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1.5.1-pre-0d71d8cd8b.log
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Julia Version 1.5.1-pre.28
Commit 0d71d8cd8b (2020-08-14 20:35 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: Intel(R) Xeon(R) Silver 4114 CPU @ 2.20GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-9.0.1 (ORCJIT, skylake-avx512)
Environment:
JULIA_DEPOT_PATH = ::/usr/local/share/julia
JULIA_NUM_THREADS = 2
Resolving package versions...
Installed CompilerSupportLibraries_jll ─ v0.3.3+0
Installed Parsers ────────────────────── v1.0.10
Installed Syslogs ────────────────────── v0.3.0
Installed SpecialFunctions ───────────── v0.8.0
Installed QuadGK ─────────────────────── v2.4.0
Installed TranscodingStreams ─────────── v0.9.5
Installed StatsBase ──────────────────── v0.32.2
Installed TreeParzen ─────────────────── v0.1.1
Installed MbedTLS ────────────────────── v1.0.2
Installed Libiconv_jll ───────────────── v1.16.0+5
Installed PDMats ─────────────────────── v0.9.12
Installed CodeTracking ───────────────── v0.5.11
Installed MLJScientificTypes ─────────── v0.2.8
Installed DocStringExtensions ────────── v0.8.2
Installed DataStructures ─────────────── v0.17.20
Installed MLJBase ────────────────────── v0.13.10
Installed SortingAlgorithms ──────────── v0.3.1
Installed BinaryProvider ─────────────── v0.5.10
Installed MLJTuning ──────────────────── v0.3.6
Installed XML2_jll ───────────────────── v2.9.10+1
Installed ScientificTypes ────────────── v0.8.1
Installed UnPack ─────────────────────── v1.0.2
Installed Revise ─────────────────────── v2.7.3
Installed DataValueInterfaces ────────── v1.0.0
Installed CoverageTools ──────────────── v1.1.0
Installed Coverage ───────────────────── v1.1.1
Installed Zlib_jll ───────────────────── v1.2.11+15
Installed PrettyTables ───────────────── v0.9.1
Installed BSON ───────────────────────── v0.2.6
Installed Reexport ───────────────────── v0.2.0
Installed Mocking ────────────────────── v0.7.1
Installed TableTraits ────────────────── v1.0.0
Installed ProgressMeter ──────────────── v1.3.2
Installed CodecZlib ──────────────────── v0.7.0
Installed JuliaInterpreter ───────────── v0.7.24
Installed InvertedIndices ────────────── v1.0.0
Installed Missings ───────────────────── v0.4.3
Installed Compat ─────────────────────── v3.13.0
Installed IteratorInterfaceExtensions ── v1.0.0
Installed Tables ─────────────────────── v1.0.5
Installed FixedPointNumbers ──────────── v0.8.4
Installed JSON ───────────────────────── v0.21.0
Installed Distributions ──────────────── v0.22.6
Installed IniFile ────────────────────── v0.5.0
Installed Formatting ─────────────────── v0.4.1
Installed JLSO ───────────────────────── v2.3.2
Installed EzXML ──────────────────────── v1.1.0
Installed FillArrays ─────────────────── v0.8.14
Installed FilePathsBase ──────────────── v0.9.4
Installed HTTP ───────────────────────── v0.8.17
Installed LossFunctions ──────────────── v0.6.2
Installed RecipesBase ────────────────── v1.0.2
Installed URIParser ──────────────────── v0.4.1
Installed StatsFuns ──────────────────── v0.9.5
Installed OpenBLAS_jll ───────────────── v0.3.9+5
Installed Rmath ──────────────────────── v0.6.1
