Package evaluation of CTParser on Julia 1.13.0-DEV.912 (a2457e6ed7*) started at 2025-07-27T12:02:09.571 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 8.96s ################################################################################ # Installation # Installing CTParser... Resolving package versions... Installed CTParser ─ v0.6.0 Updating `~/.julia/environments/v1.13/Project.toml` [32681960] + CTParser v0.6.0 Updating `~/.julia/environments/v1.13/Manifest.toml` [54762871] + CTBase v0.16.3 [32681960] + CTParser v0.6.0 [ffbed154] + DocStringExtensions v0.9.5 [d8e11817] + MLStyle v0.4.17 [bac558e1] + OrderedCollections v1.8.1 [d96e819e] + Parameters v0.12.3 [3a884ed6] + UnPack v1.0.2 [4ec0a83e] + Unicode v1.11.0 Installation completed after 4.52s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 308.64s ################################################################################ # Testing # Testing CTParser Status `/tmp/jl_uoIiZU/Project.toml` [4c88cf16] Aqua v0.8.13 [6e4b80f9] BenchmarkTools v1.6.0 [54762871] CTBase v0.16.3 [34c4fa32] CTModels v0.6.2 [32681960] CTParser v0.6.0 [052768ef] CUDA v5.8.2 [1037b233] ExaModels v0.8.3 [a98d9a8b] Interpolations v0.16.1 [63c18a36] KernelAbstractions v0.9.38 ⌃ [2621e9c9] MadNLP v0.8.7 ⌃ [d72a61cc] MadNLPGPU v0.7.7 [8dfed614] Test v1.11.0 Status `/tmp/jl_uoIiZU/Manifest.toml` Precompiling packages... 6630.3 ms ✓ CUDA_Runtime_jll 1 dependency successfully precompiled in 7 seconds. 30 already precompiled. [14f7f29c] AMD v0.5.3 [621f4979] AbstractFFTs v1.5.0 [79e6a3ab] Adapt v4.3.0 [4c88cf16] Aqua v0.8.13 [a9b6321e] Atomix v1.1.1 [13072b0f] AxisAlgorithms v1.1.0 [ab4f0b2a] BFloat16s v0.5.1 [6e4b80f9] BenchmarkTools v1.6.0 [fa961155] CEnum v0.5.0 [54762871] CTBase v0.16.3 [34c4fa32] CTModels v0.6.2 [32681960] CTParser v0.6.0 [052768ef] CUDA v5.8.2 ⌅ [1af6417a] CUDA_Runtime_Discovery v0.3.5 ⌅ [45b445bb] CUDSS v0.4.4 [a8cc9031] CUSOLVERRF v0.2.6 [d360d2e6] ChainRulesCore v1.25.2 [3da002f7] ColorTypes v0.12.1 [5ae59095] Colors v0.13.1 [34da2185] Compat v4.17.0 [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 [ffbed154] DocStringExtensions v0.9.5 [1037b233] ExaModels v0.8.3 [e2ba6199] ExprTools v0.1.10 [9aa1b823] FastClosures v0.3.2 [53c48c17] FixedPointNumbers v0.8.5 [0c68f7d7] GPUArrays v11.2.3 [46192b85] GPUArraysCore v0.2.0 [61eb1bfa] GPUCompiler v1.6.1 ⌅ [096a3bc2] GPUToolbox v0.2.0 [076d061b] HashArrayMappedTries v0.2.0 [842dd82b] InlineStrings v1.4.4 [a98d9a8b] Interpolations v0.16.1 [41ab1584] InvertedIndices v1.3.1 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.1 [682c06a0] JSON v0.21.4 [ef3ab10e] KLU v0.6.0 [63c18a36] KernelAbstractions v0.9.38 [40e66cde] LDLFactorizations v0.10.1 [929cbde3] LLVM v9.4.2 [8b046642] LLVMLoopInfo v1.0.0 [b964fa9f] LaTeXStrings v1.4.0 [5c8ed15e] LinearOperators v2.10.0 [d8e11817] MLStyle v0.4.17 [1914dd2f] MacroTools v0.5.16 ⌃ [2621e9c9] MadNLP v0.8.7 ⌃ [d72a61cc] MadNLPGPU v0.7.7 [2679e427] Metis v1.5.0 [e1d29d7a] Missings v1.2.0 [a4795742] NLPModels v0.21.5 [5da4648a] NVTX v1.0.0 [6fe1bfb0] OffsetArrays v1.17.0 [bac558e1] OrderedCollections v1.8.1 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.3 [2dfb63ee] PooledArrays v1.4.3 [aea7be01] PrecompileTools v1.3.2 [21216c6a] Preferences v1.4.3 [08abe8d2] PrettyTables v2.4.0 [74087812] Random123 v1.7.1 [e6cf234a] RandomNumbers v1.6.0 [c84ed2f1] Ratios v0.4.5 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [7e506255] ScopedValues v1.4.0 [6c6a2e73] Scratch v1.3.0 [91c51154] SentinelArrays v1.4.8 [ff4d7338] SolverCore v0.3.8 [a2af1166] SortingAlgorithms v1.2.1 [90137ffa] StaticArrays v1.9.14 [1e83bf80] StaticArraysCore v1.4.3 [10745b16] Statistics v1.11.1 [892a3eda] StringManipulation v0.4.1 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [a759f4b9] TimerOutputs v0.5.29 [e689c965] Tracy v0.1.5 [3a884ed6] UnPack v1.0.2 [013be700] UnsafeAtomics v0.3.0 [efce3f68] WoodburyMatrices v1.0.0 ⌅ [4ee394cb] CUDA_Driver_jll v0.13.1+0 ⌅ [76a88914] CUDA_Runtime_jll v0.17.1+0 ⌅ [4889d778] CUDSS_jll v0.4.0+0 [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0 [dad2f222] LLVMExtra_jll v0.0.37+2 [ad6e5548] LibTracyClient_jll v0.9.1+6 [d00139f3] METIS_jll v5.1.3+0 [e98f9f5b] NVTX_jll v3.2.1+0 [1e29f10c] demumble_jll v1.3.0+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 v1.13.0 [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 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization v1.11.0 [1a1011a3] SharedArrays v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [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 v8.15.0+0 [e37daf67] LibGit2_jll v1.9.1+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.7.15 [4536629a] OpenBLAS_jll v0.3.29+0 [458c3c95] OpenSSL_jll v3.5.1+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... 1496.2 ms ✓ LinearOperators → LinearOperatorsChainRulesCoreExt 1 dependency successfully precompiled in 2 seconds. 17 already precompiled. Precompiling packages... 1392.6 ms ✓ METIS_jll 83211.0 ms ✓ DataFrames 8443.2 ms ✓ KernelAbstractions 5501.5 ms ✓ CUDSS_jll 82258.3 ms ✓ GPUCompiler 2569.1 ms ✓ Metis 3044.8 ms ✓ KernelAbstractions → SparseArraysExt 2553.1 ms ✓ KernelAbstractions → LinearAlgebraExt 15473.4 ms ✓ GPUArrays 148526.1 ms ✓ CUDA 33103.4 ms ✓ LinearOperators → LinearOperatorsCUDAExt 36790.4 ms ✓ Atomix → AtomixCUDAExt 36108.4 ms ✓ CUSOLVERRF 37808.2 ms ✓ CUDSS 43195.4 ms ✓ MadNLPGPU 15 dependencies successfully precompiled in 540 seconds. 109 already precompiled. 2 dependencies had output during precompilation: ┌ CUDA │ WARNING: Constructor for type "Int" was extended in `CUDA` without explicit qualification or import. │ NOTE: Assumed "Int" refers to `Base.Int`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function Int end`. │ Hint: To silence the warning, qualify `Int` as `Base.Int` in the method signature or explicitly `import Base: Int`. │ WARNING: Constructor for type "UInt" was extended in `CUDA` without explicit qualification or import. │ NOTE: Assumed "UInt" refers to `Base.UInt`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function UInt end`. │ Hint: To silence the warning, qualify `UInt` as `Base.UInt` in the method signature or explicitly `import Base: UInt`. │ WARNING: Constructor for type "BroadcastStyle" was extended in `CUDA` without explicit qualification or import. │ NOTE: Assumed "BroadcastStyle" refers to `Broadcast.BroadcastStyle`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function BroadcastStyle end`. │ Hint: To silence the warning, qualify `BroadcastStyle` as `Broadcast.BroadcastStyle` in the method signature or explicitly `import Broadcast: BroadcastStyle`. │ WARNING: Constructor for type "CuArray" was extended in `CUBLAS` without explicit qualification or import. │ NOTE: Assumed "CuArray" refers to `CUDA.CuArray`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function CuArray end`. │ Hint: To silence the warning, qualify `CuArray` as `CUDA.CuArray` in the method signature or explicitly `import CUDA: CuArray`. │ WARNING: Constructor for type "SparseVector" was extended in `CUSPARSE` without explicit qualification or import. │ NOTE: Assumed "SparseVector" refers to `SparseArrays.SparseVector`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function SparseVector end`. │ Hint: To silence the warning, qualify `SparseVector` as `SparseArrays.SparseVector` in the method signature or explicitly `import SparseArrays: SparseVector`. │ WARNING: Constructor for type "SparseMatrixCSC" was extended in `CUSPARSE` without explicit qualification or import. │ NOTE: Assumed "SparseMatrixCSC" refers to `SparseArrays.SparseMatrixCSC`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function SparseMatrixCSC end`. │ Hint: To silence the warning, qualify `SparseMatrixCSC` as `SparseArrays.SparseMatrixCSC` in the method signature or explicitly `import SparseArrays: SparseMatrixCSC`. │ WARNING: Constructor for type "CuVector" was extended in `CUSPARSE` without explicit qualification or import. │ NOTE: Assumed "CuVector" refers to `CUDA.CuVector`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function CuVector end`. │ Hint: To silence the warning, qualify `CuVector` as `CUDA.CuVector` in the method signature or explicitly `import CUDA: CuVector`. │ WARNING: Constructor for type "CuMatrix" was extended in `CUSOLVER` without explicit qualification or import. │ NOTE: Assumed "CuMatrix" refers to `CUDA.CuMatrix`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function CuMatrix end`. │ Hint: To silence the warning, qualify `CuMatrix` as `CUDA.CuMatrix` in the method signature or explicitly `import CUDA: CuMatrix`. │ WARNING: Constructor for type "CuArray" was extended in `CUSOLVER` without explicit qualification or import. │ NOTE: Assumed "CuArray" refers to `CUDA.CuArray`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function CuArray end`. │ Hint: To silence the warning, qualify `CuArray` as `CUDA.CuArray` in the method signature or explicitly `import CUDA: CuArray`. └ ┌ CUSOLVERRF │ WARNING: Imported binding CUSOLVER.libcusolver was undeclared at import time during import to CUSOLVERRF. └ Precompiling packages... 11241.9 ms ✓ ExaModels → ExaModelsKernelAbstractions 1 dependency successfully precompiled in 11 seconds. 34 already precompiled. Precompiling packages... 38326.6 ms ✓ ExaModels → ExaModelsCUDA 1 dependency successfully precompiled in 39 seconds. 112 already precompiled. Precompiling packages... 38681.8 ms ✓ CUDA → ChainRulesCoreExt 1 dependency successfully precompiled in 39 seconds. 108 already precompiled. Precompiling packages... 3884.1 ms ✓ BenchmarkTools 1 dependency successfully precompiled in 4 seconds. 16 already precompiled. auxiliary functions (CPU) pragma (CPU) Barracuda sors de ce corps ! grid_size = 250 alias (CPU) time (CPU) constraint (CPU) Line 7: -1 ≤ x₂(0) + x₁(tf) + tf ≤ [1, 2] Line 7: tf ^ 2 ≥ [1, 5] Line 7: cos(x₁(t)) ≤ [1, 2] Line 7: cos(u(t)) ≤ [1, 2] Line 7: x₁(t) + u(t) == [1, 2] variable range (CPU) state range (CPU) control range (CPU) dynamics (CPU) Line 5: ẋ(t) == t + u₁(t) lagrange cost (CPU) scalar bounds test Line 4: x(0) ^ 2 == [-1, 0, 0] variable bounds test Line 5: v[1:2] ≤ 3 state bounds test Line 6: (x[1:2])(t) == [0, 0, 0] control bounds test Line 7: u(t) ≤ [1, 2] path bounds test Line 7: 3 ≤ x[1] + u(t) ≤ [1, 2] path bounds test Line 7: [3, 4] ≤ x[1] + u(t) ≤ [1, 2] initial bounds test Line 