] ↑ Libtiff_jll v4.5.1+1 ⇒ v4.7.1+0
  [38a345b3] ↑ Libuuid_jll v2.39.3+1 ⇒ v2.40.3+0
⌅ [0e4427ef] + LightGBM_jll v3.3.5+1
  [7cb0a576] - MPICH_jll v4.2.0+0
  [f1f71cc9] - MPItrampoline_jll v5.3.2+0
  [9237b28f] - MicrosoftMPI_jll v10.1.4+2
  [e98f9f5b] - NVTX_jll v3.1.0+2
  [fe0851c0] - OpenMPI_jll v5.0.2+0
  [458c3c95] ↑ OpenSSL_jll v3.0.13+0 ⇒ v3.0.16+0
  [efe28fd5] ↑ OpenSpecFun_jll v0.5.5+0 ⇒ v0.5.6+0
  [91d4177d] ↑ Opus_jll v1.3.2+0 ⇒ v1.3.3+0
  [32165bc3] - PMIx_jll v4.2.7+0
  [36c8627f] + Pango_jll v1.56.1+0
  [30392449] ↑ Pixman_jll v0.42.2+0 ⇒ v0.44.2+0
⌅ [c0090381] ↑ Qt6Base_jll v6.5.3+1 ⇒ v6.7.1+1
⌅ [629bc702] + Qt6Declarative_jll v6.7.1+2
⌅ [ce943373] + Qt6ShaderTools_jll v6.7.1+1
⌃ [e99dba38] + Qt6Wayland_jll v6.7.1+1
  [f50d1b31] ↑ Rmath_jll v0.4.0+0 ⇒ v0.5.1+0
  [a2964d1f] ↑ Wayland_jll v1.21.0+1 ⇒ v1.21.0+2
  [2381bf8a] ↑ Wayland_protocols_jll v1.31.0+0 ⇒ v1.36.0+0
  [02c8fc9c] ↑ XML2_jll v2.12.5+0 ⇒ v2.13.6+1
  [aed1982a] ↑ XSLT_jll v1.1.34+0 ⇒ v1.1.42+0
  [ffd25f8a] ↑ XZ_jll v5.6.1+0 ⇒ v5.6.4+1
  [f67eecfb] ↑ Xorg_libICE_jll v1.0.10+1 ⇒ v1.1.1+0
  [c834827a] ↑ Xorg_libSM_jll v1.2.3+0 ⇒ v1.2.4+0
  [4f6342f7] ↑ Xorg_libX11_jll v1.8.6+0 ⇒ v1.8.6+3
  [0c0b7dd1] ↑ Xorg_libXau_jll v1.0.11+0 ⇒ v1.0.12+0
  [935fb764] ↑ Xorg_libXcursor_jll v1.2.0+4 ⇒ v1.2.3+0
  [a3789734] ↑ Xorg_libXdmcp_jll v1.1.4+0 ⇒ v1.1.5+0
  [1082639a] ↑ Xorg_libXext_jll v1.3.4+4 ⇒ v1.3.6+3
  [d091e8ba] ↑ Xorg_libXfixes_jll v5.0.3+4 ⇒ v6.0.0+0
  [a51aa0fd] ↑ Xorg_libXi_jll v1.7.10+4 ⇒ v1.8.2+0
  [d1454406] ↑ Xorg_libXinerama_jll v1.1.4+4 ⇒ v1.1.5+0
  [ec84b674] ↑ Xorg_libXrandr_jll v1.5.2+4 ⇒ v1.5.4+0
  [ea2f1a96] ↑ Xorg_libXrender_jll v0.9.10+4 ⇒ v0.9.11+1
  [14d82f49] ↑ Xorg_libpthread_stubs_jll v0.1.1+0 ⇒ v0.1.2+0
  [c7cfdc94] ↑ Xorg_libxcb_jll v1.15.0+0 ⇒ v1.17.0+3
  [cc61e674] ↑ Xorg_libxkbfile_jll v1.1.2+0 ⇒ v1.1.2+1
  [35661453] ↑ Xorg_xkbcomp_jll v1.4.6+0 ⇒ v1.4.6+1
  [c5fb5394] ↑ Xorg_xtrans_jll v1.5.0+0 ⇒ v1.5.1+0
  [3161d3a3] ↑ Zstd_jll v1.5.5+0 ⇒ v1.5.7+1
  [214eeab7] ↑ fzf_jll v0.43.0+0 ⇒ v0.56.3+0
  [1a1c6b14] ↑ gperf_jll v3.1.1+0 ⇒ v3.1.1+1
  [477f73a3] - libaec_jll v1.1.2+0
  [a4ae2306] ↑ libaom_jll v3.4.0+0 ⇒ v3.11.0+0
  [0ac62f75] ↑ libass_jll v0.15.1+0 ⇒ v0.15.2+0
  [1183f4f0] + libdecor_jll v0.2.2+0
  [1080aeaf] - libevent_jll v2.1.13+1
  [f638f0a6] ↑ libfdk_aac_jll v2.0.2+0 ⇒ v2.0.3+0
  [b53b4c65] ↑ libpng_jll v1.6.43+1 ⇒ v1.6.47+0
  [f27f6e37] ↑ libvorbis_jll v1.3.7+1 ⇒ v1.3.7+2
  [eb928a42] - prrte_jll v3.0.2+0
  [d8fb68d0] ↑ xkbcommon_jll v1.4.1+1 ⇒ v1.4.1+2
  [0dad84c5] ↑ ArgTools v1.1.1 ⇒ v1.1.2
  [56f22d72] ~ Artifacts ⇒ v1.11.0
  [2a0f44e3] ~ Base64 ⇒ v1.11.0
  [ade2ca70] ~ Dates ⇒ v1.11.0
  [8ba89e20] ~ Distributed ⇒ v1.11.0
  [7b1f6079] ~ FileWatching ⇒ v1.11.0
  [9fa8497b] ~ Future ⇒ v1.11.0
  [b77e0a4c] ~ InteractiveUtils ⇒ v1.11.0
  [dc6e5ff7] + JuliaSyntaxHighlighting v1.12.0
  [4af54fe1] ~ LazyArtifacts ⇒ v1.11.0
  [76f85450] ~ LibGit2 ⇒ v1.11.0
  [8f399da3] ~ Libdl ⇒ v1.11.0
  [37e2e46d] ~ LinearAlgebra ⇒ v1.11.0
  [56ddb016] ~ Logging ⇒ v1.11.0
  [d6f4376e] ~ Markdown ⇒ v1.11.0
  [a63ad114] ~ Mmap ⇒ v1.11.0
  [44cfe95a] ↑ Pkg v1.10.0 ⇒ v1.12.0
  [de0858da] ~ Printf ⇒ v1.11.0
  [9abbd945] - Profile
  [3fa0cd96] ~ REPL ⇒ v1.11.0
  [9a3f8284] ~ Random ⇒ v1.11.0
  [9e88b42a] ~ Serialization ⇒ v1.11.0
  [1a1011a3] ~ SharedArrays ⇒ v1.11.0
  [6462fe0b] ~ Sockets ⇒ v1.11.0
  [2f01184e] ↑ SparseArrays v1.10.0 ⇒ v1.12.0
  [f489334b] + StyledStrings v1.11.0
  [8dfed614] ~ Test ⇒ v1.11.0
  [cf7118a7] ~ UUIDs ⇒ v1.11.0
  [4ec0a83e] ~ Unicode ⇒ v1.11.0
  [e66e0078] ↑ CompilerSupportLibraries_jll v1.1.0+0 ⇒ v1.2.0+0
  [deac9b47] ↑ LibCURL_jll v8.4.0+0 ⇒ v8.6.0+0
  [e37daf67] ↑ LibGit2_jll v1.6.4+0 ⇒ v1.8.0+0
  [c8ffd9c3] ↑ MbedTLS_jll v2.28.2+1 ⇒ v2.28.6+1
  [14a3606d] ↑ MozillaCACerts_jll v2023.1.10 ⇒ v2024.11.26
  [4536629a] ↑ OpenBLAS_jll v0.3.23+4 ⇒ v0.3.28+3
  [05823500] ↑ OpenLibm_jll v0.8.1+2 ⇒ v0.8.1+3
  [efcefdf7] ↑ PCRE2_jll v10.42.0+1 ⇒ v10.44.0+0
  [bea87d4a] ↑ SuiteSparse_jll v7.2.1+1 ⇒ v7.8.0+1
  [83775a58] ↑ Zlib_jll v1.2.13+1 ⇒ v1.3.1+1
