Package evaluation to test SDDP on Julia 1.13.0-alpha2.30 (5abf758bb1*) started at 2026-01-09T06:19:53.801 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 10.98s ################################################################################ # Installation # Installing SDDP... Resolving package versions... Installed Bzip2_jll ──────────── v1.0.9+0 Installed DiffResults ────────── v1.1.0 Installed ConcurrentUtilities ── v2.5.0 Installed CodecZlib ──────────── v0.7.8 Installed ExprTools ──────────── v0.1.10 Installed MacroTools ─────────── v0.5.16 Installed URIs ───────────────── v1.6.1 Installed ForwardDiff ────────── v1.3.1 Installed ExceptionUnwrapping ── v0.1.11 Installed RecipesBase ────────── v1.3.4 Installed Compat ─────────────── v4.18.1 Installed OrderedCollections ─── v1.8.1 Installed Statistics ─────────── v1.11.1 Installed TranscodingStreams ─── v0.11.3 Installed PrecompileTools ────── v1.3.3 Installed CommonSubexpressions ─ v0.3.1 Installed StaticArraysCore ───── v1.4.4 Installed LoggingExtras ──────── v1.2.0 Installed TimerOutputs ───────── v0.5.29 Installed MbedTLS ────────────── v1.1.9 Installed StructUtils ────────── v2.6.1 Installed OpenSSL ────────────── v1.6.1 Installed IrrationalConstants ── v0.2.6 Installed NaNMath ────────────── v1.1.3 Installed OpenSpecFun_jll ────── v0.5.6+0 Installed CodecBzip2 ─────────── v0.8.5 Installed JSON3 ──────────────── v1.14.3 Installed HTTP ───────────────── v1.10.19 Installed BitFlags ───────────── v0.1.9 Installed LogExpFunctions ────── v0.3.29 Installed DiffRules ──────────── v1.15.1 Installed Parsers ────────────── v2.8.3 Installed Reexport ───────────── v1.2.2 Installed SpecialFunctions ───── v2.6.1 Installed JSON ───────────────── v1.3.0 Installed SimpleBufferStream ─── v1.2.0 Installed Preferences ────────── v1.5.1 Installed MutableArithmetics ─── v1.6.7 Installed JLLWrappers ────────── v1.7.1 Installed BenchmarkTools ─────── v1.6.3 Installed MbedTLS_jll ────────── v2.28.1010+0 Installed SDDP ───────────────── v1.13.1 Installed StructTypes ────────── v1.11.0 Installed JuMP ───────────────── v1.29.3 Installed DocStringExtensions ── v0.9.5 Installed MathOptInterface ───── v1.48.0 Installing 3 artifacts Installed artifact OpenSpecFun 194.9 KiB Installed artifact Bzip2 503.5 KiB Installed artifact MbedTLS 2.2 MiB Updating `~/.julia/environments/v1.13/Project.toml` [f4570300] + SDDP v1.13.1 Updating `~/.julia/environments/v1.13/Manifest.toml` [6e4b80f9] + BenchmarkTools v1.6.3 [d1d4a3ce] + BitFlags v0.1.9 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.18.1 [f0e56b4a] + ConcurrentUtilities v2.5.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [ffbed154] + DocStringExtensions v0.9.5 [460bff9d] + ExceptionUnwrapping v0.1.11 [e2ba6199] + ExprTools v0.1.10 [f6369f11] + ForwardDiff v1.3.1 [cd3eb016] + HTTP v1.10.19 [92d709cd] + IrrationalConstants v0.2.6 [692b3bcd] + JLLWrappers v1.7.1 [682c06a0] + JSON v1.3.0 [0f8b85d8] + JSON3 v1.14.3 [4076af6c] + JuMP v1.29.3 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.48.0 [739be429] + MbedTLS v1.1.9 [d8a4904e] + MutableArithmetics v1.6.7 [77ba4419] + NaNMath v1.1.3 [4d8831e6] + OpenSSL v1.6.1 [bac558e1] + OrderedCollections v1.8.1 [69de0a69] + Parsers v2.8.3 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.1 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [f4570300] + SDDP v1.13.1 [777ac1f9] + SimpleBufferStream v1.2.0 [276daf66] + SpecialFunctions v2.6.1 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [856f2bd8] + StructTypes v1.11.0 [ec057cc2] + StructUtils v2.6.1 [a759f4b9] + TimerOutputs v0.5.29 [3bb67fe8] + TranscodingStreams v0.11.3 [5c2747f8] + URIs v1.6.1 [6e34b625] + Bzip2_jll v1.0.9+0 [c8ffd9c3] + MbedTLS_jll v2.28.1010+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [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 [de0858da] + Printf v1.11.0 [9abbd945] + Profile v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.0.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.11.0 [fa267f1f] + TOML v1.0.3 [8dfed614] + Test v1.11.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [14a3606d] + MozillaCACerts_jll v2025.12.2 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.4+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.15.0+0 Installation completed after 9.57s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling packages... 