Installed OrderedCollections ─────────── v1.3.0
Installed CategoricalArrays ──────────── v0.8.1
Installed Arpack ─────────────────────── v0.4.0
Installed Memento ────────────────────── v1.1.0
Installed TimeZones ──────────────────── v1.3.2
Installed MLJModelInterface ──────────── v0.3.2
Installed Arpack_jll ─────────────────── v3.5.0+3
Installed ColorTypes ─────────────────── v0.10.8
Installed DataAPI ────────────────────── v1.3.0
Installed LoweredCodeUtils ───────────── v0.4.7
Installed Parameters ─────────────────── v0.12.1
Installed ComputationalResources ─────── v0.3.2
Installed BinDeps ────────────────────── v1.0.1
Installed ExprTools ──────────────────── v0.1.1
Installed Crayons ────────────────────── v4.0.3
Installed MbedTLS_jll ────────────────── v2.16.6+1
Installed Rmath_jll ──────────────────── v0.2.2+1
Installed LearnBase ──────────────────── v0.4.1
Updating `~/.julia/environments/v1.5/Project.toml`
[eb66a70c] + TreeParzen v0.1.1
Updating `~/.julia/environments/v1.5/Manifest.toml`
[7d9fca2a] + Arpack v0.4.0
[68821587] + Arpack_jll v3.5.0+3
[fbb218c0] + BSON v0.2.6
[9e28174c] + BinDeps v1.0.1
[b99e7846] + BinaryProvider v0.5.10
[324d7699] + CategoricalArrays v0.8.1
[da1fd8a2] + CodeTracking v0.5.11
[944b1d66] + CodecZlib v0.7.0
[3da002f7] + ColorTypes v0.10.8
[34da2185] + Compat v3.13.0
[e66e0078] + CompilerSupportLibraries_jll v0.3.3+0
[ed09eef8] + ComputationalResources v0.3.2
[a2441757] + Coverage v1.1.1
[c36e975a] + CoverageTools v1.1.0
[a8cc5b0e] + Crayons v4.0.3
[9a962f9c] + DataAPI v1.3.0
[864edb3b] + DataStructures v0.17.20
[e2d170a0] + DataValueInterfaces v1.0.0
[31c24e10] + Distributions v0.22.6
[ffbed154] + DocStringExtensions v0.8.2
[e2ba6199] + ExprTools v0.1.1
[8f5d6c58] + EzXML v1.1.0
[48062228] + FilePathsBase v0.9.4
[1a297f60] + FillArrays v0.8.14
[53c48c17] + FixedPointNumbers v0.8.4
[59287772] + Formatting v0.4.1
[cd3eb016] + HTTP v0.8.17
[83e8ac13] + IniFile v0.5.0
[41ab1584] + InvertedIndices v1.0.0
[82899510] + IteratorInterfaceExtensions v1.0.0
[9da8a3cd] + JLSO v2.3.2
[682c06a0] + JSON v0.21.0
[aa1ae85d] + JuliaInterpreter v0.7.24
[7f8f8fb0] + LearnBase v0.4.1
[94ce4f54] + Libiconv_jll v1.16.0+5
[30fc2ffe] + LossFunctions v0.6.2
[6f1432cf] + LoweredCodeUtils v0.4.7
[a7f614a8] + MLJBase v0.13.10
[e80e1ace] + MLJModelInterface v0.3.2
[2e2323e0] + MLJScientificTypes v0.2.8
[03970b2e] + MLJTuning v0.3.6
[739be429] + MbedTLS v1.0.2
[c8ffd9c3] + MbedTLS_jll v2.16.6+1
[f28f55f0] + Memento v1.1.0
[e1d29d7a] + Missings v0.4.3
[78c3b35d] + Mocking v0.7.1
[4536629a] + OpenBLAS_jll v0.3.9+5
[bac558e1] + OrderedCollections v1.3.0
[90014a1f] + PDMats v0.9.12
[d96e819e] + Parameters v0.12.1
[69de0a69] + Parsers v1.0.10
[08abe8d2] + PrettyTables v0.9.1
[92933f4c] + ProgressMeter v1.3.2
[1fd47b50] + QuadGK v2.4.0
[3cdcf5f2] + RecipesBase v1.0.2
[189a3867] + Reexport v0.2.0
[295af30f] + Revise v2.7.3
[79098fc4] + Rmath v0.6.1
[f50d1b31] + Rmath_jll v0.2.2+1
[321657f4] + ScientificTypes v0.8.1
[a2af1166] + SortingAlgorithms v0.3.1
[276daf66] + SpecialFunctions v0.8.0
[2913bbd2] + StatsBase v0.32.2
[4c63d2b9] + StatsFuns v0.9.5
[cea106d9] + Syslogs v0.3.0
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v1.0.5
[f269a46b] + TimeZones v1.3.2