  [8e850b90] ↑ libblastrampoline_jll v5.8.0+1 ⇒ v5.11.2+0
  [8e850ede] ↑ nghttp2_jll v1.52.0+1 ⇒ v1.63.0+1
  [3f19e933] ↑ p7zip_jll v17.4.0+2 ⇒ v17.5.0+1
        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_3hwX4h/Project.toml`
  [4c88cf16] Aqua v0.8.11
  [5224ae11] CompatHelperLocal v0.1.27
  [98bfc277] ConformalPrediction v0.1.13
  [7806a523] DecisionTree v0.12.4
  [e30172f5] Documenter v1.9.0
⌅ [f6006082] EvoTrees v0.16.9
⌅ [7acf609c] LightGBM v0.7.2
  [add582a8] MLJ v0.20.7
  [c6f25543] MLJDecisionTreeInterface v0.4.2
⌅ [094fc8d1] MLJFlux v0.5.1
  [6ee0df7b] MLJLinearModels v0.10.0
  [e80e1ace] MLJModelInterface v1.11.0
  [636a865e] NearestNeighborModels v0.2.3
  [91a5bcdd] Plots v1.40.11
  [bd7198b4] TaijaPlotting v1.3.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_3hwX4h/Manifest.toml`
  [47edcb42] ADTypes v1.14.0
  [a4c015fc] ANSIColoredPrinters v0.0.1
  [da404889] ARFFFiles v1.5.0
  [621f4979] AbstractFFTs v1.5.0
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.42
  [79e6a3ab] Adapt v4.3.0
  [66dad0bd] AliasTables v1.1.3
  [4c88cf16] Aqua v0.8.11
  [dce04be8] ArgCheck v2.5.0
  [ec485272] ArnoldiMethod v0.4.0
  [7d9fca2a] Arpack v0.5.4
  [4fba245c] ArrayInterface v7.18.0
  [a9b6321e] Atomix v1.1.1
  [fbb218c0] BSON v0.3.9
  [198e06fe] BangBang v0.4.4
  [9718e550] Baselet v0.1.1
  [d1d4a3ce] BitFlags v0.1.9
  [fa961155] CEnum v0.5.0
  [324d7699] CategoricalArrays v0.10.8
  [af321ab8] CategoricalDistributions v0.1.15
⌅ [8e462317] CausalInference v0.18.0
  [082447d4] ChainRules v1.72.3
  [d360d2e6] ChainRulesCore v1.25.1
  [944b1d66] CodecZlib v0.7.8
  [35d6a980] ColorSchemes v3.29.0
⌅ [3da002f7] ColorTypes v0.11.5
⌃ [c3611d14] ColorVectorSpace v0.10.0
  [5ae59095] Colors v0.13.0
  [861a8166] Combinatorics v1.0.2
  [bbf7d656] CommonSubexpressions v0.3.1
  [34da2185] Compat v4.16.0
  [5224ae11] CompatHelperLocal v0.1.27
  [a33af91c] CompositionsBase v0.1.2
  [ed09eef8] ComputationalResources v0.3.2
  [f0e56b4a] ConcurrentUtilities v2.5.0
  [98bfc277] ConformalPrediction v0.1.13
  [187b0558] ConstructionBase v1.5.8
  [6add18c4] ContextVariablesX v0.1.3
  [d38c429a] Contour v0.6.3
  [2f13d31b] CounterfactualExplanations v1.4.5
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
  [a93c6f00] DataFrames v1.7.0
  [864edb3b] DataStructures v0.18.22
  [e2d170a0] DataValueInterfaces v1.0.0
  [7806a523] DecisionTree v0.12.4
  [244e2a9f] DefineSingletons v0.1.2
  [8bb1440f] DelimitedFiles v1.9.1
  [b429d917] DensityInterface v0.4.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [a0c0ee7d] DifferentiationInterface v0.6.48
  [b4f34e82] Distances v0.10.12
  [31c24e10] Distributions v0.25.118
  [ffbed154] DocStringExtensions v0.9.3
  [e30172f5] Documenter v1.9.0
  [792122b4] EarlyStopping v0.3.0
  [f446124b] EnergySamplers v1.0.3
⌅ [f6006082] EvoTrees v0.16.9
  [460bff9d] ExceptionUnwrapping v0.1.11
  [411431e0] Extents v0.1.5
  [c87230d0] FFMPEG v0.4.2
  [cc61a311] FLoops v0.2.2
  [b9860ae5] FLoopsBase v0.1.1
  [33837fe5] FeatureSelection v0.2.2
  [5789e2e9] FileIO v1.17.0
  [48062228] FilePathsBase v0.9.24
  [1a297f60] FillArrays v1.13.0
  [6a86dc24] FiniteDiff v2.27.0
  [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
  [68eda718] GeoFormatTypes v0.4.4
  [cf35fbd7] GeoInterface v1.4.1
  [5c1252a2] GeometryBasics v0.5.5
  [d7ba0133] Git v1.3.1
  [86223c79] Graphs v1.12.0
  [42e2da0e] Grisu v1.0.2
  [cd3eb016] HTTP v1.10.15
  [076d061b] HashArrayMappedTries v0.2.0
  [34004b35] HypergeometricFunctions v0.3.28
  [b5f81e59] IOCapture v0.2.5
  [7869d1d1] IRTools v0.4.14
  [4846b161] InferOpt v0.6.1
  [d25df0c9] Inflate v0.1.5
  [22cec73e] InitialValues v0.3.1
  [842dd82b] InlineStrings v1.4.3
  [3587e190] InverseFunctions v0.1.17
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⌅ [92ad9a40] LearnAPI v0.1.0
⌅ [7acf609c] LightGBM v0.7.2
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⌃ [7e8f7934] MLDataDevices v1.5.3
⌅ [64a0f543] MLFlowClient v0.5.1
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  [7b7b8358] MLJFlow v0.5.0
⌅ [094fc8d1] MLJFlux v0.5.1
