Package evaluation of Gogeta on Julia 1.13.0-DEV.791 (d5209bd37d*) started at 2025-07-04T18:02:42.057 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 7.72s ################################################################################ # Installation # Installing Gogeta... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [8b0c908c] + Gogeta v0.3.0 Updating `~/.julia/environments/v1.13/Manifest.toml` [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 [a9b6321e] + Atomix v1.1.1 [fbb218c0] + BSON v0.3.9 [198e06fe] + BangBang v0.4.4 [9718e550] + Baselet v0.1.1 [6e4b80f9] + BenchmarkTools v1.6.0 [fa961155] + CEnum v0.5.0 [324d7699] + CategoricalArrays v0.10.8 [082447d4] + ChainRules v1.72.5 [d360d2e6] + ChainRulesCore v1.25.2 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.17.0 [a33af91c] + CompositionsBase v0.1.2 [187b0558] + ConstructionBase v1.6.0 [6add18c4] + ContextVariablesX v0.1.3 [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 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [31c24e10] + Distributions v0.25.120 [ffbed154] + DocStringExtensions v0.9.5 ⌅ [f6006082] + EvoTrees v0.16.9 [411431e0] + Extents v0.1.6 [cc61a311] + FLoops v0.2.2 [b9860ae5] + FLoopsBase v0.1.1 [1a297f60] + FillArrays v1.13.0 ⌅ [587475ba] + Flux v0.14.25 [f6369f11] + ForwardDiff v1.0.1 ⌅ [d9f16b24] + Functors v0.4.12 [0c68f7d7] + GPUArrays v11.2.3 [46192b85] + GPUArraysCore v0.2.0 [68eda718] + GeoFormatTypes v0.4.4 [cf35fbd7] + GeoInterface v1.4.1 [5c1252a2] + GeometryBasics v0.5.9 [8b0c908c] + Gogeta v0.3.0 [076d061b] + HashArrayMappedTries v0.2.0 [34004b35] + HypergeometricFunctions v0.3.28 [7869d1d1] + IRTools v0.4.15 [22cec73e] + InitialValues v0.3.1 [3587e190] + InverseFunctions v0.1.17 [92d709cd] + IrrationalConstants v0.2.4 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 [0f8b85d8] + JSON3 v1.14.3 [4076af6c] + JuMP v1.26.0 [b14d175d] + JuliaVariables v0.2.4 [63c18a36] + KernelAbstractions v0.9.36 [929cbde3] + LLVM v9.4.2 [2ab3a3ac] + LogExpFunctions v0.3.29 [c2834f40] + MLCore v1.0.0 ⌃ [7e8f7934] + MLDataDevices v1.5.3 [e80e1ace] + MLJModelInterface v1.11.1 [d8e11817] + MLStyle v0.4.17 [f1d291b0] + MLUtils v0.4.8 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.41.0 [128add7d] + MicroCollections v0.2.0 [e1d29d7a] + Missings v1.2.0 [d8a4904e] + MutableArithmetics v1.6.4 [872c559c] + NNlib v0.9.30 [77ba4419] + NaNMath v1.1.3 [71a1bf82] + NameResolution v0.1.5 [46757867] + NetworkLayout v0.4.10 [0b1bfda6] + OneHotArrays v0.2.10 ⌅ [3bd65402] + Optimisers v0.3.4 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.35 [69de0a69] + Parsers v2.8.3 [aea7be01] + PrecompileTools v1.3.2 [21216c6a] + Preferences v1.4.3 [8162dcfd] + PrettyPrint v0.2.0 [33c8b6b6] + ProgressLogging v0.1.5 [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 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.8.0 [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 v2.5.1 [171d559e] + SplittablesBase v0.1.15 [90137ffa] + StaticArrays v1.9.13 [1e83bf80] + StaticArraysCore v1.4.3 [64bff920] + StatisticalTraits v3.4.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.5 [4c63d2b9] + StatsFuns v1.5.0 [09ab397b] + StructArrays v0.7.1 [856f2bd8] + StructTypes v1.11.0 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [3bb67fe8] + TranscodingStreams v0.11.3 [28d57a85] + Transducers v0.4.84 [013be700] + UnsafeAtomics v0.3.0 ⌅ [e88e6eb3] + Zygote v0.6.77 [700de1a5] + ZygoteRules v0.2.7 [6e34b625] + Bzip2_jll v1.0.9+0 [5ae413db] + EarCut_jll v2.2.4+0 [dad2f222] + LLVMExtra_jll v0.0.37+2 [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 v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [4af54fe1] + LazyArtifacts v1.11.0 [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.12.