Package evaluation of PartiallySeparableNLPModels on Julia 1.11.4 (a71dd056e0*) started at 2025-04-08T20:14:22.815 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 8.66s ################################################################################ # Installation # Installing PartiallySeparableNLPModels... Resolving package versions... Updating `~/.julia/environments/v1.11/Project.toml` [7f79d04d] + PartiallySeparableNLPModels v0.4.0 Updating `~/.julia/environments/v1.11/Manifest.toml` [54578032] + ADNLPModels v0.8.12 [47edcb42] + ADTypes v1.14.0 ⌅ [c3fe647b] + AbstractAlgebra v0.27.10 [1520ce14] + AbstractTrees v0.4.5 ⌅ [79e6a3ab] + Adapt v3.7.2 [66dad0bd] + AliasTables v1.1.3 ⌃ [4fba245c] + ArrayInterface v7.7.1 [6e4b80f9] + BenchmarkTools v1.6.0 [e2ed5e7c] + Bijections v0.1.9 [d360d2e6] + ChainRulesCore v1.25.1 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [861a8166] + Combinatorics v1.0.2 [38540f10] + CommonSolve v0.2.4 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.16.0 [b152e2b5] + CompositeTypes v0.1.4 ⌅ [187b0558] + ConstructionBase v1.5.6 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [31c24e10] + Distributions v0.25.118 [ffbed154] + DocStringExtensions v0.9.4 ⌅ [5b8099bc] + DomainSets v0.5.14 ⌅ [7c1d4256] + DynamicPolynomials v0.4.6 [4e289a0a] + EnumX v1.0.5 [e2ba6199] + ExprTools v0.1.10 [93090adf] + ExpressionTreeForge v0.2.0 [9aa1b823] + FastClosures v0.3.2 [1a297f60] + FillArrays v1.13.0 [59287772] + Formatting v0.4.3 ⌅ [f6369f11] + ForwardDiff v0.10.38 [069b7b12] + FunctionWrappers v1.1.3 [77dc65aa] + FunctionWrappersWrappers v0.1.3 ⌅ [46192b85] + GPUArraysCore v0.1.5 ⌅ [0b43b601] + Groebner v0.2.11 ⌅ [d5909c97] + GroupsCore v0.4.2 [34004b35] + HypergeometricFunctions v0.3.28 [615f187c] + IfElse v0.1.1 [18e54dd8] + IntegerMathUtils v0.1.2 [8197267c] + IntervalSets v0.7.10 [92d709cd] + IrrationalConstants v0.2.4 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 [0f8b85d8] + JSON3 v1.14.2 ⌅ [10dff2fc] + JSOSolvers v0.12.1 [4076af6c] + JuMP v1.25.0 [ba0b0d4f] + Krylov v0.9.10 [b964fa9f] + LaTeXStrings v1.4.0 ⌃ [2ee39098] + LabelledArrays v1.15.1 ⌅ [984bce1d] + LambertW v0.4.6 ⌅ [23fbe1c1] + Latexify v0.15.21 [50d2b5c4] + Lazy v0.15.1 [5c8ed15e] + LinearOperators v2.9.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [1914dd2f] + MacroTools v0.5.15 [b8f27783] + MathOptInterface v1.38.1 [e1d29d7a] + Missings v1.2.0 ⌅ [102ac46a] + MultivariatePolynomials v0.4.7 [d8a4904e] + MutableArithmetics v1.6.4 [a4795742] + NLPModels v0.21.3 [792afdf1] + NLPModelsJuMP v0.13.2 [e01155f1] + NLPModelsModifiers v0.7.2 [77ba4419] + NaNMath v1.1.3 [bac558e1] + OrderedCollections v1.8.0 [90014a1f] + PDMats v0.11.33 [69de0a69] + Parsers v2.8.1 [7f79d04d] + PartiallySeparableNLPModels v0.4.0 [a6683cb1] + PartitionedStructures v0.1.6 [9d5e22db] + PartitionedVectors v0.1.3 ⌃ [d236fae5] + PreallocationTools v0.4.24 ⌅ [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 [27ebfcd6] + Primes v0.5.7 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [fb686558] + RandomExtensions v0.4.4 [3cdcf5f2] + RecipesBase v1.3.4 ⌅ [731186ca] + RecursiveArrayTools v2.38.10 [189a3867] + 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Tricks v0.1.10 [781d530d] + TruncatedStacktraces v1.4.0 [a7c27f48] + Unityper v0.1.6 [6e34b625] + Bzip2_jll v1.0.9+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 [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 v1.11.0 [de0858da] + Printf v1.11.0 [9abbd945] + Profile 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 v1.11.0 [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 v1.1.1+0 [deac9b47] + LibCURL_jll v8.6.0+0 [e37daf67] + LibGit2_jll v1.7.2+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.6+0 [14a3606d] + MozillaCACerts_jll v2023.12.12 [4536629a] + OpenBLAS_jll v0.3.27+1 [05823500] + OpenLibm_jll v0.8.5+0 [bea87d4a] + SuiteSparse_jll v7.7.0+0 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 [8e850ede] + nghttp2_jll v1.59.0+0 [3f19e933] + p7zip_jll v17.4.0+2 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m` Installation completed after 7.05s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 47.79s ################################################################################ # Testing # Testing PartiallySeparableNLPModels Status `/tmp/jl_kiiXjB/Project.toml` [54578032] ADNLPModels v0.8.12 [93090adf] ExpressionTreeForge v0.2.0 [9aa1b823] FastClosures v0.3.2 ⌅ [f6369f11] ForwardDiff v0.10.38 ⌅ [10dff2fc] JSOSolvers v0.12.1 [ba0b0d4f] Krylov v0.9.10 [5c8ed15e] LinearOperators v2.9.0 [b8f27783] MathOptInterface v1.38.1 [a4795742] NLPModels v0.21.3 [792afdf1] NLPModelsJuMP v0.13.2 [e01155f1] NLPModelsModifiers v0.7.2 [5049e819] OptimizationProblems v0.9.0 [7f79d04d] PartiallySeparableNLPModels v0.4.0 [a6683cb1] PartitionedStructures v0.1.6 [9d5e22db] PartitionedVectors v0.1.3 [37e2e3b7] ReverseDiff v1.16.1 [b5612192] SolverTools v0.9.0 [10745b16] Statistics v1.11.1 [37e2e46d] LinearAlgebra v1.11.0 [de0858da] Printf v1.11.0 [2f01184e] SparseArrays v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_kiiXjB/Manifest.toml` [54578032] ADNLPModels v0.8.12 [47edcb42] ADTypes v1.14.0 ⌅ [c3fe647b] AbstractAlgebra v0.27.10 [1520ce14] AbstractTrees v0.4.5 ⌅ [79e6a3ab] Adapt v3.7.2 [66dad0bd] AliasTables v1.1.3 ⌃ [4fba245c] ArrayInterface v7.7.1 [6e4b80f9] BenchmarkTools v1.6.0 [e2ed5e7c] Bijections v0.1.9 [d360d2e6] ChainRulesCore v1.25.1 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [861a8166] Combinatorics v1.0.2 [38540f10] CommonSolve v0.2.4 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.16.0 [b152e2b5] CompositeTypes v0.1.4 ⌅ [187b0558] ConstructionBase v1.5.6 [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 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [31c24e10] Distributions v0.25.118 [ffbed154] DocStringExtensions v0.9.4 ⌅ [5b8099bc] DomainSets v0.5.14 ⌅ [7c1d4256] DynamicPolynomials v0.4.6 [4e289a0a] EnumX v1.0.5 [e2ba6199] ExprTools v0.1.10 [93090adf] ExpressionTreeForge v0.2.0 [9aa1b823] FastClosures v0.3.2 [5789e2e9] FileIO v1.17.0 [1a297f60] FillArrays v1.13.0 [59287772] Formatting v0.4.3 ⌅ [f6369f11] ForwardDiff v0.10.38 [069b7b12] FunctionWrappers v1.1.3 [77dc65aa] FunctionWrappersWrappers v0.1.3 ⌅ [46192b85] GPUArraysCore v0.1.5 ⌅ [0b43b601] Groebner v0.2.11 ⌅ [d5909c97] GroupsCore v0.4.2 [34004b35] HypergeometricFunctions v0.3.28 [615f187c] IfElse v0.1.1 [842dd82b] InlineStrings v1.4.3 [18e54dd8] IntegerMathUtils v0.1.2 [8197267c] IntervalSets v0.7.10 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.4 [82899510] IteratorInterfaceExtensions v1.0.0 ⌅ [033835bb] JLD2 v0.4.54 [692b3bcd] JLLWrappers v1.7.0 [682c06a0] JSON v0.21.4 [0f8b85d8] JSON3 v1.14.2 ⌅ [10dff2fc] JSOSolvers v0.12.1 [4076af6c] JuMP v1.25.0 [ba0b0d4f] Krylov v0.9.10 [b964fa9f] LaTeXStrings v1.4.0 ⌃ [2ee39098] LabelledArrays v1.15.1 ⌅ [984bce1d] LambertW v0.4.6 ⌅ [23fbe1c1] Latexify v0.15.21 [50d2b5c4] Lazy v0.15.1 [5c8ed15e] LinearOperators v2.9.0 [2ab3a3ac] 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[e66e0078] CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] LibCURL_jll v8.6.0+0 [e37daf67] LibGit2_jll v1.7.2+0 [29816b5a] LibSSH2_jll v1.11.0+1 [c8ffd9c3] MbedTLS_jll v2.28.6+0 [14a3606d] MozillaCACerts_jll v2023.12.12 [4536629a] OpenBLAS_jll v0.3.27+1 [05823500] OpenLibm_jll v0.8.5+0 [bea87d4a] SuiteSparse_jll v7.7.0+0 [83775a58] Zlib_jll v1.2.13+1 [8e850b90] libblastrampoline_jll v5.11.0+0 [8e850ede] nghttp2_jll v1.59.0+0 [3f19e933] p7zip_jll v17.4.0+2 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... Precompiling JSOSolvers... 1820.4 ms ✓ SolverTools 2759.4 ms ✓ JSOSolvers 2 dependencies successfully precompiled in 5 seconds. 16 already precompiled. Precompiling PartitionedVectors... 4122.3 ms ✓ StatsBase 3412.1 ms ✓ PartitionedStructures 2264.9 ms ✓ PartitionedVectors 3 dependencies successfully precompiled in 11 seconds. 30 already precompiled. Precompiling PartiallySeparableNLPModels... 2916.3 ms ? DomainSets 9752.0 ms ✓ Distributions 4960.0 ms ✓ Distributions → DistributionsTestExt 5099.9 ms ✓ Distributions → DistributionsChainRulesCoreExt 3619.5 ms ? Symbolics 6616.2 ms ? ExpressionTreeForge Info Given PartiallySeparableNLPModels was explicitly requested, output will be shown live  WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_times.jl:103 declares type variable Y but does not use it. WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_exp.jl:54 declares type variable Y but does not use it. WARNING: method definition for _evaluate_node at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_power.jl:174 declares type variable Z but does not use it. WARNING: could not import M_interface_expr_tree._transform_to_Expr_JuMP into M_trait_expr_tree WARNING: Method definition is_expr_tree(Number) in module M_trait_expr_tree at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:28 overwritten at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:29. ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. 6825.1 ms ? PartiallySeparableNLPModels 3 dependencies successfully precompiled in 47 seconds. 174 already precompiled. 4 dependencies failed but may be precompilable after restarting julia 4 dependencies had output during precompilation: ┌ DomainSets │ WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/pkgeval/.julia/packages/IntervalSets/kyCuf/src/IntervalSets.jl:296 overwritten in module DomainSets at /home/pkgeval/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52. │ ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. └ ┌ ExpressionTreeForge │ WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_times.jl:103 declares type variable Y but does not use it. │ WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_exp.jl:54 declares type variable Y but does not use it. │ WARNING: method definition for _evaluate_node at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_power.jl:174 declares type variable Z but does not use it. │ WARNING: could not import M_interface_expr_tree._transform_to_Expr_JuMP into M_trait_expr_tree │ WARNING: Method definition is_expr_tree(Number) in module M_trait_expr_tree at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:28 overwritten at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:29. │ ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. └ ┌ Symbolics │ WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/pkgeval/.julia/packages/IntervalSets/kyCuf/src/IntervalSets.jl:296 overwritten in module DomainSets at /home/pkgeval/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52. │ ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. └ ┌ PartiallySeparableNLPModels │ [Output was shown above] └ WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_times.jl:103 declares type variable Y but does not use it. WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_exp.jl:54 declares type variable Y but does not use it. WARNING: method definition for _evaluate_node at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_power.jl:174 declares type variable Z but does not use it. WARNING: could not import M_interface_expr_tree._transform_to_Expr_JuMP into M_trait_expr_tree WARNING: Method definition is_expr_tree(Number) in module M_trait_expr_tree at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:28 overwritten at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:29. ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. Precompiling ExpressionTreeForge... 2891.6 ms ? DomainSets 3545.3 ms ? Symbolics Info Given ExpressionTreeForge was explicitly requested, output will be shown live  WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_times.jl:103 declares type variable Y but does not use it. WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_exp.jl:54 declares type variable Y but does not use it. WARNING: method definition for _evaluate_node at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_power.jl:174 declares type variable Z but does not use it. WARNING: could not import M_interface_expr_tree._transform_to_Expr_JuMP into M_trait_expr_tree WARNING: Method definition is_expr_tree(Number) in module M_trait_expr_tree at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:28 overwritten at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:29. ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. 6358.0 ms ? ExpressionTreeForge WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_times.jl:103 declares type variable Y but does not use it. WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_exp.jl:54 declares type variable Y but does not use it. WARNING: method definition for _evaluate_node at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_power.jl:174 declares type variable Z but does not use it. WARNING: could not import M_interface_expr_tree._transform_to_Expr_JuMP into M_trait_expr_tree WARNING: Method definition is_expr_tree(Number) in module M_trait_expr_tree at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:28 overwritten at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:29. ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_times.jl:103 declares type variable Y but does not use it. WARNING: method definition for _node_bound at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_exp.jl:54 declares type variable Y but does not use it. WARNING: method definition for _evaluate_node at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/node_expr_tree/impl_power.jl:174 declares type variable Z but does not use it. WARNING: could not import M_interface_expr_tree._transform_to_Expr_JuMP into M_trait_expr_tree WARNING: Method definition is_expr_tree(Number) in module M_trait_expr_tree at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:28 overwritten at /home/pkgeval/.julia/packages/ExpressionTreeForge/vqeSK/src/expr_tree/tr_expr_tree.jl:29. Precompiling Symbolics... 2891.8 ms ? DomainSets Info Given Symbolics was explicitly requested, output will be shown live  WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/pkgeval/.julia/packages/IntervalSets/kyCuf/src/IntervalSets.jl:296 overwritten in module DomainSets at /home/pkgeval/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52. ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. 3571.2 ms ? Symbolics WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/pkgeval/.julia/packages/IntervalSets/kyCuf/src/IntervalSets.jl:296 overwritten in module DomainSets at /home/pkgeval/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52. ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. Precompiling DomainSets... Info Given DomainSets was explicitly requested, output will be shown live  WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/pkgeval/.julia/packages/IntervalSets/kyCuf/src/IntervalSets.jl:296 overwritten in module DomainSets at /home/pkgeval/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52. ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. 2922.9 ms ? DomainSets WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/pkgeval/.julia/packages/IntervalSets/kyCuf/src/IntervalSets.jl:296 overwritten in module DomainSets at /home/pkgeval/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52. ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/pkgeval/.julia/packages/IntervalSets/kyCuf/src/IntervalSets.jl:296 overwritten in module DomainSets at /home/pkgeval/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52. WARNING: Wrapping `Vararg` directly in UnionAll is deprecated (wrap the tuple instead). You may need to write `f(x::Vararg{T})` rather than `f(x::Vararg{<:T})` or `f(x::Vararg{T}) where T` instead of `f(x::Vararg{T} where T)`. WARNING: Code.get_symbolify is deprecated, use get_rewrites instead. likely near /home/pkgeval/.julia/packages/Symbolics/VIBnK/src/build_function.jl:130 WARNING: method definition for #MOIObjectiveBackend#2 at /home/pkgeval/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/backends/ObjectiveBackends/MOIObjectiveBackend.jl:19 declares type variable T but does not use it. ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 Test Summary: | Pass Total Time NLPModels.methods | 6 6 1m49.2s ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 Test Summary: | Pass Total Time trunk | 8 8 39.0s ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:151 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:151 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:151 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:176 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The gradient computes each element contribution from the Evaluator of an MathOptInterface.Nonlinear.Model └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:179 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model representing a modifier obejctive function └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:183 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model representing a partially-separable function for which each constraint is an element function └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:186 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 Test Summary: | Pass Total Time Merge, from a limit function | 14 14 21.6s ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:176 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The gradient computes each element contribution from the Evaluator of an MathOptInterface.Nonlinear.Model └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:179 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model representing a modifier obejctive function └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:183 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 ┌ Warning: mem usage to important, reduction to an unstructured structure └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:146 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model representing a partially-separable function for which each constraint is an element function └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:186 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 Test Summary: | Pass Total Time Methods after merging + x[1] may not appear in the expression tree | 16 16 8.6s ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 Test Summary: | Pass Total Time test PartiallySeparableNLPModels (ADNLPModel) | 32 32 9.6s ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:176 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The gradient computes each element contribution from the Evaluator of an MathOptInterface.Nonlinear.Model └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:179 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model representing a modifier obejctive function └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:183 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 ┌ Warning: The objective function is computed by an Evaluator of an MathOptInterface.Nonlinear.Model representing a partially-separable function for which each constraint is an element function └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:186 ┌ Warning: Common backend for the objective and the gradient └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:203 Test Summary: | Pass Total Time test PartiallySeparableNLPModels (JuMPModel) | 46 46 33.3s ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 Test Summary: | Pass Total Time hessop | 8 8 2.5s ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ADNLPModel - Model with automatic differentiation backend ADModelBackend{ ForwardDiffADGradient, ForwardDiffADHvprod, EmptyADbackend, EmptyADbackend, EmptyADbackend, SparseADHessian, EmptyADbackend, } Problem name: arwhead All variables: ████████████████████ 10 All constraints: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 free: ████████████████████ 10 free: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 lower: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 lower: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 upper: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 upper: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 low/upp: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 low/upp: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 fixed: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 fixed: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 infeas: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 infeas: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 nnzh: ( 65.45% sparsity) 19 linear: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 nonlinear: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 nnzj: (------% sparsity) Counters: obj: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 grad: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 cons: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 cons_lin: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 cons_nln: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jcon: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jgrad: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jac: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jac_lin: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jac_nln: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jprod: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jprod_lin: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jprod_nln: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jtprod: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jtprod_lin: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jtprod_nln: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 