4922.1 ms ✓ TestEnv 1 dependency successfully precompiled in 5 seconds. 27 already precompiled. Precompiling package dependencies... Precompilation completed after 812.16s ################################################################################ # Testing # Testing SDDP Status `/tmp/jl_p3IovA/Project.toml` [87dc4568] HiGHS v1.20.1 [b6b21f68] Ipopt v1.13.0 [682c06a0] JSON v1.3.0 [7d188eb4] JSONSchema v1.5.0 [91a5bcdd] Plots v1.41.4 [f4570300] SDDP v1.13.1 [10745b16] Statistics v1.11.1 [8ba89e20] Distributed v1.11.0 [f43a241f] Downloads v1.7.0 [44cfe95a] Pkg v1.13.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_p3IovA/Manifest.toml` [66dad0bd] AliasTables v1.1.3 [6e4b80f9] BenchmarkTools v1.6.3 [d1d4a3ce] BitFlags v0.1.9 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [35d6a980] ColorSchemes v3.31.0 [3da002f7] ColorTypes v0.12.1 [c3611d14] ColorVectorSpace v0.11.0 [5ae59095] Colors v0.13.1 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [f0e56b4a] ConcurrentUtilities v2.5.0 [d38c429a] Contour v0.6.3 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.19.3 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Testing Running tests... [ Info: Experimental.jl [ Info: fetching remote ref https://jump.dev/MathOptFormat/schemas/mof.1.schema.json [ Info: Inner.jl Node: 3 - elapsed time: 0.38 plus 7.39 for vertex selection. Node: 2 - elapsed time: 0.32 plus 0.29 for vertex selection. Node: 1 - elapsed time: 0.31 plus 0.29 for vertex selection. First-stage upper bound: 45.83333333333332 Total time for upper bound: 8.97656043 ┌ Warning: You must select an optimizer for performing vertex selection. └ @ SDDP.Inner ~/.julia/packages/SDDP/ScjyB/src/Inner.jl:1048 Node: 19 - elapsed time: 0.39 plus 0.34 for vertex selection. Node: 18 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 17 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 16 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 15 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 14 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 13 - elapsed time: 0.5 plus 0.34 for vertex selection. Node: 12 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 11 - elapsed time: 0.49 plus 0.35 for vertex selection. Node: 10 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 9 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 8 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 7 - elapsed time: 0.47 plus 0.32 for vertex selection. Node: 6 - elapsed time: 0.46 plus 0.34 for vertex selection. Node: 5 - elapsed time: 0.85 plus 0.34 for vertex selection. Node: 4 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 3 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 2 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 1 - elapsed time: 0.48 plus 0.34 for vertex selection. Selection removed 500 vertices [ Info: MSPFormat.jl [ Info: algorithm.jl ┌ Warning: Unable to recover in direct mode! Remove `direct = true` when creating the policy graph. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:401 [ Info: Writing cuts to the file `model_infeasible_node_1.cuts.json` [ Info: Writing cuts to the file `model_infeasible_node_1.cuts.json` ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.AffExpr in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [2, 2] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- † 1 0.000000e+00 0.000000e+00 5.908790e-01 4 1 3 0.000000e+00 0.000000e+00 1.003082e+00 12 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.003082e+00 total solves : 12 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 1 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [4, 4] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.100000e+05 1.075000e+05 8.254919e-01 9 1 20 7.500000e+04 1.075000e+05 1.335810e+00 204 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.335810e+00 total solves : 204 best bound : 1.075000e+05 simulation ci : 8.268750e+04 ± 1.084410e+04 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:1181 ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:1181 [ Info: binary_expansion.jl [ Info: deterministic_equivalent.jl [ Info: modeling_aids.jl ┌ Warning: Budget for nodes is less than the number of stages. Using one node per stage. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/modeling_aids.jl:125 [ Info: user_interface.jl [ Info: backward_sampling_schemes.jl [ Info: bellman_functions.