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.13.0 [de0858da] + Printf v1.11.0 [9abbd945] + Profile v1.11.0 [3fa0cd96] + REPL 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 v1.3.0+1 [deac9b47] + LibCURL_jll v8.14.1+1 [e37daf67] + LibGit2_jll v1.9.1+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.5.20 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.5+0 [458c3c95] + OpenSSL_jll v3.5.0+0 [efcefdf7] + PCRE2_jll v10.45.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.13.1+0 [8e850ede] + nghttp2_jll v1.65.0+0 [3f19e933] + p7zip_jll v17.5.0+2 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m` Installation completed after 5.57s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 327.8s ################################################################################ # Testing # Testing Gogeta Status `/tmp/jl_WMFshX/Project.toml` [fbb218c0] BSON v0.3.9 ⌅ [f6006082] EvoTrees v0.16.9 ⌅ [587475ba] Flux v0.14.25 [60bf3e95] GLPK v1.2.1 [8b0c908c] Gogeta v0.3.0 [87dc4568] HiGHS v1.18.1 [682c06a0] JSON v0.21.4 [4076af6c] JuMP v1.26.0 [8a4e6c94] QuasiMonteCarlo v0.3.3 [10745b16] Statistics v1.11.1 [8ba89e20] Distributed v1.11.0 [37e2e46d] LinearAlgebra v1.12.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_WMFshX/Manifest.toml` [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 [a9b6321e] Atomix v1.1.1 [fbb218c0] BSON v0.3.9 [198e06fe] BangBang v0.4.4 [9718e550] Baselet v0.1.1 [6e4b80f9] BenchmarkTools v1.6.0 [fa961155] CEnum v0.5.0 [324d7699] CategoricalArrays v0.10.8 [082447d4] ChainRules v1.72.5 [d360d2e6] ChainRulesCore v1.25.2 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.17.0 [a33af91c] CompositionsBase v0.1.2 [2569d6c7] ConcreteStructs v0.2.3 [187b0558] ConstructionBase v1.6.0 [6add18c4] ContextVariablesX v0.1.3 [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 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [31c24e10] Distributions v0.25.120 [ffbed154] DocStringExtensions v0.9.5 ⌅ [f6006082] EvoTrees v0.16.9 [411431e0] Extents v0.1.6 [cc61a311] FLoops v0.2.2 [b9860ae5] FLoopsBase v0.1.1 [1a297f60] FillArrays v1.13.0 ⌅ [587475ba] Flux v0.14.25 [f6369f11] ForwardDiff v1.0.1 ⌅ [d9f16b24] Functors v0.4.12 [60bf3e95] GLPK v1.2.1 [0c68f7d7] GPUArrays v11.2.3 [46192b85] GPUArraysCore v0.2.0 [68eda718] GeoFormatTypes v0.4.4 [cf35fbd7] GeoInterface v1.4.1 [5c1252a2] GeometryBasics v0.5.9 [8b0c908c] Gogeta v0.3.0 [076d061b] HashArrayMappedTries v0.2.0 [87dc4568] HiGHS v1.18.1 [34004b35] HypergeometricFunctions v0.3.28 [7869d1d1] IRTools v0.4.15 [22cec73e] InitialValues v0.3.1 [18e54dd8] IntegerMathUtils v0.1.3 [3587e190] InverseFunctions v0.1.17 [92d709cd] IrrationalConstants v0.2.4 [c8e1da08] IterTools v1.10.0 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.0 [682c06a0] JSON v0.21.4 [0f8b85d8] JSON3 v1.14.3 [4076af6c] JuMP v1.26.0 [b14d175d] JuliaVariables v0.2.4 [63c18a36] KernelAbstractions v0.9.36 [929cbde3] LLVM v9.4.2 [73f95e8e] LatticeRules v0.0.1 [2ab3a3ac] LogExpFunctions v0.3.29 [c2834f40] MLCore v1.0.0 ⌃ [7e8f7934] MLDataDevices v1.5.3 [e80e1ace] MLJModelInterface v1.11.1 [d8e11817] MLStyle v0.4.17 [f1d291b0] MLUtils v0.4.8 [1914dd2f] MacroTools v0.5.16 [b8f27783] MathOptInterface v1.41.0 [128add7d] MicroCollections v0.2.0 [e1d29d7a] Missings v1.2.0 [d8a4904e] MutableArithmetics v1.6.4 [872c559c] NNlib v0.9.30 [77ba4419] NaNMath v1.1.3 [71a1bf82] NameResolution v0.1.5 [46757867] NetworkLayout v0.4.10 [0b1bfda6] OneHotArrays v0.2.10 ⌅ [3bd65402] Optimisers v0.3.4 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.35 [69de0a69] Parsers v2.8.3 [aea7be01] PrecompileTools v1.3.2 [21216c6a] Preferences v1.4.3 [8162dcfd] PrettyPrint v0.2.0 [27ebfcd6] Primes v0.5.7 [33c8b6b6] ProgressLogging v0.1.5 [43287f4e] PtrArrays v1.3.0 [1fd47b50] QuadGK v2.11.2 [8a4e6c94] QuasiMonteCarlo v0.3.3 [c1ae055f] RealDot v0.1.0 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [79098fc4] Rmath v0.8.0 [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 [ed01d8cd] Sobol v1.5.0 [a2af1166] SortingAlgorithms