[3bb67fe8] + TranscodingStreams v0.9.5
[eb66a70c] + TreeParzen v0.1.1
[30578b45] + URIParser v0.4.1
[3a884ed6] + UnPack v1.0.2
[02c8fc9c] + XML2_jll v2.9.10+1
[83775a58] + Zlib_jll v1.2.11+15
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[7b1f6079] + FileWatching
[9fa8497b] + Future
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building SpecialFunctions → `~/.julia/packages/SpecialFunctions/ne2iw/deps/build.log`
Building TimeZones ───────→ `~/.julia/packages/TimeZones/v0mfN/deps/build.log`
Testing TreeParzen
Status `/tmp/jl_fHW76y/Project.toml`
[34da2185] Compat v3.13.0
[a2441757] Coverage v1.1.1
[7806a523] DecisionTree v0.10.9
[31c24e10] Distributions v0.22.6
[ffbed154] DocStringExtensions v0.8.2
[a7f614a8] MLJBase v0.13.10
[d491faf4] MLJModels v0.10.1
[03970b2e] MLJTuning v0.3.6
[295af30f] Revise v2.7.3
[276daf66] SpecialFunctions v0.8.0
[2913bbd2] StatsBase v0.32.2
[eb66a70c] TreeParzen v0.1.1
[ade2ca70] Dates
[10745b16] Statistics
[8dfed614] Test
Status `/tmp/jl_fHW76y/Manifest.toml`
[7d9fca2a] Arpack v0.4.0
[68821587] Arpack_jll v3.5.0+3
[fbb218c0] BSON v0.2.6
[9e28174c] BinDeps v1.0.1
[b99e7846] BinaryProvider v0.5.10
[324d7699] CategoricalArrays v0.8.1
[da1fd8a2] CodeTracking v0.5.11
[944b1d66] CodecZlib v0.7.0
[3da002f7] ColorTypes v0.10.8
[34da2185] Compat v3.13.0
[e66e0078] CompilerSupportLibraries_jll v0.3.3+0
[ed09eef8] ComputationalResources v0.3.2
[a2441757] Coverage v1.1.1
[c36e975a] CoverageTools v1.1.0
[a8cc5b0e] Crayons v4.0.3
[9a962f9c] DataAPI v1.3.0
[864edb3b] DataStructures v0.17.20
[e2d170a0] DataValueInterfaces v1.0.0
[7806a523] DecisionTree v0.10.9
[b4f34e82] Distances v0.8.2
[31c24e10] Distributions v0.22.6
[ffbed154] DocStringExtensions v0.8.2
[e2ba6199] ExprTools v0.1.1
[8f5d6c58] EzXML v1.1.0
[48062228] FilePathsBase v0.9.4
[1a297f60] FillArrays v0.8.14
[53c48c17] FixedPointNumbers v0.8.4
[59287772] Formatting v0.4.1
[cd3eb016] HTTP v0.8.17
[83e8ac13] IniFile v0.5.0
[41ab1584] InvertedIndices v1.0.0
[82899510] IteratorInterfaceExtensions v1.0.0
[9da8a3cd] JLSO v2.3.2
[682c06a0] JSON v0.21.0
[aa1ae85d] JuliaInterpreter v0.7.24
[7f8f8fb0] LearnBase v0.4.1
[94ce4f54] Libiconv_jll v1.16.0+5
[30fc2ffe] LossFunctions v0.6.2
[6f1432cf] LoweredCodeUtils v0.4.7
[a7f614a8] MLJBase v0.13.10
[e80e1ace] MLJModelInterface v0.3.2
[d491faf4] MLJModels v0.10.1
[2e2323e0] MLJScientificTypes v0.2.8
[03970b2e] MLJTuning v0.3.6
[739be429] MbedTLS v1.0.2
[c8ffd9c3] MbedTLS_jll v2.16.6+1
[f28f55f0] Memento v1.1.0
[e1d29d7a] Missings v0.4.3
[78c3b35d] Mocking v0.7.1
[6f286f6a] MultivariateStats v0.7.0
[4536629a] OpenBLAS_jll v0.3.9+5
[bac558e1] OrderedCollections v1.3.0
[90014a1f] PDMats v0.9.12
[d96e819e] Parameters v0.12.1
[69de0a69] Parsers v1.0.10
[08abe8d2] PrettyTables v0.9.1
[92933f4c] ProgressMeter v1.3.2
[1fd47b50] QuadGK v2.4.0
[3cdcf5f2] RecipesBase v1.0.2
[189a3867] Reexport v0.2.0
[ae029012] Requires v1.0.1
[295af30f] Revise v2.7.3
[79098fc4] Rmath v0.6.1
[f50d1b31] Rmath_jll v0.2.2+1
[321657f4] ScientificTypes v0.8.1
[6e75b9c4] ScikitLearnBase v0.5.0
[a2af1166] SortingAlgorithms v0.3.1
[276daf66] SpecialFunctions v0.8.0
[2913bbd2] StatsBase v0.32.2
[4c63d2b9] StatsFuns v0.9.5
[cea106d9] Syslogs v0.3.0
[3783bdb8] TableTraits v1.0.0