5: x(0) == [-1, 0] final bounds test Line 5: x(1) == [-1, 0] use case no. 1: simple example (mayer) (CPU) This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 3005 Number of nonzeros in Lagrangian Hessian.............: 2250 Total number of variables............................: 1004 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 755 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.0000000e-01 1.10e+00 1.27e-12 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 -5.0000000e-03 7.36e-02 2.77e-12 -1.0 6.08e+00 - 1.00e+00 1.00e+00h 1 2 6.0003829e+00 2.53e-15 8.88e-16 -2.5 6.01e+00 - 1.00e+00 1.00e+00h 1 Number of Iterations....: 2 (scaled) (unscaled) Objective...............: 6.0003828724303245e+00 6.0003828724303245e+00 Dual infeasibility......: 8.8817841970012523e-16 8.8817841970012523e-16 Constraint violation....: 2.5257573810222311e-15 2.5257573810222311e-15 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 2.5257573810222311e-15 2.5257573810222311e-15 Number of objective function evaluations = 3 Number of objective gradient evaluations = 3 Number of constraint evaluations = 3 Number of constraint Jacobian evaluations = 3 Number of Lagrangian Hessian evaluations = 2 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 101.141 Total wall-clock secs in linear solver = 0.261 Total wall-clock secs in NLP function evaluations = 0.000 Total wall-clock secs = 101.402 EXIT: Optimal Solution Found (tol = 1.0e-08). This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 12005 Number of nonzeros in Lagrangian Hessian.............: 9000 Total number of variables............................: 4004 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 3005 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.0000000e-01 1.10e+00 1.72e-12 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 -5.0000000e-03 1.86e-02 3.63e-12 -1.0 6.09e+00 - 1.00e+00 1.00e+00h 1 2 6.0000240e+00 2.48e-15 8.88e-16 -3.8 6.01e+00 - 1.00e+00 1.00e+00h 1 Number of Iterations....: 2 (scaled) (unscaled) Objective...............: 6.0000239820958532e+00 6.0000239820958532e+00 Dual infeasibility......: 8.8817841970012523e-16 8.8817841970012523e-16 Constraint violation....: 2.4806545706468341e-15 2.4806545706468341e-15 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 2.4806545706468341e-15 2.4806545706468341e-15 Number of objective function evaluations = 3 Number of objective gradient evaluations = 3 Number of constraint evaluations = 3 Number of constraint Jacobian evaluations = 3 Number of Lagrangian Hessian evaluations = 2 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 0.014 Total wall-clock secs in linear solver = 0.057 Total wall-clock secs in NLP function evaluations = 0.001 Total wall-clock secs = 0.072 EXIT: Optimal Solution Found (tol = 1.0e-08). use case no. 1: simple example (mayer), testing getters (1/2) (CPU) This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 12005 Number of nonzeros in Lagrangian Hessian.............: 9000 Total number of variables............................: 4004 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 3005 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.0000000e-01 1.10e+00 1.72e-12 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 -5.0000000e-03 1.86e-02 3.63e-12 -1.0 6.09e+00 - 1.00e+00 1.00e+00h 1 2 6.0000240e+00 2.48e-15 8.88e-16 -3.8 6.01e+00 - 1.00e+00 1.00e+00h 1 Number of Iterations....: 2 (scaled) (unscaled) Objective...............: 