v1.2.1 [dc90abb0] SparseInverseSubset v0.1.2 [276daf66] SpecialFunctions v2.5.1 [171d559e] SplittablesBase v0.1.15 [90137ffa] StaticArrays v1.9.13 [1e83bf80] StaticArraysCore v1.4.3 [64bff920] StatisticalTraits v3.4.0 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.7.1 [2913bbd2] StatsBase v0.34.5 [4c63d2b9] StatsFuns v1.5.0 [09ab397b] StructArrays v0.7.1 [856f2bd8] StructTypes v1.11.0 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [3bb67fe8] TranscodingStreams v0.11.3 [28d57a85] Transducers v0.4.84 [013be700] UnsafeAtomics v0.3.0 ⌅ [e88e6eb3] Zygote v0.6.77 [700de1a5] ZygoteRules v0.2.7 [6e34b625] Bzip2_jll v1.0.9+0 [5ae413db] EarCut_jll v2.2.4+0 [e8aa6df9] GLPK_jll v5.0.1+1 [8fd58aa0] HiGHS_jll v1.11.0+1 [dad2f222] LLVMExtra_jll v0.0.37+2 [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 v1.7.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.12.0 [4af54fe1] LazyArtifacts v1.11.0 [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.12.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.13.0 [de0858da] Printf v1.11.0 [9abbd945] Profile v1.11.0 [3fa0cd96] REPL 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 v1.3.0+1 [781609d7] GMP_jll v6.3.0+2 [deac9b47] LibCURL_jll v8.14.1+1 [e37daf67] LibGit2_jll v1.9.1+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.5.20 [4536629a] OpenBLAS_jll v0.3.29+0 [05823500] OpenLibm_jll v0.8.5+0 [458c3c95] OpenSSL_jll v3.5.0+0 [efcefdf7] PCRE2_jll v10.45.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.1+2 [8e850b90] libblastrampoline_jll v5.13.1+0 [8e850ede] nghttp2_jll v1.65.0+0 [3f19e933] p7zip_jll v17.5.0+2 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... Precompiling packages... 16712.7 ms ✓ GLPK 1 dependency successfully precompiled in 18 seconds. 68 already precompiled. [ Info: Creating a medium-sized neural network with random weights [ Info: Compressing the neural network with simultaneous bound tightening. Starting compression... LAYER 1 Neuron: 1, bounds: [0.16892524808645248, 0.7776865735650063] Neuron: 2, bounds: [-0.2680980712175369, 0.04221390187740326] Neuron: 3, bounds: [-0.4801315367221832, 0.10741600394248962] Neuron: 4, bounds: [-0.17742440849542618, 0.42832256108522415] Neuron: 5, bounds: [-0.2498505935072899, 0.5106385871767998] Neuron: 6, bounds: [-1.3318716883659363, -0.0035308003425598145] Neuron: 7, bounds: [0.21568965166807175, 0.9142742231488228] Neuron: 8, bounds: [0.08210700750350952, 1.2899381518363953] Neuron: 9, bounds: [-0.14929509907960892, 0.5632241740822792] Neuron: 10, bounds: [-0.35886954702436924, 0.30129695124924183] Removed 2/10 neurons LAYER 2 Neuron: 1, bounds: [-0.204124655840976, 0.18278819779693922] Neuron: 2, bounds: [-0.08638546423628675, 0.08306160389779295] Neuron: 3, bounds: [0.12178459175894843, 0.6100031088195936] Neuron: 4, bounds: [-0.1230882495575163, 0.053507364682039815] Neuron: 5, bounds: [0.047082434130390934, 0.30614746944558996] Neuron: 6, bounds: [-0.7663025402195429, -0.1474696911561732] Neuron: 7, bounds: [-0.14331266432251638, 0.09932318344763202] Neuron: 8, bounds: [-0.21450056110607527, 0.1895002968974037] Neuron: 9, bounds: [-0.3225289569718, -0.057967686201655155] Neuron: 10, bounds: [-0.06048689975774592, 0.6596252721760898] Neuron: 11, bounds: [-0.0773518676217694, 0.7676084145562012] Neuron: 12, bounds: [-0.49864287955647324, 0.07517452175070236] Neuron: 13, bounds: [0.023200310442092392, 0.5049305494643218] Neuron: 14, bounds: [-0.6014186963037759, -0.10687182153678623] Neuron: 15, bounds: [0.03875438022886124, 0.9188053995306739] Neuron: 16, bounds: [-0.11895814880508127, 0.14722337495390284] Neuron: 17, bounds: [-0.24355792851704794, 0.17521396245850226] Neuron: 18, bounds: [-0.05638461046347154, 0.16373819448559457] Neuron: 19, bounds: [0.08549798986608637, 0.6157361345820475] Neuron: 20, bounds: [-0.5873057341839123, -0.18094156229142028] Removed 4/20 neurons