[bd369af6] Tables v1.0.5
[f269a46b] TimeZones v1.3.2
[3bb67fe8] TranscodingStreams v0.9.5
[eb66a70c] TreeParzen v0.1.1
[30578b45] URIParser v0.4.1
[3a884ed6] UnPack v1.0.2
[02c8fc9c] XML2_jll v2.9.10+1
[83775a58] Zlib_jll v1.2.11+15
[2a0f44e3] Base64
[ade2ca70] Dates
[8bb1440f] DelimitedFiles
[8ba89e20] Distributed
[7b1f6079] FileWatching
[9fa8497b] Future
[b77e0a4c] InteractiveUtils
[76f85450] LibGit2
[8f399da3] Libdl
[37e2e46d] LinearAlgebra
[56ddb016] Logging
[d6f4376e] Markdown
[a63ad114] Mmap
[44cfe95a] Pkg
[de0858da] Printf
[3fa0cd96] REPL
[9a3f8284] Random
[ea8e919c] SHA
[9e88b42a] Serialization
[1a1011a3] SharedArrays
[6462fe0b] Sockets
[2f01184e] SparseArrays
[10745b16] Statistics
[4607b0f0] SuiteSparse
[8dfed614] Test
[cf7118a7] UUIDs
[4ec0a83e] Unicode
[ Info: Bincount
┌ Warning: Assignment to `#s41` in soft scope is ambiguous because a global variable by the same name exists: `#s41` will be treated as a new local. Disambiguate by using `local #s41` to suppress this warning or `global #s41` to assign to the existing global variable.
└ @ ~/.julia/packages/MLJTuning/JZ7ZX/src/strategies/explicit.jl:3
[ Info: Configuration
[ Info: dfs
[ Info: graph
[ Info: Trials
[ Info: fmin: 3 / 3 trials carried out
[ Info: GMM1
[ Info: GMM1 Math and QGMM1 Math
[ Info: LGMM1
[ Info: Resolve
[ Info: Spaces
[ Info: Basic
[ Info: fmin: 50 / 50 trials carried out
[ Info: Successfully completed fmin
[ Info: fmin: 10 / 10 trials carried out
[ Info: Successfully completed fmin
[ Info: bjkomer/Squared
[ Info: fmin: 100 / 100 trials carried out
[ Info: Successfully completed fmin
[ Info: bjkomer/Function fitting
[ Info: fmin: 1000 / 1000 trials carried out
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[ Info: fmin: 1000 / 1000 trials carried out
[ Info: Successfully completed fmin
[ Info: fmin: 1000 / 1000 trials carried out
[ Info: Successfully completed fmin
[ Info: Official Cases
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[ Info: Successfully completed fmin
[ Info: fmin/Quadratic
[ Info: fmin: 50 / 50 trials carried out
[ Info: Successfully completed fmin
[ Info: fmin/Return Inf
[ Info: fmin: 50 / 50 trials carried out
[ Info: Successfully completed fmin
[ Info: fmin/Submit points to Trial
[ Info: fmin: 10 / 10 trials carried out
[ Info: Successfully completed fmin
[ Info: Silvrback
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[ Info: Vooban/Basic
[ Info: fmin: 100 / 100 trials carried out
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[ Info: Vooban/Find min
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[ Info: Successfully completed fmin
[ Info: Vooban/Status Fail skip
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[ Info: Successfully completed fmin
[ Info: hp_pchoice
[ Info: LogQuantNormal
[ Info: fmin: 100 / 100 trials carried out
[ Info: Successfully completed fmin
[ Info: fmin: 100 / 100 trials carried out
[ Info: Successfully completed fmin
[ Info: LogUniform
[ Info: QuantUniform
[ Info: fmin: 100 / 100 trials carried out
[ Info: Successfully completed fmin
[ Info: QuantNormal
[ Info: LogQuantUniform
[ Info: Uniform
[ Info: MLJ Unit tests
[ Info: MLJ integration
[ Info: Model metadata loaded from registry.