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.138889e+01 1.325140e+00 12 1 10 2.500000e+00 3.361111e+01 1.353828e+00 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.353828e+00 total solves : 120 best bound : 3.361111e+01 simulation ci : 2.775000e+01 ± 3.280073e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.083333e+01 6.118829e-01 12 1 10 2.500000e+00 3.361111e+01 6.469140e-01 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.469140e-01 total solves : 120 best bound : 3.361111e+01 simulation ci : 2.775000e+01 ± 3.280073e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [3, 3] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.250000e+01 5.268631e+01 8.965969e-03 46 1 50 0.000000e+00 1.191663e+02 5.056779e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.056779e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [3, 3] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.250000e+01 5.268631e+01 1.234293e-02 46 1 50 0.000000e+00 1.191663e+02 5.192091e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.192091e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- [ Info: duality_handlers.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 1.00000e+02 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 11] JuMP.AffExpr in MOI.LessThan{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [3, 7] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 7] JuMP.VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -4.650000e+01 -7.053967e+01 2.570848e+00 103 1 3S -5.785826e+01 -6.755367e+01 4.146741e+00 309 1 4S -6.230988e+01 -6.688020e+01 5.162959e+00 412 1 5S -7.577792e+01 -6.680771e+01 6.286723e+00 515 1 6S -6.064080e+01 -6.678327e+01 7.380640e+00 618 1 8S -5.772300e+01 -6.677661e+01 9.497640e+00 824 1 17S -6.068889e+01 -6.677644e+01 1.526852e+01 1751 1 27S -6.068889e+01 -6.677644e+01 2.108901e+01 2781 1 37S -7.668889e+01 -6.677644e+01 2.662800e+01 3811 1 47S -5.768889e+01 -6.677644e+01 3.219671e+01 4841 1 57S -8.368889e+01 -6.677644e+01 3.789715e+01 5871 1 65S -4.168889e+01 -6.677644e+01 4.346189e+01 6695 1 75S -8.368889e+01 -6.677644e+01 4.946851e+01 7725 1 85S -6.068889e+01 -6.677644e+01 5.559101e+01 8755 1 95S -6.468889e+01 -6.677644e+01 6.171631e+01 9785 1 100 -8.368889e+01 -6.677644e+01 6.415701e+01 10300 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.415701e+01 total solves : 10300 best bound : -6.677644e+01 simulation ci : -5.960112e+01 ± 3.154656e+00 numeric issues : 0 ------------------------------------------------------------------- ****************************************************************************** This program contains Ipopt, a library for large-scale nonlinear optimization. Ipopt is released as open source code under the Eclipse Public License (EPL). For more information visit https://github.com/coin-or/Ipopt ****************************************************************************** [ Info: forward_passes.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.VariableRef in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 3.000000e+00 6.000000e+00 5.903959e-03 8 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.903959e-03 total solves : 8 best bound : 6.000000e+00 simulation ci : 3.000000e+00 ± NaN numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:1181 [ Info: local_improvement_search.jl [ Info: exp = 15 [ Info: OA(exp) = 220 [ Info: piecewise = 7 [ Info: OA(piecewise) = 6 [ Info: squared = 3 [ Info: OA(squared) = 16 [ Info: parallel_schemes.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [1, 1] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+00 6.000000e+00 2.191773e+02 2 5 20 5.000000e+00 6.000000e+00 2.234823e+02 40 5 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.234823e+02 total solves : 40 best bound : 6.000000e+00 simulation ci : 5.800000e+00 ± 1.116014e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:1181 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : true options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [4e+00, 4e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 5.000000e+00 6.000000e+00 5.542860e-01 48 1 20 9.000000e+00 6.000000e+00 9.630451e-01 162 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.630451e-01 total solves : 162 best bound : 6.000000e+00 simulation ci : 5.900000e+00 ± 9.633534e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: risk_measures.jl ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/risk_measures.jl:528 [ Info: sampling_schemes.jl [ Info: stopping_rules.