LAYER 3 Neuron: 1, bounds: [-0.04280341184807124, 0.11878472143716659] Neuron: 2, bounds: [0.02256083871014896, 0.9120931964227156] Neuron: 3, bounds: [0.007810766303696329, 0.27001696973319816] Neuron: 4, bounds: [-0.699609880245913, -0.12343165223355541] Neuron: 5, bounds: [-0.5187849657977001, -0.0857069780432827] Removed 2/5 neurons LAYER 4 Neuron: 1, bounds: [-0.702059556624737, -0.10055643466240936] Creating JuMP model... LAYER 1 LAYER 2 LAYER 3 LAYER 4 [ Info: Testing that the compressed model and the corresponding JuMP model are equal to the original neural network. [ Info: Creating a JuMP model from the neural network with bound tightening but without compression. Creating JuMP model... LAYER 1 Neuron: 1, bounds: [0.16892524808645248, 0.7776865735650063] Neuron: 2, bounds: [-0.2680980712175369, 0.04221390187740326] Neuron: 3, bounds: [-0.4801315367221832, 0.10741600394248962] Neuron: 4, bounds: [-0.17742440849542618, 0.42832256108522415] Neuron: 5, bounds: [-0.2498505935072899, 0.5106385871767998] Neuron: 6, bounds: [-1.3318716883659363, -0.0035308003425598145] Neuron: 7, bounds: [0.21568965166807175, 0.9142742231488228] Neuron: 8, bounds: [0.08210700750350952, 1.2899381518363953] Neuron: 9, bounds: [-0.14929509907960892, 0.5632241740822792] Neuron: 10, bounds: [-0.35886954702436924, 0.30129695124924183] LAYER 2 Neuron: 1, bounds: [-0.20412472928805475, 0.18278808645037875] Neuron: 2, bounds: [-0.0863855109804773, 0.08306156548248451] Neuron: 3, bounds: [0.1217845478507323, 0.6100030003890271] Neuron: 4, bounds: [-0.12308829506149438, 0.053507348633525076] Neuron: 5, bounds: [0.04708236796792755, 0.3061472989372608] Neuron: 6, bounds: [-0.7663025277187504, -0.14746968806007418] Neuron: 7, bounds: [-0.14331261564059156, 0.09932322123670151] Neuron: 8, bounds: [-0.21450045776854917, 0.1895003583045474] Neuron: 9, bounds: [-0.3225287760443095, -0.05796763815771] Neuron: 10, bounds: [-0.06048696979595501, 0.6596250728609041] Neuron: 11, bounds: [-0.07735185957156968, 0.7676085016002656] Neuron: 12, bounds: [-0.49864287602156165, 0.07517452435976688] Neuron: 13, bounds: [0.023200326513075797, 0.5049306433713441] Neuron: 14, bounds: [-0.6014187211595349, -0.10687181994851827] Neuron: 15, bounds: [0.038754295953257634, 0.9188051322533609] Neuron: 16, bounds: [-0.1189581490839963, 0.14722340449274288] Neuron: 17, bounds: [-0.24355784574207975, 0.17521400412495655] Neuron: 18, bounds: [-0.056384612508312504, 0.16373819441555482] Neuron: 19, bounds: [0.08549791361122552, 0.6157358951177498] Neuron: 20, bounds: [-0.5873057256184733, -0.1809415543269072] LAYER 3 Neuron: 1, bounds: [-0.04280364803696057, 0.11878455756424713] Neuron: 2, bounds: [0.022560826277516894, 0.9120931601932567] Neuron: 3, bounds: [0.0078107449063999496, 0.27001697613595216] Neuron: 4, bounds: [-0.6996096418314006, -0.12343159688273675] Neuron: 5, bounds: [-0.5187846847921361, -0.08570691407314165] LAYER 4 Neuron: 1, bounds: [-0.7020595465633641, -0.10055640336815123] [ Info: Creating bound tightened JuMP model with output bounds present. Creating JuMP model... LAYER 1 LAYER 2 LAYER 3 LAYER 4 Starting bound tightening based on output bounds as well as input bounds. LAYER 1 Neuron: 1, bounds: [0.21480483178352944, 0.5247513744321706] Neuron: 2, bounds: [-0.2077416969929622, 0.01777799022605238] Neuron: 3, bounds: [-0.3805417414679213, 0.06709602996336328] Neuron: 4, bounds: [-0.174069522075442, 0.3778596326074081] Neuron: 5, bounds: [-0.2216388228831811, 0.4409558919034912] Neuron: 6, bounds: [-0.9750514092628358, -0.14799323579521156] Neuron: 7, bounds: [0.2609416871646269, 0.6123472546147706] Neuron: 8, bounds: [0.23053340849139253, 0.9233269309967497] Neuron: 9, bounds: [-0.14376024352874534, 0.47997097715300996] Neuron: 10, bounds: [-0.3434861177834677, 0.2950688084448581] LAYER 2 Neuron: 1, bounds: [-0.19056269805753034, 0.16509149526530836] Neuron: 