[ Info: lazy space
[ Info: Training [34mMachine{ProbabilisticTunedModel{MLJTreeParzenTuning,…}} @ 1…42[39m.
[ Info: Attempting to evaluate 100 models.
Evaluating over 20 metamodels: 0%[> ] ETA: N/A[KEvaluating over 20 metamodels: 5%[=> ] ETA: 0:07:29[KEvaluating over 20 metamodels: 10%[==> ] ETA: 0:03:37[KEvaluating over 20 metamodels: 15%[===> ] ETA: 0:02:17[KEvaluating over 20 metamodels: 20%[=====> ] ETA: 0:01:37[KEvaluating over 20 metamodels: 25%[======> ] ETA: 0:01:13[KEvaluating over 20 metamodels: 30%[=======> ] ETA: 0:00:57[KEvaluating over 20 metamodels: 35%[========> ] ETA: 0:00:45[KEvaluating over 20 metamodels: 40%[==========> ] ETA: 0:00:36[KEvaluating over 20 metamodels: 45%[===========> ] ETA: 0:00:30[KEvaluating over 20 metamodels: 50%[============> ] ETA: 0:00:24[KEvaluating over 20 metamodels: 55%[=============> ] ETA: 0:00:20[KEvaluating over 20 metamodels: 60%[===============> ] ETA: 0:00:16[KEvaluating over 20 metamodels: 65%[================> ] ETA: 0:00:13[KEvaluating over 20 metamodels: 70%[=================> ] ETA: 0:00:10[KEvaluating over 20 metamodels: 75%[==================> ] ETA: 0:00:08[KEvaluating over 20 metamodels: 80%[====================> ] ETA: 0:00:06[KEvaluating over 20 metamodels: 85%[=====================> ] ETA: 0:00:04[KEvaluating over 20 metamodels: 90%[======================> ] ETA: 0:00:03[KEvaluating over 20 metamodels: 95%[=======================> ] ETA: 0:00:01[KEvaluating over 20 metamodels: 100%[=========================] Time: 0:00:24[K
Evaluating over 100 metamodels: 0%[> ] ETA: N/A[KEvaluating over 100 metamodels: 1%[> ] ETA: 0:00:11[KEvaluating over 100 metamodels: 2%[> ] ETA: 0:00:09[KEvaluating over 100 metamodels: 3%[> ] ETA: 0:00:06[KEvaluating over 100 metamodels: 4%[=> ] ETA: 0:00:05[KEvaluating over 100 metamodels: 5%[=> ] ETA: 0:00:04[KEvaluating over 100 metamodels: 6%[=> ] ETA: 0:00:03[KEvaluating over 100 metamodels: 7%[=> ] ETA: 0:00:03[KEvaluating over 100 metamodels: 8%[==> ] ETA: 0:00:02[KEvaluating over 100 metamodels: 9%[==> ] ETA: 0:00:02[KEvaluating over 100 metamodels: 10%[==> ] ETA: 0:00:02[KEvaluating over 100 metamodels: 11%[==> ] ETA: 0:00:02[KEvaluating over 100 metamodels: 12%[===> ] ETA: 0:00:02[KEvaluating over 100 metamodels: 13%[===> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 14%[===> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 15%[===> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 16%[====> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 17%[====> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 18%[====> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 19%[====> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 20%[=====> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 21%[=====> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 22%[=====> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 23%[=====> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 24%[======> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 25%[======> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 26%[======> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 27%[======> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 28%[=======> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 29%[=======> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 30%[=======> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 31%[=======> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 32%[========> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 33%[========> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 34%[========> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 35%[========> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 36%[=========> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 37%[=========> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 38%[=========> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 39%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 40%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 41%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 42%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 43%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 44%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 45%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 46%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 47%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 48%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 49%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 50%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 51%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 52%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 53%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 54%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 55%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 56%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 57%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 58%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 59%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 60%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 61%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 62%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 63%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 64%[================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 65%[================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 66%[================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 67%[================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 68%[=================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 69%[=================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 70%[=================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 71%[=================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 72%[==================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 73%[==================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 74%[==================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 75%[==================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 76%[===================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 77%[===================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 78%[===================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 79%[===================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 80%[====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 81%[====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 82%[====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 83%[====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 84%[=====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 85%[=====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 86%[=====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 87%[=====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 88%[======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 89%[======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 90%[======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 91%[======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 92%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 93%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 94%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 95%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 96%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 97%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 98%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 99%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 100%[=========================] Time: 0:00:00[K
[ Info: single suggestion
[ Info: Training [34mMachine{ProbabilisticTunedModel{MLJTreeParzenTuning,…}} @ 1…70[39m.