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⌅ [3bd65402] Optimisers v0.3.4
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⌅ [a19d573c] StatisticalMeasures v0.1.7
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  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.0
  [2913bbd2] StatsBase v0.34.4
  [4c63d2b9] StatsFuns v1.3.2
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  [09ab397b] StructArrays v0.7.0
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  [bd369af6] Tables v1.12.0
  [3eeacb1d] TabularDisplay v1.3.0
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  [28d57a85] Transducers v0.4.84
  [592b5752] Trapz v2.0.3
  [bc48ee85] Tullio v0.3.8
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  [41fe7b60] Unzip v0.2.0
⌅ [e88e6eb3] Zygote v0.6.75
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⌅ [68821587] Arpack_jll v3.5.1+1
  [6e34b625] Bzip2_jll v1.0.9+0
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  [ee1fde0b] Dbus_jll v1.14.10+0
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⌅ [b22a6f82] FFMPEG_jll v4.4.4+1
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  [d2c73de3] GR_jll v0.73.13+0
  [78b55507] Gettext_jll v0.21.0+0
  [f8c6e375] Git_jll v2.47.1+0
⌃ [7746bdde] Glib_jll v2.82.4+0
  [3b182d85] Graphite2_jll v1.3.14+1
  [2e76f6c2] HarfBuzz_jll v8.5.0+0
  [aacddb02] JpegTurbo_jll v3.1.1+0
  [c1c5ebd0] LAME_jll v3.100.2+0
  [88015f11] LERC_jll v4.0.1+0
  [dad2f222] LLVMExtra_jll v0.0.35+0
  [1d63c593] LLVMOpenMP_jll v18.1.7+0
  [dd4b983a] LZO_jll v2.10.3+0
⌅ [e9f186c6] Libffi_jll v3.2.2+2
  [d4300ac3] Libgcrypt_jll v1.11.0+0
  [7e76a0d4] Libglvnd_jll v1.7.0+0
  [7add5ba3] Libgpg_error_jll v1.51.1+0
  [94ce4f54] Libiconv_jll v1.18.0+0
  [4b2f31a3] Libmount_jll v2.40.3+0
  [89763e89] Libtiff_jll v4.7.1+0
  [38a345b3] Libuuid_jll v2.40.3+0
⌅ [0e4427ef] LightGBM_jll v3.3.5+1
  [e7412a2a] Ogg_jll v1.3.5+1
  [458c3c95] OpenSSL_jll v3.0.16+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [91d4177d] Opus_jll v1.3.3+0
  [36c8627f] Pango_jll v1.56.1+0
  [30392449] Pixman_jll v0.44.2+0
⌅ [c0090381] Qt6Base_jll v6.7.1+1
⌅ [629bc702] Qt6Declarative_jll v6.7.1+2
⌅ [ce943373] Qt6ShaderTools_jll v6.7.1+1
⌃ [e99dba38] Qt6Wayland_jll v6.7.1+1
  [f50d1b31] Rmath_jll v0.5.1+0
  [a44049a8] Vulkan_Loader_jll v1.3.243+0
  [a2964d1f] Wayland_jll v1.21.0+2
  [2381bf8a] Wayland_protocols_jll v1.36.0+0
  [02c8fc9c] XML2_jll v2.13.6+1
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  [ffd25f8a] XZ_jll v5.6.4+1
  [f67eecfb] Xorg_libICE_jll v1.1.1+0
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  [4f6342f7] Xorg_libX11_jll v1.8.6+3
  [0c0b7dd1] Xorg_libXau_jll v1.0.12+0
  [935fb764] Xorg_libXcursor_jll v1.2.3+0
  [a3789734] Xorg_libXdmcp_jll v1.1.5+0
  [1082639a] Xorg_libXext_jll v1.3.6+3
  [d091e8ba] Xorg_libXfixes_jll v6.0.0+0
  [a51aa0fd] Xorg_libXi_jll v1.8.2+0
  [d1454406] Xorg_libXinerama_jll v1.1.5+0
  [ec84b674] Xorg_libXrandr_jll v1.5.4+0
  [ea2f1a96] Xorg_libXrender_jll v0.9.11+1
  [14d82f49] Xorg_libpthread_stubs_jll v0.1.2+0
  [c7cfdc94] Xorg_libxcb_jll v1.17.0+3
  [cc61e674] Xorg_libxkbfile_jll v1.1.2+1
  [e920d4aa] Xorg_xcb_util_cursor_jll v0.1.4+0
  [12413925] Xorg_xcb_util_image_jll v0.4.0+1
  [2def613f] Xorg_xcb_util_jll v0.4.0+1
  [975044d2] Xorg_xcb_util_keysyms_jll v0.4.0+1
  [0d47668e] Xorg_xcb_util_renderutil_jll v0.3.9+1
  [c22f9ab0] Xorg_xcb_util_wm_jll v0.4.1+1
  [35661453] Xorg_xkbcomp_jll v1.4.6+1
  [33bec58e] Xorg_xkeyboard_config_jll v2.39.0+0
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  [1a1c6b14] gperf_jll v3.1.1+1
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  [1183f4f0] libdecor_jll v0.2.2+0
  [2db6ffa8] libevdev_jll v1.11.0+0
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⌅ [1270edf5] x264_jll v2021.5.5+0
⌅ [dfaa095f] x265_jll v3.5.0+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: Method definition _dummy_backedge() in module Memoization at /home/pkgeval/.julia/packages/Memoization/ON3Za/src/Memoization.jl:49 overwritten at /home/pkgeval/.julia/packages/Memoization/ON3Za/src/Memoization.jl:65.