2, bounds: [-0.0863855109804773, 0.050081673543741025] Neuron: 3, bounds: [0.15445417788285407, 0.4421394477931019] Neuron: 4, bounds: [-0.0869449555443118, 0.044487860839498586] Neuron: 5, bounds: [0.04804882866406922, 0.2514234236127688] Neuron: 6, bounds: [-0.5475927353210297, -0.1565440981003631] Neuron: 7, bounds: [-0.10576769895566618, 0.09905323236007074] Neuron: 8, bounds: [-0.18420729734181776, 0.14895556194978601] Neuron: 9, bounds: [-0.23624008239619257, -0.062096450860319924] Neuron: 10, bounds: [-0.023226155947844287, 0.4727120626155764] Neuron: 11, bounds: [-0.01872654427245863, 0.55712566773659] Neuron: 12, bounds: [-0.3924910970228941, 0.04192783440984332] Neuron: 13, bounds: [0.1001469259480061, 0.320046869921038] Neuron: 14, bounds: [-0.4161844918584351, -0.12321994466326419] Neuron: 15, bounds: [0.1521162090657074, 0.6356195932304258] Neuron: 16, bounds: [-0.11788287084462623, 0.08866693774347784] Neuron: 17, bounds: [-0.16398113825884533, 0.13669675409796125] Neuron: 18, bounds: [-0.03238101837437567, 0.13310817243843004] Neuron: 19, bounds: [0.12851321879032002, 0.44704411781367004] Neuron: 20, bounds: [-0.41883438228796555, -0.1809415543269072] LAYER 3 Neuron: 1, bounds: [-0.025304857646799725, 0.08837540117533178] Neuron: 2, bounds: [0.1123550657401983, 0.5928294642123964] Neuron: 3, bounds: [0.00988789406073514, 0.21346904996318955] Neuron: 4, bounds: [-0.485494512881771, -0.1341464683064494] Neuron: 5, bounds: [-0.38637593372682344, -0.08570691407314163] [ Info: Testing that the output tightened model is the same in the areas it's defined in. ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 ERROR: MathOptInterface.ResultIndexBoundsError{MathOptInterface.VariablePrimal}(MathOptInterface.VariablePrimal(1), 0) ┌ Warning: Input or output outside of bounds or incorrectly constructed model. └ @ Gogeta ~/.julia/packages/Gogeta/lEEud/src/neural_networks/NN_to_MIP.jl:221 [ Info: Testing that the created JuMP model is equal to the original neural network. [ Info: Compressing with the precomputed bounds. Removed 2/10 neurons Removed 4/20 neurons Removed 2/5 neurons [ Info: Testing that this compression result is equal to the original. [ Info: Testing that the removed neurons are the same as with simultaneous bound tightening compression. [ Info: Creating a JuMP model of the network with loose bound tightening. Creating JuMP model... LAYER 1 LAYER 2 LAYER 3 LAYER 4 [ Info: Testing that the loose JuMP model is equal to the original neural network. [ Info: Compressing with the precomputed loose bounds. Removed 2/10 neurons Removed 2/20 neurons Removed 0/5 neurons [ Info: Testing that this loose compression result is equal to the original neural network. Test Summary: | Pass Total Time Neural networks | 8 8 2m23.1s Precompiling packages... 37854.4 ms ✓ HiGHS 1 dependency successfully precompiled in 40 seconds. 52 already precompiled. [ Info: Creating a JuMP model from the neural network with bound tightening. Creating JuMP model... LAYER 1 From worker 3: Neuron: 2, bounds: [-0.2680980712175369, 0.04221390187740326] From worker 4: Neuron: 3, bounds: [-0.4801315367221832, 0.10741600394248962] From worker 2: Neuron: 1, bounds: [0.16892524808645248, 0.7776865735650063] From worker 5: Neuron: 4, bounds: [-0.17742440849542618, 0.42832256108522415] From worker 3: Neuron: 5, bounds: [-0.2498505935072899, 0.5106385871767998] From worker 4: Neuron: 6, bounds: [-1.3318716883659363, -0.0035308003425598145] From worker 3: Neuron: 9, bounds: [-0.14929509907960892, 0.5632241740822792] From worker 4: Neuron: 10, bounds: [-0.35886954702436924, 0.30129695124924183] From worker 2: Neuron: 7, bounds: [0.21568965166807175, 0.9142742231488228] From worker 5: Neuron: 8, bounds: [0.08210700750350952, 1.2899381518363953] LAYER 2 From worker 4: Neuron: 3, bounds: [0.12178454785073231, 0.610003000389027] From worker 