6.0000239820958532e+00 6.0000239820958532e+00 Dual infeasibility......: 8.8817841970012523e-16 8.8817841970012523e-16 Constraint violation....: 2.4806545706468341e-15 2.4806545706468341e-15 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 2.4806545706468341e-15 2.4806545706468341e-15 Number of objective function evaluations = 3 Number of objective gradient evaluations = 3 Number of constraint evaluations = 3 Number of constraint Jacobian evaluations = 3 Number of Lagrangian Hessian evaluations = 2 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 0.014 Total wall-clock secs in linear solver = 0.054 Total wall-clock secs in NLP function evaluations = 0.001 Total wall-clock secs = 0.069 EXIT: Optimal Solution Found (tol = 1.0e-08). use case no. 1: simple example (mayer), testing getters (2/2) (CPU) This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 14005 Number of nonzeros in Lagrangian Hessian.............: 16000 Total number of variables............................: 5005 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 3005 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.0000000e-01 1.10e+00 1.00e-04 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 -1.0033370e-02 1.85e-02 2.94e-05 -1.0 6.08e+00 - 1.00e+00 1.00e+00h 1 2 6.0000132e+00 8.41e-08 2.93e-12 -3.8 6.01e+00 - 1.00e+00 1.00e+00h 1 3 6.0000240e+00 8.12e-16 8.88e-16 -8.6 1.08e-05 - 1.00e+00 1.00e+00h 1 Number of Iterations....: 3 (scaled) (unscaled) Objective...............: 6.0000239820958559e+00 6.0000239820958559e+00 Dual infeasibility......: 8.8817841970012523e-16 8.8817841970012523e-16 Constraint violation....: 8.1185058675714572e-16 8.1185058675714572e-16 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 8.8817841970012523e-16 8.8817841970012523e-16 Number of objective function evaluations = 4 Number of objective gradient evaluations = 4 Number of constraint evaluations = 4 Number of constraint Jacobian evaluations = 4 Number of Lagrangian Hessian evaluations = 3 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 47.449 Total wall-clock secs in linear solver = 0.103 Total wall-clock secs in NLP function evaluations = 0.002 Total wall-clock secs = 47.554 EXIT: Optimal Solution Found (tol = 1.0e-08). use case no. 1: simple example (lagrange) (CPU) This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 2004 Number of nonzeros in Lagrangian Hessian.............: 1751 Total number of variables............................: 753 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 504 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 5.0000000e-03 1.10e+00 4.16e-17 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 6.0003829e+00 1.64e-15 3.18e-13 -1.0 6.08e+00 - 1.00e+00 1.00e+00h 1 Number of Iterations....: 1 (scaled) (unscaled) Objective...............: 6.0003828724303343e+00 6.0003828724303343e+00 Dual infeasibility......: 3.1796787425264483e-13 3.1796787425264483e-13 Constraint violation....: 1.6410484082740595e-15 1.6410484082740595e-15 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 3.1796787425264483e-13 3.1796787425264483e-13 Number of objective function evaluations = 2 Number of objective gradient evaluations = 2 Number of constraint evaluations = 2 Number of constraint Jacobian evaluations = 2 Number of Lagrangian Hessian evaluations = 1 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 42.757 Total wall-clock secs in linear solver = 0.007 Total wall-clock secs in NLP function