┌ Warning: Unable to determine HTML(edit_link = ...) from remote HEAD branch, defaulting to "master".
│ Calling `git remote` failed with an exception. Set JULIA_DEBUG=Documenter to see the error.
│ Unless this is due to a configuration error, the relevant variable should be set explicitly.
└ @ Documenter ~/.julia/packages/Documenter/QLA7E/src/utilities/utilities.jl:655
[ Info: SetupBuildDirectory: setting up build directory.
[ Info: Doctest: running doctests.
[ Info: Skipped ExpandTemplates step (doctest only).
[ Info: Skipped CrossReferences step (doctest only).
[ Info: Skipped CheckDocument step (doctest only).
[ Info: Skipped Populate step (doctest only).
[ Info: Skipped RenderDocument step (doctest only).
Test Summary:                 | Pass  Total   Time
Doctests: ConformalPrediction |    1      1  49.0s
WARNING: using deprecated binding ColorTypes.RGB1 in Colors.
, use XRGB instead.
WARNING: using deprecated binding Colors.RGB1 in PlotUtils.
, use ColorTypes.XRGB{T} where T<:Union{AbstractFloat, FixedPointNumbers.FixedPoint{T, f} where f where T<:Integer} instead.
WARNING: PlotUtils.RGB1 is deprecated, use ColorTypes.XRGB{T} where T<:Union{AbstractFloat, FixedPointNumbers.FixedPoint{T, f} where f where T<:Integer} instead.
  likely near /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/aqua.jl:3
WARNING: using deprecated binding ColorTypes.RGB4 in Colors.
, use RGBX instead.
WARNING: using deprecated binding Colors.RGB4 in PlotUtils.
, use ColorTypes.RGBX{T} where T<:Union{AbstractFloat, FixedPointNumbers.FixedPoint{T, f} where f where T<:Integer} instead.
WARNING: PlotUtils.RGB4 is deprecated, use ColorTypes.RGBX{T} where T<:Union{AbstractFloat, FixedPointNumbers.FixedPoint{T, f} where f where T<:Integer} instead.
  likely near /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/aqua.jl:3
[ Info: For silent loading, specify `verbosity=0`. 
import NearestNeighborModels ✔
[ Info: Training machine(AdaptiveInductiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: Training machine(AdaptiveInductiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: Training machine(AdaptiveInductiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: Training machine(NaiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: Training machine(NaiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: Training machine(NaiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = KNNClassifier(K = 5, …), …), …).
[ Info: For silent loading, specify `verbosity=0`. 
import EvoTrees ✔
┌ Info: Training machine(AdaptiveInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123)
└ , …), …).
┌ Info: Training machine(AdaptiveInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 8016, 7014, 286))
└ , …), …).
┌ Info: Training machine(AdaptiveInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 15030, 14028, 172))
└ , …), …).
┌ Info: Training machine(NaiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 22044, 21042, 158))
└ , …), …).
┌ Info: Training machine(NaiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 36072, 35070, 30))
└ , …), …).
┌ Info: Training machine(NaiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 49098, 48096, 504))
└ , …), …).
┌ Info: Training machine(SimpleInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 63126, 62124, 76))
└ , …), …).
┌ Info: Training machine(SimpleInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 160320, 159318, 779))
└ , …), …).
┌ Info: Training machine(SimpleInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 167334, 166332, 665))
└ , …), …).
[ Info: For silent loading, specify `verbosity=0`. 
import MLJDecisionTreeInterface ✔
[ Info: Training machine(AdaptiveInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(AdaptiveInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(AdaptiveInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(NaiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(NaiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(NaiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …).
