Package evaluation to test BlockTensorFactorization on Julia 1.14.0-DEV.1589 (2d9a3f8a61*) started at 2026-01-21T07:24:44.856 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 9.55s ################################################################################ # Installation # Installing BlockTensorFactorization... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [07b766a1] + BlockTensorFactorization v0.4.0 Updating `~/.julia/environments/v1.14/Manifest.toml` [07b766a1] + BlockTensorFactorization v0.4.0 [34da2185] + Compat v4.18.1 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.8.1 [864edb3b] + DataStructures v0.19.3 [e2d170a0] + DataValueInterfaces v1.0.0 [842dd82b] + InlineStrings v1.4.5 [41ab1584] + InvertedIndices v1.3.1 [82899510] + IteratorInterfaceExtensions v1.0.0 [b964fa9f] + LaTeXStrings v1.4.0 [e1d29d7a] + Missings v1.2.0 [bac558e1] + OrderedCollections v1.8.1 [2dfb63ee] + PooledArrays v1.4.3 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.1 [08abe8d2] + PrettyTables v3.1.2 [189a3867] + Reexport v1.2.2 [91c51154] + SentinelArrays v1.4.9 [a2af1166] + SortingAlgorithms v1.2.2 [10745b16] + Statistics v1.11.1 [892a3eda] + StringManipulation v0.4.2 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [d6f4376e] + Markdown v1.11.0 [de0858da] + Printf v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.0.0 [6462fe0b] + Sockets v1.11.0 [f489334b] + StyledStrings v1.13.0 [fa267f1f] + TOML v1.0.3 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [4536629a] + OpenBLAS_jll v0.3.29+0 [8e850b90] + libblastrampoline_jll v5.15.0+0 Installation completed after 4.06s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling packages... 10735.0 ms ✓ BlockTensorFactorization 1 dependency successfully precompiled in 11 seconds. 39 already precompiled. Precompilation completed after 28.6s ################################################################################ # Testing # Testing BlockTensorFactorization Status `/tmp/jl_vPS3A1/Project.toml` [07b766a1] BlockTensorFactorization v0.4.0 [10745b16] Statistics v1.11.1 [37e2e46d] LinearAlgebra v1.13.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_vPS3A1/Manifest.toml` [07b766a1] BlockTensorFactorization v0.4.0 [34da2185] Compat v4.18.1 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.1 [864edb3b] DataStructures v0.19.3 [e2d170a0] DataValueInterfaces v1.0.0 [842dd82b] InlineStrings v1.4.5 [41ab1584] InvertedIndices v1.3.1 [82899510] IteratorInterfaceExtensions v1.0.0 [b964fa9f] LaTeXStrings v1.4.0 [e1d29d7a] Missings v1.2.0 [bac558e1] OrderedCollections v1.8.1 [2dfb63ee] PooledArrays v1.4.3 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.1 [08abe8d2] PrettyTables v3.1.2 [189a3867] Reexport v1.2.2 [91c51154] SentinelArrays v1.4.9 [a2af1166] SortingAlgorithms v1.2.2 [10745b16] Statistics v1.11.1 [892a3eda] StringManipulation v0.4.2 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [de0858da] Printf v1.11.0 [3fa0cd96] REPL v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v1.0.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [f489334b] StyledStrings v1.13.0 [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 [4536629a] OpenBLAS_jll v0.3.29+0 [8e850b90] libblastrampoline_jll v5.15.0+0 Testing Running tests... ┌ Warning: Size of core (3, 2) is not compatible with the other factor's dimensions (2, 2) └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/decomposition.jl:235 ┌ Warning: `match_slices!` may not have found the best ordering; using O(n²) greedy approach. └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factormatching.jl:32 ┌ Warning: maximum iteration 2 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 [ Info: converged based on GradientNorm less than Inf [ Info: converged based on GradientNorm less than Inf [ Info: converged based on GradientNorm less than Inf [ Info: converged based on GradientNorm less than Inf [ Info: converged based on GradientNorm less than Inf [ Info: converged based on GradientNorm less than Inf ┌ Warning: maximum iteration 2 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 ┌ Warning: maximum iteration 2 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 ┌ Warning: maximum iteration 2 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 ┌ Warning: maximum iteration 2 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 ┌ Warning: maximum iteration 2 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 [ Info: converged based on RelativeError less than 0.05 [ Info: converged based on RelativeError less than 0.01 ┌ Warning: Initial decomposition does not satisfy the following constraints: AbstractUpdate[Projection(1, ProjectedNormalization(l2norm, l2project!, eachcol)), Projection(2, ProjectedNormalization(l2norm, l2project!, eachcol))]. This