[ Info: Attempting to evaluate 100 models.
Evaluating over 20 metamodels: 0%[> ] ETA: N/A[KEvaluating over 20 metamodels: 5%[=> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 10%[==> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 15%[===> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 20%[=====> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 25%[======> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 30%[=======> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 35%[========> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 40%[==========> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 45%[===========> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 50%[============> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 55%[=============> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 60%[===============> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 65%[================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 70%[=================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 75%[==================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 80%[====================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 85%[=====================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 90%[======================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 95%[=======================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 100%[=========================] Time: 0:00:00[K
Evaluating over 100 metamodels: 0%[> ] ETA: N/A[KEvaluating over 100 metamodels: 1%[> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 2%[> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 3%[> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 4%[=> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 5%[=> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 6%[=> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 7%[=> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 8%[==> ] ETA: 0:00:01[KEvaluating over 100 metamodels: 9%[==> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 10%[==> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 11%[==> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 12%[===> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 13%[===> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 14%[===> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 15%[===> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 16%[====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 17%[====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 18%[====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 19%[====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 20%[=====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 21%[=====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 22%[=====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 23%[=====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 24%[======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 25%[======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 26%[======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 27%[======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 28%[=======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 29%[=======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 30%[=======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 31%[=======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 32%[========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 33%[========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 34%[========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 35%[========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 36%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 37%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 38%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 39%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 40%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 41%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 42%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 43%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 44%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 45%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 46%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 47%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 48%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 49%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 50%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 51%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 52%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 53%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 54%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 55%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 56%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 57%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 58%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 59%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 60%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 61%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 62%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 63%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 64%[================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 65%[================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 66%[================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 67%[================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 68%[=================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 69%[=================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 70%[=================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 71%[=================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 72%[==================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 73%[==================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 74%[==================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 75%[==================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 76%[===================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 77%[===================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 78%[===================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 79%[===================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 80%[====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 81%[====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 82%[====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 83%[====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 84%[=====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 85%[=====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 86%[=====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 87%[=====================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 88%[======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 89%[======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 90%[======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 91%[======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 92%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 93%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 94%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 95%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 96%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 97%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 98%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 99%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 100%[=========================] Time: 0:00:00[K
[ Info: three suggestions
[ Info: Training [34mMachine{ProbabilisticTunedModel{MLJTreeParzenTuning,…}} @ 5…18[39m.
[ Info: Attempting to evaluate 100 models.