4: Neuron: 5, bounds: [0.047082367967927564, 0.3061472989372608] From worker 5: Neuron: 4, bounds: [-0.12308829506149438, 0.053507348633525076] From worker 3: Neuron: 2, bounds: [-0.08638551098047731, 0.08306156548248449] From worker 4: Neuron: 6, bounds: [-0.7663025277187504, -0.14746968806007416] From worker 5: Neuron: 7, bounds: [-0.14331261564059156, 0.09932322123670155] From worker 3: Neuron: 8, bounds: [-0.21450045776854917, 0.1895003583045474] From worker 4: Neuron: 9, bounds: [-0.3225287760443095, -0.05796763815771] From worker 5: Neuron: 10, bounds: [-0.06048696979595501, 0.6596250728609041] From worker 3: Neuron: 11, bounds: [-0.07735185957156968, 0.7676085016002656] From worker 4: Neuron: 12, bounds: [-0.49864287602156165, 0.07517452435976689] From worker 5: Neuron: 13, bounds: [0.023200326513075797, 0.5049306433713441] From worker 3: Neuron: 14, bounds: [-0.601418721159535, -0.10687181994851827] From worker 4: Neuron: 15, bounds: [0.038754295953257634, 0.9188051322533609] From worker 5: Neuron: 16, bounds: [-0.11895814908399632, 0.14722340449274288] From worker 2: Neuron: 1, bounds: [-0.20412472928805475, 0.18278808645037875] From worker 4: Neuron: 18, bounds: [-0.056384612508312525, 0.16373819441555482] From worker 3: Neuron: 17, bounds: [-0.24355784574207973, 0.17521400412495655] From worker 5: Neuron: 19, bounds: [0.08549791361122551, 0.6157358951177498] From worker 2: Neuron: 20, bounds: [-0.5873057256184733, -0.18094155432690717] LAYER 3 From worker 3: Neuron: 2, bounds: [0.022560826277516936, 0.9120931601932567] From worker 5: Neuron: 4, bounds: [-0.6996096418314005, -0.12343159688273676] From worker 4: Neuron: 3, bounds: [0.007810744906399936, 0.2700169761359523] From worker 3: Neuron: 5, bounds: [-0.5187846847921362, -0.08570691407314167] From worker 2: Neuron: 1, bounds: [-0.042803648036960615, 0.11878455756424884] LAYER 4 From worker 2: Neuron: 1, bounds: [-0.7020595465633644, -0.10055640336815128] [ Info: Testing that correct model is produced [ Info: Testing that parallel computed bounds are the same. Test Summary: | Pass Total Time Parallel tests | 3 3 10m32.1s Precompiling packages... 4721.2 ms ✓ QuasiMonteCarlo → QuasiMonteCarloDistributionsExt 1 dependency successfully precompiled in 6 seconds. 67 already precompiled. [ Info: Formulating the MIP with heuristic bound tightening. [ Info: Solving by sampling. [ Info: Testing that sampling solution and extremum agree. [ Info: Testing that optimum is correct (precomputed). Test Summary: | Pass Total Time Sampling tests | 3 3 49.6s [ Info: Creating a small neural network with random weights [ Info: Creating an optimization problem [ Info: setting up a solver for bound tightening WARNING: Method definition set_solver!(Any) in module Main at /home/pkgeval/.julia/packages/Gogeta/lEEud/test/neural_networks/NN_parallel_test.jl:7 overwritten at /home/pkgeval/.julia/packages/Gogeta/lEEud/test/neural_networks/NN_in_larger_problem.jl:39. [ Info: include neural network as a part of the larger optimization problem. Use bound tightening and compress the network LAYER: 1 Neuron: 1, bounds: [0.16892524808645248, 0.7776865735650063] Neuron: 2, bounds: [-0.2680980712175369, 0.04221390187740326] Neuron: 3, bounds: [-0.4801315367221832, 0.10741600394248962] Neuron: 4, bounds: [-0.17742440849542618, 0.42832256108522415] Neuron: 5, bounds: [-0.2498505935072899, 0.5106385871767998] Neuron: 6, bounds: [-1.3318716883659363, -0.0035308003425598145] Neuron: 7, bounds: [0.21568965166807175, 0.9142742231488228] Neuron: 8, bounds: [0.08210700750350952, 1.2899381518363953] Neuron: 9, bounds: [-0.14929509907960892, 0.5632241740822792] Neuron: 10, bounds: [-0.35886954702436924, 0.30129695124924183] Removed 2/10 neurons LAYER: 2 Neuron: 1, bounds: [-0.12547274169625489, 0.037194370579637204] Neuron: 2, bounds: [-0.06294380481980272, 0.3177906666261906] Neuron: 3, bounds: [-0.1480369187278232, 0.11205503452510278] Neuron: 4, bounds: [0.008051333989021497, 0.28387308588560345] Neuron: 5, bounds: [-0.09820879021414813, 0.14830404251298596] Neuron: 6, bounds: [-0.506661232489289, -0.14553319718049995] Neuron: 7, bounds: [-0.2618062172832012, -0.04886808543414492] Neuron: 8, bounds: [-0.07524783669883495, 0.2824707352588838] Neuron: 9, bounds: [0.2152598389260548, 0.6940759885981498] Neuron: 10, bounds: [-0.11301034849998065, 0.052493635218931356] Neuron: 11, bounds: [-0.03864744960555183, 0.30714672718394287] Neuron: 12, bounds: [-0.07449174133825674, 0.5714896688707525] Neuron: 13, bounds: [0.08463192665178937, 0.8429640190431623] Neuron: 14, bounds: [0.028072113592455553, 0.14650031788897977] Neuron: 15, bounds: [0.04110856165473978, 0.15172086675695629] Neuron: 16, bounds: [-0.45258237836109205, -0.09149532608982347] Neuron: 17, bounds: [-0.398320238854901, -0.07549628675430857] Neuron: 18, bounds: [-0.29907203114853875, 0.08528297609294014] Neuron: 19, bounds: [0.10080845667252006, 0.49003525258491437] Neuron: 20, bounds: [-0.01772219606606562, 0.07649076926361634] Neuron: 21, bounds: [-0.5096756498038622, -0.04891735852318568] Neuron: 22, bounds: [0.038620414050423976, 0.18096347712038022] Neuron: 23, bounds: [-0.10158835837621372, -0.008550028937702209] Neuron: 24, bounds: [-0.02768773566601951, 0.11029909357351761] Neuron: 25, bounds: [-0.7684471067514494, -0.15512474574213309] Neuron: 26, bounds: [-0.1328354022093913, 0.1476956062026823] Neuron: 27, bounds: [-0.14845351745993574, -0.020320551385496988] Neuron: 28, bounds: [-0.6368220128186743, -0.03266885245771356] Neuron: 29, bounds: [0.0008167135853149876, 0.1518820768890403] Neuron: 30, bounds: [0.08937962126262111, 0.35775568294636007] Neuron: 31, bounds: [-0.3511604232473767, 0.12843396252867267] Neuron: 32, bounds: [-0.366193576335273, -0.05615693061158708] Neuron: 33, bounds: [-0.08931906673778842, 0.03294054300018523] Neuron: 34, bounds: [-0.12436479657797961, 0.08817331828312214] Neuron: 35, bounds: [0.09138397491881779, 0.5086980680620262] Neuron: 36, bounds: [-0.2697032290263971, 0.03430034179213748] Neuron: 37, bounds: [-0.13113664061064317, 0.1141803637158103] Neuron: 38, bounds: [-0.23758434603872558, 0.1766447181195978] Neuron: 39, bounds: [-0.32262406403241917, -0.020712322218464863] Neuron: 40, bounds: [-0.0775651697203592, 0.11597348067640252] Neuron: 41, bounds: [-0.15608472055950529, -0.018793193803942093] Neuron: 42, bounds: [0.00334448550192723, 0.3158078982488665] Neuron: 43, bounds: [-0.5385059284502184, -0.03987429567854511] Neuron: 44, bounds: [0.0476688621537773, 0.4042177337709925] Neuron: 45, bounds: [0.08555940524672458, 0.3268730712092248] Neuron: 46, bounds: [-0.5012525148543787, 0.07769965798130431] Neuron: 47, bounds: [-0.03276445796278551, 0.04745530873832017] Neuron: 48, bounds: [0.10509950770022809, 0.388414765330902] Neuron: 49, bounds: [-0.0010466273147396454, 0.5703552167934527] Neuron: 50, bounds: [-0.04523540071709842, 0.33649960248706384] Removed 17/50 neurons LAYER: 3 Neuron: 1, bounds: [-0.16442505510636826, -0.01817665397657465] Neuron: 2, bounds: [-0.3646071560379658, -0.0551994990878488] Neuron: 3, bounds: [0.12202593394676833, 0.46168791309145496] Neuron: 4, bounds: [0.007443778909788345, 0.1275218200071321] Neuron: 5, bounds: [-0.004614620987214431, 0.08908093498818694] Neuron: 6, bounds: [-0.3295275911237912, -0.060857154205845615] Neuron: 7, bounds: [-0.04736596781842012, 0.13267156635726543] Neuron: 8, bounds: [-0.43944674030146447, -0.017347793575859395] Neuron: 9, bounds: [-0.38631805526875035, -0.11647600805691888] Neuron: 10, bounds: [0.07303733416064115, 0.35910240106277375] Neuron: 11, bounds: [0.12475743474725243, 0.43770665489959437] Neuron: 12, bounds: [-0.08252833923787713, -0.008495168942557006] Neuron: 13, bounds: [-0.2168642063901008, -0.028307810135067123] Neuron: 