[ Info: For silent loading, specify `verbosity=0`. 
import MLJLinearModels ✔
[ Info: Training machine(AdaptiveInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: Training machine(AdaptiveInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: Training machine(AdaptiveInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: Training machine(NaiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: Training machine(NaiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: Training machine(NaiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: Training machine(SimpleInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: Training machine(SimpleInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: Training machine(SimpleInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …).
┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}}
│   optim_options: Optim.Options{Float64, Nothing}
└   lbfgs_options: @NamedTuple{} NamedTuple()
[ Info: For silent loading, specify `verbosity=0`. 
import MLJDecisionTreeInterface ✔
[ Info: Training machine(AdaptiveInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(AdaptiveInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(AdaptiveInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(NaiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(NaiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(NaiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: Training machine(SimpleInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …).
[ Info: For silent loading, specify `verbosity=0`. 
import MLJLinearModels ✔
┌ Warning: This test is skipped as the method is not suitable for Quantile Regression
└ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80
[ Info: Training machine(CVPlusRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(CVPlusRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(NaiveRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.Analytical
│   iterative: Bool false
└   max_inner: Int64 200
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(NaiveRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.Analytical
│   iterative: Bool false
└   max_inner: Int64 200
[ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(JackknifePlusAbRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifePlusAbRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(JackknifePlusRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifePlusRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(CVMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(CVMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(JackknifeRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.Analytical
│   iterative: Bool false
└   max_inner: Int64 200
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifeRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.Analytical
│   iterative: Bool false
└   max_inner: Int64 200
[ Info: Training machine(JackknifeMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifeMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = RidgeRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(SimpleInductiveRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.Analytical
│   iterative: Bool false
└   max_inner: Int64 200
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(SimpleInductiveRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.Analytical
│   iterative: Bool false
└   max_inner: Int64 200
[ Info: For silent loading, specify `verbosity=0`. 
import MLJLinearModels ✔
┌ Warning: This test is skipped as the method is not suitable for Quantile Regression
└ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80
[ Info: Training machine(CVPlusRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(CVPlusRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(NaiveRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.ProxGrad
│   accel: Bool true
│   max_iter: Int64 1000
│   tol: Float64 0.0001
│   max_inner: Int64 100
│   beta: Float64 0.8
└   gram: Bool false
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(NaiveRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.ProxGrad
│   accel: Bool true
│   max_iter: Int64 1000
│   tol: Float64 0.0001
│   max_inner: Int64 100
│   beta: Float64 0.8
└   gram: Bool false
[ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(JackknifePlusAbRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifePlusAbRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(JackknifePlusRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifePlusRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(CVMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(CVMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(JackknifeRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.ProxGrad
│   accel: Bool true
│   max_iter: Int64 1000
│   tol: Float64 0.0001
│   max_inner: Int64 100
│   beta: Float64 0.8
└   gram: Bool false
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifeRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.ProxGrad
│   accel: Bool true
│   max_iter: Int64 1000
│   tol: Float64 0.0001
│   max_inner: Int64 100
│   beta: Float64 0.8
└   gram: Bool false
[ Info: Training machine(JackknifeMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(JackknifeMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = LassoRegressor(lambda = 1.0, …), …), …).
[ Info: Training machine(SimpleInductiveRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.ProxGrad
│   accel: Bool true
│   max_iter: Int64 1000
│   tol: Float64 0.0001
│   max_inner: Int64 100
│   beta: Float64 0.8
└   gram: Bool false
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
[ Info: Training machine(SimpleInductiveRegressor(model = LassoRegressor(lambda = 1.0, …), …), …).
┌ Info: Solver: MLJLinearModels.ProxGrad
│   accel: Bool true
│   max_iter: Int64 1000
│   tol: Float64 0.0001
│   max_inner: Int64 100
│   beta: Float64 0.8
└   gram: Bool false
[ Info: For silent loading, specify `verbosity=0`. 
import EvoTrees ✔
┌ Warning: This test is skipped as the method is not suitable for Quantile Regression
└ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80
┌ Info: Training machine(CVPlusRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123)
└ , …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
┌ Info: Training machine(CVPlusRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 43086, 42084, 916))
└ , …), …).
┌ Info: Training machine(NaiveRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 84168, 83166, 435))
└ , …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
┌ Info: Training machine(NaiveRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 91182, 90180, 721))
└ , …), …).
┌ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 98196, 97194, 607))
└ , …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
┌ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 233466, 232464, 341))
└ , …), …).
┌ Info: Training machine(JackknifePlusAbRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 356712, 355710, 101))
└ , …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
┌ Info: Training machine(JackknifePlusAbRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 490980, 489978, 836))
└ , …), …).
┌ Info: Training machine(JackknifePlusRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 614226, 613224, 593))
└ , …), …).
[ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable.
┌ Info: Training machine(JackknifePlusRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE}
│  - nrounds: 100
│  - L2: 0.0
│  - lambda: 0.0
│  - gamma: 0.0
│  - eta: 0.1
│  - max_depth: 6
│  - min_weight: 1.0
│  - rowsample: 1.0
│  - colsample: 1.0
│  - nbins: 64
│  - alpha: 0.5
│  - monotone_constraints: Dict{Int64, Int64}()
│  - tree_type: binary
│  - rng: Random.MersenneTwister(123, (0, 3973932, 3972930, 532))
└ , …), …).

