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Current git-hash: bb3da5498a7ec1994891f33dac83f626ca69e85c (last fully tested stable version 6 commits ago [b9f1e470f24bdacf974e4cf9defd5b88ea683b32, 9405])
Using coverage run -p because $RUN_WITH_COVERAGE is set
[WARNING 07-20 19:39:37] ax.service.utils.with_db_settings_base: Ax currently requires a sqlalchemy version below 2.0. This will be addressed in a future release. Disabling SQL storage in Ax for now, if you would like to use SQL storage please install Ax with mysql extras via `pip install ax-platform[mysql]`.
Run-UUID: cb351e13-42c7-49cc-a0cb-ec6a87b1bd63
/home/runner/.omniax_venvs/Python_3.10.12/x86_64/lib/python3.10/site-packages/plyer/platforms/linux/notification.py:103: UserWarning: The Python dbus package is not installed.
Try installing it with your distribution's package manager, it is usually called python-dbus or python3-dbus, but you might have to try dbus-python instead, e.g. when using pip.
warnings.warn(msg)
/home/runner/.omniax_venvs/Python_3.10.12/x86_64/lib/python3.10/site-packages/plyer/platforms/linux/notification.py:107: UserWarning: notify-send not found.
warnings.warn("notify-send not found.")
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omniopt --partition=alpha --experiment_name=example_all_float --mem_gb=4 --time=60 --worker_timeout=5 --max_eval=2 --num_parallel_jobs=1 --gpus=0 --num_random_steps=1 --send_anonymized_usage_stats --run_program=LnRlc3RzL29wdGltaXphdGlvbl9leGFtcGxlX2FsbF9mbG9hdCAgLS14PSUoeCkgLS15PSUoeSkgLS16PSUoeikgLS1hPSUoYSkK --cpus_per_task=1 --nodes_per_job=1 --model=BOTORCH_MODULAR --run_mode=local --parameter x range -1000 1000 float --parameter y range -1000 1000 float --parameter z range -1000 1000 float --parameter a range -1000 1000 float --live_share --generate_all_jobs_at_once --follow --show_generate_time_table --disable_notifications
Run-folder: /home/runner/work/OmniOpt/OmniOpt/runs/example_all_float/0See https://imageseg.scads.de/omniax/share?user_id=runner&experiment_name=example_all_float&run_nr=163 for live-results.You have 4 CPUs available for the main process.No CUDA devices found.Generation strategy: SOBOL for 1 step and then BOTORCH_MODULAR for 1 step.
Run-Program: .tests/optimization_example_all_float --x=%(x) --y=%(y) --z=%(z) --a=%(a)
Experiment parameters
┏━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━┓
┃Name┃Type ┃Lower bound┃Upper bound┃Type ┃Log Scale?┃
┡━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━┩
│x │range│-1000 │1000 │float│No │
│y │range│-1000 │1000 │float│No │
│z │range│-1000 │1000 │float│No │
│a │range│-1000 │1000 │float│No │
└──────┴───────┴─────────────┴─────────────┴───────┴────────────┘
Result-Names
┏━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃Result-Name┃Min or max?┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│RESULT │ min│
└─────────────┴─────────────┘
Failed Jobs parameters
┏━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃param1┃param2┃param3┃error_description ┃
┡━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│value1│value2│value3│Some error occurred during execution (this is not a real error!).│
└────────┴────────┴────────┴───────────────────────────────────────────────────────────────────┘
Best RESULT, min (total: 2)
┏━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓
┃x ┃y ┃z ┃a ┃RESULT ┃
┡━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩
│990.4942195862532│982.2642803192139│-982.2851568460464│964.7992234677076│-38241140.4246366│
└───────────────────┴───────────────────┴────────────────────┴───────────────────┴───────────────────┘
Not printing sixel graphics in CI
Runtime Infos
┏━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃Number of evaluations┃Min time ┃Max time ┃Average time┃Median time┃
┡━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ 2 │ 6.00 sec │ 6.00 sec │ 6.00 sec │ 6.00 sec │
└───────────────────────┴───────────┴───────────┴──────────────┴─────────────┘
Model generation times
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃Iteration┃Seconds┃Jobs┃Time per job┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 0.024 │ 1 │ 0.024 │