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 1.320970e-01 4 1 50 0.000000e+00 0.000000e+00 5.233610e-01 200 1 ------------------------------------------------------------------- status : first_stage_stopping total time (s) : 5.233610e-01 total solves : 200 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/stopping_rules.jl:132 Simulated policy value: [ 5.035598e+00, 6.964402e+00] Simulated policy value: [ 5.282880e+00, 7.117120e+00] Simulated policy value: [ 5.606329e+00, 7.393671e+00] ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/stopping_rules.jl:132 Simulated policy value: [ 5.035598e+00, 6.964402e+00] Simulated policy value: [ 5.282880e+00, 7.117120e+00] Simulated policy value: [ 5.606329e+00, 7.393671e+00] ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/stopping_rules.jl:132 [ Info: threaded.jl [ Info: value_functions.jl [ Info: visualization.jl ====================================================================================== Information request received. A stacktrace will print followed by a 1.0 second profile. --trace-compile is enabled during profile collection. ====================================================================================== cmd: /opt/julia/bin/julia 876 running 0 of 1 signal (10): User defined signal 1 epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404 uv_run at /workspace/srcdir/libuv/src/unix/core.c:430 ijl_task_get_next at /source/src/scheduler.c:457 wait at ./task.jl:1246 wait_forever at ./task.jl:1168 jfptr_wait_forever_34528.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [inlined] start_task at /source/src/task.c:1281 unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== ┌ Warning: There were no samples collected in one or more groups. │ This may be due to idle threads, or you may need to run your │ program longer (perhaps by running it multiple times), │ or adjust the delay between samples with `Profile.init()`. └ @ Profile /opt/julia/share/julia/stdlib/v1.13/Profile/src/Profile.jl:1361 Overhead ╎ [+additional indent] Count File:Line Function ========================================================= Thread 1 (default) Task 0x0000705ae9148b50 Total snapshots: 760. Utilization: 0% ╎760 @Base/task.jl:1168 wait_forever() 759╎ 760 @Base/task.jl:1246 wait() ====================================================================================== Information request received. A stacktrace will print followed by a 1.0 second profile. --trace-compile is enabled during profile collection. ====================================================================================== cmd: /opt/julia/bin/julia 1 running 0 of 1 signal (10): User defined signal 1 epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404 uv_run at /workspace/srcdir/libuv/src/unix/core.c:430 ijl_task_get_next at /source/src/scheduler.c:457 wait at ./task.jl:1246 wait_forever at ./task.jl:1168 jfptr_wait_forever_34528.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [inlined] start_task at /source/src/task.c:1281 unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== ┌ Warning: There were no samples collected in one or more groups. │ This may be due to idle threads, or you may need to run your │ program longer (perhaps by running it multiple times), │ or adjust the delay between samples with `Profile.init()`. └ @ Profile /opt/julia/share/julia/stdlib/v1.13/Profile/src/Profile.jl:1361 Overhead ╎ [+additional indent] Count File:Line Function ========================================================= Thread 1 (default) Task 0x000077540c2f5d20 Total snapshots: 365. Utilization: 0% ╎365 @Base/task.jl:1168 wait_forever() 364╎ 365 @Base/task.jl:1246 wait() [876] signal 15: Terminated in expression starting at /home/pkgeval/.julia/packages/SDDP/ScjyB/test/visualization/visualization.jl:11 epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404 uv_run at /workspace/srcdir/libuv/src/unix/core.c:430 ijl_task_get_next at /source/src/scheduler.c:457 wait at ./task.jl:1246 wait_forever at ./task.jl:1168 jfptr_wait_forever_34528.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2275 [inlined] start_task at /source/src/task.c:1281 unknown function (ip: (nil)) at (unknown file) Allocations: 446922377 (Pool: 446918758; Big: 3619); GC: 91 PkgEval terminated after 2733.51s: test duration exceeded the time limit