Evaluating over 20 metamodels: 0%[> ] ETA: N/A[KEvaluating over 20 metamodels: 5%[=> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 10%[==> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 15%[===> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 20%[=====> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 25%[======> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 30%[=======> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 35%[========> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 40%[==========> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 45%[===========> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 50%[============> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 55%[=============> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 60%[===============> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 65%[================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 70%[=================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 75%[==================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 80%[====================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 85%[=====================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 90%[======================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 95%[=======================> ] ETA: 0:00:00[KEvaluating over 20 metamodels: 100%[=========================] Time: 0:00:00[K
Evaluating over 100 metamodels: 0%[> ] ETA: N/A[KEvaluating over 100 metamodels: 1%[> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 2%[> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 3%[> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 4%[=> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 5%[=> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 6%[=> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 7%[=> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 8%[==> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 9%[==> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 10%[==> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 11%[==> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 12%[===> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 13%[===> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 14%[===> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 15%[===> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 16%[====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 17%[====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 18%[====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 19%[====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 20%[=====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 21%[=====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 22%[=====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 23%[=====> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 24%[======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 25%[======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 26%[======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 27%[======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 28%[=======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 29%[=======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 30%[=======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 31%[=======> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 32%[========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 33%[========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 34%[========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 35%[========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 36%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 37%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 38%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 39%[=========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 40%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 41%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 42%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 43%[==========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 44%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 45%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 46%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 47%[===========> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 48%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 49%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 50%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 51%[============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 52%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 53%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 54%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 55%[=============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 56%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 57%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 58%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 59%[==============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 60%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 61%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 62%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 63%[===============> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 64%[================> ] ETA: 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100 metamodels: 93%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 94%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 95%[=======================> ] ETA: 0:00:00[KEvaluating over 100 metamodels: 96%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 97%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 98%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 99%[========================>] ETA: 0:00:00[KEvaluating over 100 metamodels: 100%[=========================] Time: 0:00:00[K
[ Info: API
[ Info: SpacePrint
1: Dict{Symbol,TreeParzen.HP.PChoice} of 1 items
├args
└1: TreeParzen.HP.PChoice
├choice
├1: TreeParzen.Delayed.Param
│├label
│├1: :probchoice
│├obj
│└1: TreeParzen.Delayed.CategoricalIndex
│ ├probabilities
│ └1: Array{Float64,1} of 3 items
│ ├1: 0.1
│ ├2: 0.2
│ └3: 0.7
├options
└1: Array{Dict{Symbol,V} where V,1} of 3 items
├1: Dict{Symbol,Any} of 5 items
│├symbol
│├1: :test
│├int
│├2: 1
│├string
│├3: "test"
│├nothing
│├4: nothing
│├float
│└5: 1.0
├2: Dict{Symbol,TreeParzen.HP.Choice} of 1 items
│├dists
│└1: TreeParzen.HP.Choice
│ ├choice
│ ├1: TreeParzen.Delayed.Param
│ │├label
│ │├1: :dists
│ │├obj
│ │└1: TreeParzen.Delayed.RandIndex
│ │ ├upper
│ │ └1: 2
│ ├options
│ └1: Array{TreeParzen.Delayed.AbstractDelayed,1} of 2 items
│ ├1: TreeParzen.Delayed.Add
│ │├left
│ │├1: TreeParzen.HP.Uniform
│ ││├label
│ ││├1: :uniform
│ ││├obj
│ ││└1: TreeParzen.Delayed.Uniform
│ ││ ├low
│ ││ ├1: -10.0
│ ││ ├high
│ ││ └1: 10.0
│ │├right
│ │└1: TreeParzen.HP.Normal
│ │ ├label
│ │ ├1: :normal
│ │ ├obj
│ │ └1: TreeParzen.Delayed.Normal
│ │ ├mu
│ │ ├1: -10.0
│ │ ├sigma
│ │ └1: 10.0
│ └2: TreeParzen.Delayed.Float
│ ├arg
│ └1: TreeParzen.HP.LogNormal
│ ├label
│ ├1: :lognormal
│ ├obj
│ └1: TreeParzen.Delayed.LogNormal
│ ├mu
│ ├1: -10.0
│ ├sigma
│ └1: 10.0
└3: Dict{Symbol,Dict{Symbol,T} where T} of 2 items
├dictmiddle
├1: Dict{Symbol,Any} of 3 items
│├tuple
│├1: Tuple{Float64,Float64,Float64} of 3 items
││├1: 0.1
││├2: 0.3
││└3: 0.6
│├vector
│├2: Array{Int64,1} of 3 items
││├1: 7
││├2: 8
││└3: 9
│├set
│└3: Set{Int64} of 3 items
│ ├1: 4
│ ├2: 5
│ └3: 6
├dictend
└2: Dict{Symbol,Int64} of 2 items
├a
├1: 1
├b
└2: 4
Test Summary: | Pass Total
Unit Tests | 341 341
524.506593 seconds (166.57 M allocations: 15.390 GiB, 1.51% gc time)
Testing TreeParzen tests passed