│ 2 │ 0.303 │ 1 │ 0.303 │
├───────────┼─────────┼──────┼──────────────┤
│ Average │ 0.164 │ │ │
│ Median │ 0.164 │ │ │
│ Total │ 0.327 │ │ │
│ Max │ 0.303 │ │ │
│ Min │ 0.024 │ │ │
└───────────┴─────────┴──────┴──────────────┘
Job submission durations
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Batch┃Seconds┃Jobs┃Time per job┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 0.122 │ 1 │ 0.122 │
│ 2 │ 0.073 │ 1 │ 0.073 │
├─────────┼─────────┼──────┼──────────────┤
│ Average │ 0.097 │ │ │
│ Median │ 0.097 │ │ │
│ Total │ 0.195 │ │ │
│ Max │ 0.122 │ │ │
│ Min │ 0.073 │ │ │
└─────────┴─────────┴──────┴──────────────┘
╭───────────────────────────────────────────────────────────────OmniOpt2 Run Summary───────────────────────────────────────────────────────────────╮│││ ✅ Optimization complete!││││ 📊 Trials: 2 succeeded / 0 failed / 2 done / 2 submitted ││ ⏱️ Duration: 30s ││ 🏆 Best RESULT: -38241140.4246366 ││ 📁 Results: /home/runner/work/OmniOpt/OmniOpt/runs/example_all_float/0/results.csv││ 🤖 Model: BOTORCH_MODULAR │││╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
2026-07-20 19:39:39 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): SOBOL, Started OmniOpt2 run...
2026-07-20 19:39:40 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): SOBOL, getting new HP set (no sbatch)
2026-07-20 19:39:40 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): SOBOL, requested 1 jobs, got 1, 0.02 s/job
2026-07-20 19:39:40 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): SOBOL, eval #1/1 start
2026-07-20 19:39:40 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): SOBOL, starting new job
2026-07-20 19:39:40 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): SOBOL, started new job
2026-07-20 19:39:49 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): SOBOL, new result: RESULT: -7176273.515876
2026-07-20 19:39:50 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): SOBOL, best RESULT: -7176273.51587587, finishing jobs, finished 1 job
2026-07-20 19:39:50 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): BOTORCH_MODULAR, best RESULT: -7176273.51587587, getting new HP set (no sbatch)
2026-07-20 19:39:50 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): BOTORCH_MODULAR, best RESULT: -7176273.51587587, requested 1 jobs, got 1, 0.30 s/job
2026-07-20 19:39:50 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): BOTORCH_MODULAR, best RESULT: -7176273.51587587, eval #1/1 start
2026-07-20 19:39:50 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): BOTORCH_MODULAR, best RESULT: -7176273.51587587, starting new job
2026-07-20 19:39:50 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): BOTORCH_MODULAR, best RESULT: -7176273.51587587, started new job
2026-07-20 19:39:59 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): BOTORCH_MODULAR, best RESULT: -7176273.51587587, new result: RESULT: -38241140.424637
2026-07-20 19:40:01 (db044543-83dd-42c5-8e58-dd2ea13eb3ca): BOTORCH_MODULAR, best RESULT: -38241140.4246366, ▁█, finishing jobs, finished 1 job
Job submission durations
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Batch ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 0.122 │ 1 │ 0.122 │
│ 2 │ 0.073 │ 1 │ 0.073 │
├─────────┼─────────┼──────┼──────────────┤
│ Average │ 0.097 │ │ │
│ Median │ 0.097 │ │ │
│ Total │ 0.195 │ │ │
│ Max │ 0.122 │ │ │
│ Min │ 0.073 │ │ │
└─────────┴─────────┴──────┴──────────────┘
Model generation times
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Iteration ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 0.024 │ 1 │ 0.024 │
│ 2 │ 0.303 │ 1 │ 0.303 │
├───────────┼─────────┼──────┼──────────────┤
│ Average │ 0.164 │ │ │
│ Median │ 0.164 │ │ │
│ Total │ 0.327 │ │ │
│ Max │ 0.303 │ │ │
│ Min │ 0.024 │ │ │
└───────────┴─────────┴──────┴──────────────┘
! No notable correlations between parameters were found (threshold: |r| > 0.3).
Top-5 Best Results
Parameter Sensitivity Ranking
Parameters ranked by absolute Pearson correlation with each result. Stronger correlations (|r| ≥ 0.7) suggest the parameter has more influence on the outcome.