evaluations = 0.000 Total wall-clock secs = 42.765 EXIT: Optimal Solution Found (tol = 1.0e-07). This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 8004 Number of nonzeros in Lagrangian Hessian.............: 7001 Total number of variables............................: 3003 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 2004 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 5.0000000e-03 1.10e+00 5.55e-17 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 6.0000240e+00 1.72e-15 3.30e-13 -1.0 6.09e+00 - 1.00e+00 1.00e+00h 1 Number of Iterations....: 1 (scaled) (unscaled) Objective...............: 6.0000239820961445e+00 6.0000239820961445e+00 Dual infeasibility......: 3.3040237212844659e-13 3.3040237212844659e-13 Constraint violation....: 1.7156415177410622e-15 1.7156415177410622e-15 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 3.3040237212844659e-13 3.3040237212844659e-13 Number of objective function evaluations = 2 Number of objective gradient evaluations = 2 Number of constraint evaluations = 2 Number of constraint Jacobian evaluations = 2 Number of Lagrangian Hessian evaluations = 1 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 0.011 Total wall-clock secs in linear solver = 0.027 Total wall-clock secs in NLP function evaluations = 0.001 Total wall-clock secs = 0.038 EXIT: Optimal Solution Found (tol = 1.0e-07). use case no. 1: simple example (bolza) (CPU) This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 3005 Number of nonzeros in Lagrangian Hessian.............: 2501 Total number of variables............................: 1004 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 755 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.0500000e-01 1.10e+00 1.55e-12 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 1.2000766e+01 8.15e-14 3.34e-12 -1.0 6.08e+00 - 1.00e+00 1.00e+00H 1 Number of Iterations....: 1 (scaled) (unscaled) Objective...............: 1.2000765744860379e+01 1.2000765744860379e+01 Dual infeasibility......: 3.3395508580724709e-12 3.3395508580724709e-12 Constraint violation....: 8.1526799200482003e-14 8.1526799200482003e-14 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 3.3395508580724709e-12 3.3395508580724709e-12 Number of objective function evaluations = 3 Number of objective gradient evaluations = 2 Number of constraint evaluations = 3 Number of constraint Jacobian evaluations = 2 Number of Lagrangian Hessian evaluations = 1 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 40.751 Total wall-clock secs in linear solver = 0.011 Total wall-clock secs in NLP function evaluations = 0.000 Total wall-clock secs = 40.762 EXIT: Optimal Solution Found (tol = 1.0e-07). This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 12005 Number of nonzeros in Lagrangian Hessian.............: 10001 Total number of variables............................: 4004 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 3005 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.0500000e-01 1.10e+00 2.21e-12 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 1.2000048e+01 8.60e-13 4.07e-12 -1.0 6.09e+00 - 1.00e+00 1.00e+00H 1 Number of Iterations....: 1 (scaled) (unscaled) Objective...............: 1.2000047964213135e+01 1.2000047964213135e+01 Dual infeasibility......: 4.0678571622265736e-12 4.0678571622265736e-12 Constraint violation....: 8.6045797223488485e-13 8.6045797223488485e-13 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 