14, bounds: [-0.08001730012983396, 0.05923592965943672] Neuron: 15, bounds: [-0.9781547484768432, -0.09744131856501903] Neuron: 16, bounds: [-0.000450764974611351, 0.12459031193538314] Neuron: 17, bounds: [0.06728178250179795, 0.27403924023813286] Neuron: 18, bounds: [-0.006279397737038554, 0.09351780218338994] Neuron: 19, bounds: [-0.5942607804820161, -0.1492685057033639] Neuron: 20, bounds: [-0.34666823845559913, -0.03681436309617152] Removed 10/20 neurons LAYER: 4 Neuron: 1, bounds: [0.06412805963346636, 0.25500724602221] Neuron: 2, bounds: [0.019230523222134, 0.10722034571759223] Neuron: 3, bounds: [0.06784806047036061, 0.3688583214253333] Neuron: 4, bounds: [0.008251039230662026, 0.10759546590914813] Neuron: 5, bounds: [0.036195532327630425, 0.1809899935242798] Fully stable layer Removed 5/5 neurons LAYER: 5 Neuron: 1, bounds: [-0.5035839406961269, -0.1207453134511664] [ Info: Testing that correct optimum is found [ Info: Testing that NN output matches Flux model Test Summary: | Pass Total Time Larger formulation tests | 4 4 48.5s [ Info: creating an optimization problem [ Info: include input convex neural network as a part of the larger optimization problem [ Info: testing for correct values Test Summary: | Pass Total Time ICNN tests | 3 3 16.7s [ Info: Creating a random convolutional neural network model [ Info: Formulating as a JuMP model Formulating CNN as JuMP model... Preprocessing completed Added conv layer Added maxpool layer Added flatten layer Added dense layer Added dense layer Formulation complete. [ Info: Testing image forward pass with some random inputs - passing test indicates that model is constructed correctly. [ Info: Repeating the test with a different model and input size [ Info: Creating a random convolutional neural network model [ Info: Formulating as a JuMP model Formulating CNN as JuMP model... Preprocessing completed Added conv layer Added maxpool layer Added meanpool layer Added flatten layer Added dense layer Added dense layer Formulation complete. [ Info: Testing image forward pass with some random inputs - passing test indicates that model is constructed correctly. Test Summary: | Pass Total Time CNN tests | 20 20 1m03.9s [ Info: Loading a trained tree ensemble model. [ Info: Creating JuMP models and optimizing them. [ Info: Getting solutions. [ Info: Comparing obtained optimal solutions to the true minimum of the tree ensemble. Test Summary: | Pass Total Time Tree ensemble tests | 4 4 36.0s [ Info: Creating a random neural network model [ Info: Test that activation function at each layer (except last one) is relu [ Info: Test that activation function at the last layer is identity [ Info: Test that non-providing boundaries with 'precomputed' bound-tightening results in error [ Info: Test that non-existent strategy result in error [ Info: Test that P<2 with 'equalrange' strategy result in error [ Info: Test: dimension of boundaries should be the same as input layer in NN [ Info: Generating sample dataset [ Info: Formulating the MIP with with strategy='equalsize' and bound_tightening='fast' [ Info: Testing that corresponding JuMP model has the same output as NN, P=3 [ Info: Testing that corresponding JuMP model has the same output as NN, P=4 [ Info: Testing that corresponding JuMP model has the same output as NN, P=5 [ Info: Formulating the MIP with with strategy='equalsize' and bound_tightening='standard', P=4 [ Info: Testing that corresponding JuMP model has the same output as NN, strategy = 'equalsize' [ Info: Testing that corresponding JuMP model has the same output as NN, strategy = 'equalrange' [ Info: Testing that corresponding JuMP model has the same output as NN, strategy = 'snake' [ Info: Testing that corresponding JuMP model has the same output as NN, strategy = 'random' Testing Gogeta tests passed Testing completed after 1064.26s PkgEval succeeded after 1421.1s