may be ok if later iterations satisfy the constraints └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:342 [ Info: converged based on RelativeError less than 0.045 [ Info: converged based on RelativeError less than 0.01 ┌ Warning: Initial decomposition does not satisfy the following constraints: AbstractUpdate[BlockedUpdate([SafeNNProjection(1, ProjectedNormalization(l1norm, projsplx!, eachcol)), Rescale{Missing}(1, ScaledNormalization{Int64}(l1norm, eachcol, 1), missing)]), Projection(2, ProjectedNormalization(isnonnegative_sumtoone, projsplx!, eachcol))]. This may be ok if later iterations satisfy the constraints └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:342 [ Info: converged based on RelativeError less than 0.01 [ Info: converged based on RelativeError less than 0.045 [ Info: Factorizing at scale 16... [ Info: converged based on GradientNorm less than 1 [ Info: Factorizing at scale 8... [ Info: converged based on GradientNorm less than 1 [ Info: Factorizing at scale 4... [ Info: converged based on GradientNorm less than 1 [ Info: Factorizing at scale 2... [ Info: converged based on GradientNorm less than 1 [ Info: Factorizing at scale 1... [ Info: converged based on GradientNorm less than 1 ┌ Warning: Scaling ProjectedNormalization constraints is not implemented (YET!) Leaving the constraint ProjectedNormalization(l1norm, projsplx!, each1slice) alone. └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/multiscale.jl:440 [ Info: Factorizing at scale 32... [ Info: converged based on GradientNNCone less than 1.0e-5 ┌ Warning: Scaling ProjectedNormalization constraints is not implemented (YET!) Leaving the constraint ProjectedNormalization(l1norm, projsplx!, each1slice) alone. └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/multiscale.jl:440 [ Info: Factorizing at scale 16... [ Info: converged based on GradientNNCone less than 1.0e-5 ┌ Warning: Scaling ProjectedNormalization constraints is not implemented (YET!) Leaving the constraint ProjectedNormalization(l1norm, projsplx!, each1slice) alone. └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/multiscale.jl:440 [ Info: Factorizing at scale 8... [ Info: converged based on GradientNNCone less than 1.0e-5 ┌ Warning: Scaling ProjectedNormalization constraints is not implemented (YET!) Leaving the constraint ProjectedNormalization(l1norm, projsplx!, each1slice) alone. └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/multiscale.jl:440 [ Info: Factorizing at scale 4... ┌ Warning: maximum iteration 200 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 ┌ Warning: Scaling ProjectedNormalization constraints is not implemented (YET!) Leaving the constraint ProjectedNormalization(l1norm, projsplx!, each1slice) alone. └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/multiscale.jl:440 [ Info: Factorizing at scale 2... ┌ Warning: maximum iteration 200 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 ┌ Warning: Scaling ProjectedNormalization constraints is not implemented (YET!) Leaving the constraint ProjectedNormalization(l1norm, projsplx!, each1slice) alone. └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/multiscale.jl:440 [ Info: Factorizing at scale 1... ┌ Warning: maximum iteration 200 reached, without convergence └ @ BlockTensorFactorization.Core ~/.julia/packages/BlockTensorFactorization/QAu7d/src/Core/factorize.jl:451 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.6331343180940479 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.35254625206418444 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.0022381061510656623 [ Info: Trying rank=4... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.003622814086714928 [ Info: Trying rank=5... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.004962325257994309 [ Info: Trying rank=6... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.005624874443211515 [ Info: Trying rank=7... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.002853943709194746 [ Info: Trying rank=8... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.0030732062933626217 [ Info: Trying rank=9... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.004367355818602448 [ Info: Trying rank=10... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.004357712597186477 [ Info: Optimal rank found: 3 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.633132741798938 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.35252910181166897 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.002648881868613177 [ Info: Trying rank=4... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.01217370408747805 [ Info: Trying rank=5... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.00444797922298721 [ Info: Trying rank=6... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.005432935696952091 [ Info: Trying rank=7... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.0044854811698997275 [ Info: Trying rank=8... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.0058821746580987435 [ Info: Trying rank=9... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.00471514320980023 [ Info: Trying rank=10... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.004257223637658726 [ Info: Optimal rank found: 3 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.6331324914484306 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.3525524376875428 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.004618041106409338 [ Info: Trying rank=4... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.0032758490412955225 [ Info: Trying rank=5... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.003022036898108048 [ Info: Trying rank=6... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.005945105473302159 [ Info: Trying rank=7... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.007695724697455688 [ Info: Trying rank=8... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.004859322710894958 [ Info: Trying rank=9... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.006294122013195923 [ Info: Trying rank=10... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.01308621268807388 [ Info: Optimal rank found: 3 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.6331357477511032 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.35251964745156067 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.007061250423849124 [ Info: Trying rank=4... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.005368010376439088 [ Info: Trying rank=5... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.006227205120803683 [ Info: Trying rank=6... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.008760175593717062 [ Info: Trying rank=7... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.012758524476589787 [ Info: Trying rank=8... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.008445062081942033 [ Info: Trying rank=9... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.005580186039813116 [ Info: Trying rank=10... [ Info: converged based on GradientNorm less than 1 [ Info: Final relative error = 0.0053617795728376424 [ Info: Optimal rank found: 3 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.7583607661805988 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.4921740166724802 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.2978502937322606 [ Info: Trying rank=4... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 2.437946814507523e-5 [ Info: Trying rank=5... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.0002470329796052974 [ Info: Optimal rank found: 4 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.8088293421656647 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.4921740170672646 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.3953786202972382 [ Info: Optimal rank found: 2 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.7583607661797777 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.4921740167634538 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.39537862111130184 [ Info: Optimal rank found: 2 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.7583607661845612 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.4921740166459596 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.2978502944177712 [ Info: Trying rank=4... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 5.1876487023326123e-5 [ Info: Trying rank=5... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.00011092919223089123 [ Info: Optimal rank found: 4 [ Info: Trying rank=1... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.7583607661769051 [ Info: Trying rank=2... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.4921740167113818 [ Info: Trying rank=3... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 0.29785029462332535 [ Info: Trying rank=4... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 3.315473490660319e-5 [ Info: Trying rank=5... [ Info: converged based on GradientNorm less than 0.01 [ Info: Final relative error = 3.6628712684229484e-5 [ Info: Optimal rank found: 4 Test Summary: | Pass Broken Total Time BlockTensorFactorization | 199 4 203 4m46.5s Utils | 39 39 18.0s Products | 6 6 12.4s Constraints | 41 2 43 37.9s SuperDiagonal | 14 14 2.4s AbstractDecomposition | 41 41 17.8s Matching | 6 6 14.9s BlockUpdates | 13 13 14.1s BlockUpdatedDecomposition | 15 2 17 1m54.0s MultiScale | 14 14 30.6s RankDetection | 10 10 24.3s Testing BlockTensorFactorization tests passed Testing completed after 304.73s PkgEval succeeded after 364.24s