======================================================================================
Information request received. A stacktrace will print followed by a 1.0 second profile
======================================================================================

cmd: /opt/julia/bin/julia 234 running 1 of 1

signal (10): User defined signal 1
_setindex! at ./array.jl:991 [inlined]
setindex! at ./array.jl:986 [inlined]
_fill! at ./array.jl:333 [inlined]
fill! at ./array.jl:329 [inlined]
zeros at ./array.jl:596 [inlined]
zeros at ./array.jl:592 [inlined]
zeros at ./array.jl:590 [inlined]
#TrainNode##4 at ./none (unknown line) [inlined]
iterate at ./generator.jl:48 [inlined]
collect at ./array.jl:790
TrainNode at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/structs.jl:21
unknown function (ip: 0x7d0419b84994) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
#init_core##0 at ./none (unknown line)
iterate at ./generator.jl:48 [inlined]
collect_to! at ./array.jl:848
collect_to_with_first! at ./array.jl:826
unknown function (ip: 0x7d0419b86d0b) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
collect at ./array.jl:800
init_core at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/init.jl:99
fit at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/MLJ.jl:7
fit at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/MLJ.jl:3 [inlined]
fit at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/src/conformal_models/transductive_regression.jl:197
unknown function (ip: 0x7d04189f8e3e) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
do_apply at /source/src/builtins.c:839
#fit_only!#56 at /home/pkgeval/.julia/packages/MLJBase/7nGJF/src/machines.jl:692
fit_only! at /home/pkgeval/.julia/packages/MLJBase/7nGJF/src/machines.jl:617 [inlined]
#fit!#64 at /home/pkgeval/.julia/packages/MLJBase/7nGJF/src/machines.jl:789 [inlined]
fit! at /home/pkgeval/.julia/packages/MLJBase/7nGJF/src/machines.jl:786
unknown function (ip: 0x7d04189ed626) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:43 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:39 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:30 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:26 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
top-level scope at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:23
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_invoke at /source/src/gf.c:3366
jl_toplevel_eval_flex at /source/src/toplevel.c:1059
jl_toplevel_eval_flex at /source/src/toplevel.c:1010
ijl_toplevel_eval at /source/src/toplevel.c:1082
ijl_toplevel_eval_in at /source/src/toplevel.c:1127
eval at ./boot.jl:485
include_string at ./loading.jl:2846
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
_include at ./loading.jl:2906
include at ./Base.jl:301
IncludeInto at ./Base.jl:302
jfptr_IncludeInto_69051.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
do_call at /source/src/interpreter.c:125
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:687
eval_body at /source/src/interpreter.c:562
eval_body at /source/src/interpreter.c:562
jl_interpret_toplevel_thunk at /source/src/interpreter.c:896
jl_toplevel_eval_flex at /source/src/toplevel.c:1070
jl_toplevel_eval_flex at /source/src/toplevel.c:1010
ijl_toplevel_eval at /source/src/toplevel.c:1082
ijl_toplevel_eval_in at /source/src/toplevel.c:1127
eval at ./boot.jl:485
include_string at ./loading.jl:2846
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
_include at ./loading.jl:2906
include at ./Base.jl:301
IncludeInto at ./Base.jl:302
jfptr_IncludeInto_69051.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
do_call at /source/src/interpreter.c:125
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:687
jl_interpret_toplevel_thunk at /source/src/interpreter.c:896
jl_toplevel_eval_flex at /source/src/toplevel.c:1070
jl_toplevel_eval_flex at /source/src/toplevel.c:1010
ijl_toplevel_eval at /source/src/toplevel.c:1082
ijl_toplevel_eval_in at /source/src/toplevel.c:1127
eval at ./boot.jl:485
exec_options at ./client.jl:295
_start at ./client.jl:558
jfptr__start_108457.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
true_main at /source/src/jlapi.c:922
jl_repl_entrypoint at /source/src/jlapi.c:1081
main at /source/cli/loader_exe.c:58
unknown function (ip: 0x7d0445d7c249) at /lib/x86_64-linux-gnu/libc.so.6
__libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S
unknown function (ip: (nil)) at (unknown file)

==============================================================
Profile collected. A report will print at the next yield point
==============================================================

┌ 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/v1.12/Profile/src/Profile.jl:1353
Overhead ╎ [+additional indent] Count File:Line  Function
=========================================================
Thread 1 (default) Task 0x00007d037ce5ecb0 Total snapshots: 1. Utilization: 100%
 ╎1 @Base/…adingconstructs.jl:177  (::Base.Threads.var"#threading_run##0#thread…
 ╎ 1 @Base/…dingconstructs.jl:243  #grow_tree!##0
 ╎  1 @Base/…dingconstructs.jl:276  (::EvoTrees.var"#grow_tree!##0#grow_tree!##…
 ╎   1 @EvoTrees/src/fit.jl:95  macro expansion
 ╎    1 @EvoTrees/…fit-utils.jl:319  update_gains!(node::EvoTrees.TrainNode{Sub…
 ╎     1 @Base/broadcast.jl:897  materialize!
 ╎    ╎ 1 @Base/broadcast.jl:900  materialize!
 ╎    ╎  1 @Base/broadcast.jl:942  copyto!
 ╎    ╎   1 @Base/broadcast.jl:989  copyto!
 ╎    ╎    1 @Base/simdloop.jl:77  macro expansion
 ╎    ╎     1 @Base/broadcast.jl:990  macro expansion
 ╎    ╎    ╎ 1 @Base/…imensional.jl:743  setindex!
 ╎    ╎    ╎  1 @Base/array.jl:997  setindex!
 ╎    ╎    ╎   1 @Base/array.jl:1003  _setindex!