4.0678571622265736e-12 4.0678571622265736e-12 Number of objective function evaluations = 3 Number of objective gradient evaluations = 2 Number of constraint evaluations = 3 Number of constraint Jacobian evaluations = 2 Number of Lagrangian Hessian evaluations = 1 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 0.016 Total wall-clock secs in linear solver = 0.040 Total wall-clock secs in NLP function evaluations = 0.001 Total wall-clock secs = 0.056 EXIT: Optimal Solution Found (tol = 1.0e-07). use case no. 2: Goddard (CPU) This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 3804 Number of nonzeros in Lagrangian Hessian.............: 12200 Total number of variables............................: 805 variables with only lower bounds: 201 variables with lower and upper bounds: 402 variables with only upper bounds: 0 Total number of equality constraints.................: 604 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 -1.2354900e+00 1.84e-01 9.17e-02 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 -1.2213727e+00 1.73e-01 2.26e+01 -1.7 4.63e+00 - 2.04e-02 6.11e-02h 1 2 -1.1676891e+00 1.30e-01 3.91e+01 -1.7 1.30e+00 - 8.91e-02 2.46e-01h 1 3 -1.0067269e+00 1.31e-03 3.27e+02 -1.7 3.79e-01 - 5.52e-01 9.90e-01h 1 4 -1.0104816e+00 4.82e-04 3.96e+02 -1.7 3.46e-01 - 6.67e-01 8.53e-01h 1 5 -1.0084533e+00 1.25e-04 1.00e+04 -1.7 9.94e-02 - 3.89e-01 9.91e-01h 1 6 -1.0084494e+00 2.46e-05 3.69e-02 -1.7 8.70e-02 - 1.00e+00 1.00e+00h 1 7 -1.0084450e+00 3.73e-08 2.10e-02 -2.5 9.66e-03 - 1.00e+00 1.00e+00h 1 8 -1.0084673e+00 1.36e-08 1.83e-02 -3.8 3.40e-03 - 1.00e+00 1.00e+00h 1 9 -1.0088520e+00 3.75e-06 3.66e-04 -3.8 6.04e-02 - 1.00e+00 1.00e+00h 1 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 10 -1.0091890e+00 1.25e-06 6.43e+02 -5.7 3.11e-02 - 9.57e-01 1.00e+00h 1 11 -1.0116140e+00 8.73e-05 2.66e-01 -5.7 1.66e-01 - 1.00e+00 8.23e-01h 1 12 -1.0123133e+00 2.92e-05 9.47e-03 -5.7 8.95e-02 - 1.00e+00 9.89e-01h 1 13 -1.0122685e+00 9.03e-07 3.02e-05 -5.7 5.13e-02 - 1.00e+00 1.00e+00h 1 14 -1.0122728e+00 6.08e-08 1.96e-07 -5.7 8.44e-03 - 1.00e+00 1.00e+00h 1 15 -1.0125174e+00 5.95e-06 1.34e+01 -8.0 5.57e-02 - 9.09e-01 8.36e-01h 1 16 -1.0125543e+00 3.93e-06 4.95e+00 -8.0 1.04e-01 - 6.46e-01 6.39e-01h 1 17 -1.0125684e+00 2.05e-06 1.42e+00 -8.0 8.63e-02 - 7.20e-01 7.17e-01h 1 18 -1.0125737e+00 1.28e-06 8.11e-06 -8.0 8.77e-02 - 1.00e+00 1.00e+00h 1 19 -1.0125736e+00 2.14e-07 1.01e-06 -8.0 1.02e-01 - 1.00e+00 1.00e+00h 1 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 20 -1.0125736e+00 9.18e-09 3.32e-08 -8.0 1.64e-02 - 1.00e+00 1.00e+00h 1 Number of Iterations....: 20 (scaled) (unscaled) Objective...............: -1.0125736217159587e+00 -1.0125736217159587e+00 Dual infeasibility......: 3.3150771136360651e-08 3.3150771136360651e-08 Constraint violation....: 9.1832485186061491e-09 9.1832485186061491e-09 Complementarity.........: 9.3716248351037360e-09 9.3716248351037360e-09 Overall NLP error.......: 3.3150771136360651e-08 3.3150771136360651e-08 Number of objective function evaluations = 21 Number of objective gradient evaluations = 21 Number of constraint evaluations = 21 Number of constraint Jacobian evaluations = 21 Number of Lagrangian Hessian evaluations = 20 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 60.955 Total wall-clock secs in linear solver = 0.103 Total wall-clock secs in NLP function evaluations = 0.008 Total wall-clock secs = 61.067 EXIT: Optimal Solution Found (tol = 