hess: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 hprod: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jhess: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jhprod: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 Partitioned structure summary: element functions: ████████████████████ 10 distinct element functions: ████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2 Element statistics: constant: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 convex: ████████████████████ 9 linear: ███⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 1 concave: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 quadratic: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 general: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 cubic: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 general: ████████████████████ 9 Element function dimensions: Variable overlaps: min: █████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2.0 min: █████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2.0 mean: ██████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2.7 mean: ██████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2.7 max: ████████████████████ 9.0 max: ████████████████████ 9.0 ┌ Warning: The objective function is computed NLPModels.obj(nlp, x), nlp being the original NLPModel └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:197 ┌ Warning: The gradient computes each element contribution from a ReverseDiff.GradientTape └ @ PartiallySeparableNLPModels.Utils ~/.julia/packages/PartiallySeparableNLPModels/HO2HZ/src/partitionedNLPModels/utils.jl:230 ADNLPModel - Model with automatic differentiation backend ADModelBackend{ ForwardDiffADGradient, ForwardDiffADHvprod, EmptyADbackend, EmptyADbackend, EmptyADbackend, SparseADHessian, EmptyADbackend, } Problem name: arwhead All variables: ████████████████████ 10 All constraints: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 free: ████████████████████ 10 free: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 lower: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 lower: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 upper: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 upper: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 low/upp: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 low/upp: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 fixed: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 fixed: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 infeas: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 infeas: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 nnzh: ( 65.45% sparsity) 19 linear: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 nonlinear: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 nnzj: (------% sparsity) Counters: obj: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 grad: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 cons: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 cons_lin: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 cons_nln: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jcon: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jgrad: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jac: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jac_lin: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jac_nln: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jprod: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jprod_lin: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jprod_nln: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jtprod: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jtprod_lin: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jtprod_nln: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 hess: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 hprod: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jhess: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 jhprod: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 Partitioned structure summary: element functions: ████████████████████ 10 distinct element functions: ████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2 Element statistics: constant: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 convex: ████████████████████ 9 linear: ███⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 1 concave: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 quadratic: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 general: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 cubic: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0 general: ████████████████████ 9 Element function dimensions: Variable overlaps: min: █████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2.0 min: █████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2.0 mean: ██████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2.7 mean: ██████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 2.7 max: ████████████████████ 9.0 max: ████████████████████ 9.0 not done yet Test Summary: | Pass Total Time show | 1 1 16.3s Test Summary: | Pass Total Time Backend errors | 3 3 0.3s Testing PartiallySeparableNLPModels tests passed Testing completed after 500.31s PkgEval succeeded after 572.77s