======================================================================================
Information request received. A stacktrace will print followed by a 1.0 second profile
======================================================================================

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:454
poptask at ./task.jl:1187
wait at ./task.jl:1199
#wait#551 at ./condition.jl:141
wait at ./condition.jl:136 [inlined]
wait at ./process.jl:694
wait at ./process.jl:687
jfptr_wait_97191.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
subprocess_handler at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:2377
unknown function (ip: 0x71ecc437f2a3) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
#201 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:2317
withenv at ./env.jl:265
#186 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:2138
with_temp_env at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:1996
#182 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:2105
#mktempdir#21 at ./file.jl:899
unknown function (ip: 0x71ecc436f1ac) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
mktempdir at ./file.jl:895
mktempdir at ./file.jl:895
#sandbox#178 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:2052 [inlined]
sandbox at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:2044
unknown function (ip: 0x71ecc436d901) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
#test#189 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:2302
test at /source/usr/share/julia/stdlib/v1.12/Pkg/src/Operations.jl:2214 [inlined]
#test#170 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/API.jl:481
test at /source/usr/share/julia/stdlib/v1.12/Pkg/src/API.jl:460
unknown function (ip: 0x71ecc436d531) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
#test#84 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/API.jl:159
unknown function (ip: 0x71ecc4364168) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
test at /source/usr/share/julia/stdlib/v1.12/Pkg/src/API.jl:148
#test#82 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/API.jl:147
test at /source/usr/share/julia/stdlib/v1.12/Pkg/src/API.jl:147 [inlined]
#test#81 at /source/usr/share/julia/stdlib/v1.12/Pkg/src/API.jl:146 [inlined]
test at /source/usr/share/julia/stdlib/v1.12/Pkg/src/API.jl:146
unknown function (ip: 0x71ecc43625cf) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
do_call at /source/src/interpreter.c:125
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:687
eval_body at /source/src/interpreter.c:562
eval_body at /source/src/interpreter.c:562
jl_interpret_toplevel_thunk at /source/src/interpreter.c:896
jl_toplevel_eval_flex at /source/src/toplevel.c:1070
jl_toplevel_eval_flex at /source/src/toplevel.c:1010
ijl_toplevel_eval at /source/src/toplevel.c:1082
ijl_toplevel_eval_in at /source/src/toplevel.c:1127
eval at ./boot.jl:485
include_string at ./loading.jl:2846
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
_include at ./loading.jl:2906
include at ./Base.jl:300
exec_options at ./client.jl:329
_start at ./client.jl:558
jfptr__start_108457.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
true_main at /source/src/jlapi.c:922
jl_repl_entrypoint at /source/src/jlapi.c:1081
main at /source/cli/loader_exe.c:58
unknown function (ip: 0x71ecc61c8249) at /lib/x86_64-linux-gnu/libc.so.6
__libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S
unknown function (ip: (nil)) at (unknown file)

==============================================================
Profile collected. A report will print at the next yield point
==============================================================

┌ 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/v1.12/Profile/src/Profile.jl:1353
Overhead ╎ [+additional indent] Count File:Line  Function
=========================================================
Thread 1 (default) Task 0x000071ecb8000010 Total snapshots: 1. Utilization: 0%
 ╎1 @Base/client.jl:558  _start()
 ╎ 1 @Base/client.jl:329  exec_options(opts::Base.JLOptions)
 ╎  1 @Base/Base.jl:300  include(mod::Module, _path::String)
 ╎   1 @Base/loading.jl:2906  _include(mapexpr::Function, mod::Module, _path::S…
 ╎    1 @Base/loading.jl:2846  include_string(mapexpr::typeof(identity), mod::M…
 ╎     1 @Base/boot.jl:485  eval(m::Module, e::Any)
 ╎    ╎ 1 @Pkg/src/API.jl:146  kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(…
 ╎    ╎  1 @Pkg/src/API.jl:146  #test#81
 ╎    ╎   1 @Pkg/src/API.jl:147  test
 ╎    ╎    1 @Pkg/src/API.jl:147  test(pkgs::Vector{String}; kwargs::Base.Pairs…
 ╎    ╎     1 @Pkg/src/API.jl:148  kwcall(::@NamedTuple{julia_args::Cmd}, ::typ…
 ╎    ╎    ╎ 1 @Pkg/src/API.jl:159  test(pkgs::Vector{Pkg.Types.PackageSpec}; i…
 ╎    ╎    ╎  1 @Pkg/src/API.jl:460  kwcall(::@NamedTuple{julia_args::Cmd, io::…
 ╎    ╎    ╎   1 @Pkg/src/API.jl:481  test(ctx::Pkg.Types.Context, pkgs::Vector…
 ╎    ╎    ╎    1 @Pkg/…Operations.jl:2214  test
 ╎    ╎    ╎     1 @Pkg/…perations.jl:2302  test(ctx::Pkg.Types.Context, pkgs::…
 ╎    ╎    ╎    ╎ 1 @Pkg/…perations.jl:2044  kwcall(::@NamedTuple{preferences::…
 ╎    ╎    ╎    ╎  1 @Pkg/…perations.jl:2052  #sandbox#178
 ╎    ╎    ╎    ╎   1 @Base/file.jl:895  mktempdir(fn::Function)
 ╎    ╎    ╎    ╎    1 @Base/file.jl:895  mktempdir(fn::Function, parent::Strin…
 ╎    ╎    ╎    ╎     1 @Base/file.jl:899  mktempdir(fn::Pkg.Operations.var"#18…
 ╎    ╎    ╎    ╎    ╎ 1 @Pkg/…rations.jl:2105  (::Pkg.Operations.var"#182#183"…
 ╎    ╎    ╎    ╎    ╎  1 @Pkg/…rations.jl:1996  with_temp_env(fn::Pkg.Operatio…
 ╎    ╎    ╎    ╎    ╎   1 @Pkg/…ations.jl:2138  (::Pkg.Operations.var"#186#187…
 ╎    ╎    ╎    ╎    ╎    1 @Base/env.jl:265  withenv(::Pkg.Operations.var"#201…
 ╎    ╎    ╎    ╎    ╎     1 @Pkg/…tions.jl:2317  (::Pkg.Operations.var"#201#20…
 ╎    ╎    ╎    ╎    ╎    ╎ 1 @Pkg/…tions.jl:2377  subprocess_handler(cmd::Cmd,…
 ╎    ╎    ╎    ╎    ╎    ╎  1 @Base/…cess.jl:687  wait(x::Base.Process)