1.0e-07). use case no. 3: quadrotor (CPU) This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 4309 Number of nonzeros in Lagrangian Hessian.............: 5900 Total number of variables............................: 1313 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 909 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.8397000e+00 1.00e-01 4.39e-03 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 4.4840712e+00 4.52e-02 3.26e-02 -2.5 9.16e+00 -4.0 1.00e+00 1.00e+00h 1 2 4.0680842e+00 6.44e-03 1.68e-03 -2.5 3.05e+00 -4.5 1.00e+00 1.00e+00h 1 3 4.2061913e+00 1.07e-04 7.31e-05 -3.8 3.85e-01 -5.0 1.00e+00 1.00e+00h 1 4 4.2064196e+00 1.13e-08 2.20e-08 -5.7 4.36e-03 -5.4 1.00e+00 1.00e+00h 1 5 4.2064197e+00 7.64e-14 1.83e-11 -9.0 1.48e-05 -5.9 1.00e+00 1.00e+00h 1 Number of Iterations....: 5 (scaled) (unscaled) Objective...............: 4.2064197085695820e+00 4.2064197085695820e+00 Dual infeasibility......: 1.8321290665146428e-11 1.8321290665146428e-11 Constraint violation....: 7.6431916351538121e-14 7.6431916351538121e-14 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 1.8321290665146428e-11 1.8321290665146428e-11 Number of objective function evaluations = 6 Number of objective gradient evaluations = 6 Number of constraint evaluations = 6 Number of constraint Jacobian evaluations = 6 Number of Lagrangian Hessian evaluations = 5 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 59.526 Total wall-clock secs in linear solver = 0.135 Total wall-clock secs in NLP function evaluations = 0.002 Total wall-clock secs = 59.663 EXIT: Optimal Solution Found (tol = 1.0e-08). This is MadNLP version v0.8.7, running with umfpack Number of nonzeros in constraint Jacobian............: 4309 Number of nonzeros in Lagrangian Hessian.............: 5900 Total number of variables............................: 1313 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 909 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.8577000e+00 1.00e-01 4.58e-03 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 4.6660886e+00 5.21e-02 3.94e-02 -2.5 9.51e+00 -4.0 1.00e+00 1.00e+00h 1 2 4.1138294e+00 9.36e-03 1.89e-03 -2.5 3.54e+00 -4.5 1.00e+00 1.00e+00h 1 3 4.3286478e+00 2.69e-04 1.31e-04 -3.8 5.94e-01 -5.0 1.00e+00 1.00e+00h 1 4 4.3292020e+00 6.16e-08 9.83e-08 -5.7 9.85e-03 -5.4 1.00e+00 1.00e+00h 1 5 4.3292025e+00 4.25e-13 3.24e-11 -8.6 2.62e-05 -5.9 1.00e+00 1.00e+00h 1 Number of Iterations....: 5 (scaled) (unscaled) Objective...............: 4.3292025149922306e+00 4.3292025149922306e+00 Dual infeasibility......: 3.2399156274509622e-11 3.2399156274509622e-11 Constraint violation....: 4.2471408334687766e-13 4.2471408334687766e-13 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 3.2399156274509622e-11 3.2399156274509622e-11 Number of objective function evaluations = 6 Number of objective gradient evaluations = 6 Number of constraint evaluations = 6 Number of constraint Jacobian evaluations = 6 Number of Lagrangian Hessian evaluations = 5 Total wall-clock secs in solver (w/o fun. eval./lin. alg.) = 57.187 Total wall-clock secs in linear solver = 0.111 Total wall-clock secs in NLP function evaluations = 0.002 Total wall-clock secs = 57.301 EXIT: Optimal Solution Found (tol = 1.0e-08). ********** CUDA not available Test Summary: | Pass Total Time CTParser tests | 90 90 20m02.9s onepass_exa | 90 90 20m02.9s Testing CTParser tests passed Testing completed after 1904.98s PkgEval succeeded after 2247.87s