 ╎    ╎    ╎    ╎    ╎    ╎   1 @Base/…cess.jl:694  wait(x::Base.Process, syncd…
 ╎    ╎    ╎    ╎    ╎    ╎    1 @Base/…ion.jl:136  wait
 ╎    ╎    ╎    ╎    ╎    ╎     1 @Base/…ion.jl:141  wait(c::Base.GenericCondit…
 ╎    ╎    ╎    ╎    ╎    ╎    ╎ 1 @Base/…sk.jl:1199  wait()
 ╎    ╎    ╎    ╎    ╎    ╎    ╎  1 @Base/…sk.jl:1187  poptask(W::Base.Intrusiv…


[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:454

[234] signal 15: Terminated
in expression starting at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:22
poptask at ./task.jl:1187
popfirst! at ./task.jl:894
wait at ./task.jl:1199
trypoptask at ./task.jl:1167
#wait#551 at ./condition.jl:141
poptask at ./task.jl:1185
wait at ./condition.jl:136 [inlined]
_trywait at ./asyncevent.jl:145
wait at ./task.jl:1199
profile_printing_listener at ./Base.jl:326
#wait#551 at ./condition.jl:141
#start_profile_listener##0 at ./Base.jl:346
wait at ./condition.jl:136 [inlined]
_wait at ./task.jl:312
threading_run at ./threadingconstructs.jl:191
macro expansion at ./threadingconstructs.jl:213 [inlined]
predict! at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/predict.jl:2
unknown function (ip: 0x7d04189826b2) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
#_predict#94 at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/predict.jl:103
_predict at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/predict.jl:90 [inlined]
#predict#93 at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/predict.jl:87
predict at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/predict.jl:84 [inlined]
predict at /home/pkgeval/.julia/packages/EvoTrees/73o4j/src/MLJ.jl:45 [inlined]
#43 at ./none (unknown line)
unknown function (ip: 0x7d04189f67d2) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
iterate at ./generator.jl:48 [inlined]
collect_to! at ./array.jl:848
collect_to_with_first! at ./array.jl:826
unknown function (ip: 0x7d04189f6965) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
collect at ./array.jl:800
predict at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/src/conformal_models/transductive_regression.jl:228
unknown function (ip: 0x7d04189f612d) at (unknown file)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
macro expansion at /home/pkgeval/.julia/packages/TaijaPlotting/ZxgZe/src/ConformalPrediction/regression.jl:40 [inlined]
apply_recipe at /home/pkgeval/.julia/packages/RecipesBase/BRe07/src/RecipesBase.jl:300
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
do_apply at /source/src/builtins.c:839
_process_userrecipes! at /home/pkgeval/.julia/packages/RecipesPipeline/BGM3l/src/user_recipe.jl:38
recipe_pipeline! at /home/pkgeval/.julia/packages/RecipesPipeline/BGM3l/src/RecipesPipeline.jl:72
_plot! at /home/pkgeval/.julia/packages/Plots/3u4B6/src/plot.jl:223
#plot#147 at /home/pkgeval/.julia/packages/Plots/3u4B6/src/plot.jl:102
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
do_apply at /source/src/builtins.c:839
plot at /home/pkgeval/.julia/packages/Plots/3u4B6/src/plot.jl:93
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:59 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:49 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:39 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:30 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:26 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.12/Test/src/Test.jl:1724 [inlined]
top-level scope at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:23
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_invoke at /source/src/gf.c:3366
jl_toplevel_eval_flex at /source/src/toplevel.c:1059
jl_toplevel_eval_flex at /source/src/toplevel.c:1010
ijl_toplevel_eval at /source/src/toplevel.c:1082
ijl_toplevel_eval_in at /source/src/toplevel.c:1127
jfptr_YY.start_profile_listenerYY.YY.0_111230.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
start_task at /source/src/task.c:1281
unknown function (ip: (nil)) at (unknown file)
Allocations: 34335203 (Pool: 34333219; Big: 1984); GC: 35
eval at ./boot.jl:485
include_string at ./loading.jl:2846
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
_include at ./loading.jl:2906
include at ./Base.jl:301
IncludeInto at ./Base.jl:302
jfptr_IncludeInto_69051.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
do_call at /source/src/interpreter.c:125
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:687
eval_body at /source/src/interpreter.c:562
eval_body at /source/src/interpreter.c:562
jl_interpret_toplevel_thunk at /source/src/interpreter.c:896
jl_toplevel_eval_flex at /source/src/toplevel.c:1070
jl_toplevel_eval_flex at /source/src/toplevel.c:1010
ijl_toplevel_eval at /source/src/toplevel.c:1082
ijl_toplevel_eval_in at /source/src/toplevel.c:1127
eval at ./boot.jl:485
include_string at ./loading.jl:2846
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
_include at ./loading.jl:2906
include at ./Base.jl:301
IncludeInto at ./Base.jl:302
jfptr_IncludeInto_69051.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
do_call at /source/src/interpreter.c:125
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:687
jl_interpret_toplevel_thunk at /source/src/interpreter.c:896
jl_toplevel_eval_flex at /source/src/toplevel.c:1070
jl_toplevel_eval_flex at /source/src/toplevel.c:1010
ijl_toplevel_eval at /source/src/toplevel.c:1082
ijl_toplevel_eval_in at /source/src/toplevel.c:1127
eval at ./boot.jl:485
exec_options at ./client.jl:295
_start at ./client.jl:558
jfptr__start_108457.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:3359 [inlined]
ijl_apply_generic at /source/src/gf.c:3547
jl_apply at /source/src/julia.h:2244 [inlined]
true_main at /source/src/jlapi.c:922
jl_repl_entrypoint at /source/src/jlapi.c:1081
main at /source/cli/loader_exe.c:58
unknown function (ip: 0x7d0445d7c249) 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: 638170336 (Pool: 638163851; Big: 6485); GC: 201

PkgEval terminated after 2733.48s: test duration exceeded the time limit