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Current git-hash: e5400cf5355eafc83fee2560bf8d06d5d8a990a6 (last fully tested stable version 1 commit ago [40e86984857e047bcfb600b452b0692331ba16d4, 9396])
Using coverage run -p because $RUN_WITH_COVERAGE is set
[INFO 07-20 07:27:55] ax.storage.sqa_store.with_db_settings_base: Ax SQL storage initialized with SQLAlchemy 2.0.51
Run-UUID: af4230f6-d819-494e-bd47-35de82e98d82
/home/runner/.omniax_venvs/Python_3.12.3/x86_64/lib/python3.12/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_3.12.3/x86_64/lib/python3.12/site-packages/plyer/platforms/linux/notification.py:107: UserWarning: notify-send not found.
warnings.warn("notify-send not found.")
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omniopt --live_share --send_anonymized_usage_stats --partition alpha --experiment_name=adding_old_jobs_to_new_jobs --mem_gb=4 --time=60 --worker_timeout=5 --max_eval 2 --num_parallel_jobs 1 --gpus=0 --run_program Li8udGVzdHMvb3B0aW1pemF0aW9uX2V4YW1wbGUgLS1pbnRfcGFyYW09JyUoaW50X3BhcmFtKScgLS1mbG9hdF9wYXJhbT0nJShmbG9hdF9wYXJhbSknIC0tY2hvaWNlX3BhcmFtPSclKGNob2ljZV9wYXJhbSknICAtLWludF9wYXJhbV90d289JyUoaW50X3BhcmFtX3R3byknIC0tbnJfcmVzdWx0cz0x --parameter int_param range -100 10 int --parameter float_param range -100 10 float --parameter choice_param choice 1,2,4,8,16,hallo --parameter int_param_two range -100 10 int --follow --num_random_steps 1 --model BOTORCH_MODULAR --auto_exclude_defective_hosts --load_data_from_existing_jobs runs/adding_old_jobs_to_new_jobs//0 runs/adding_old_jobs_to_new_jobs//1
Run-folder: /home/runner/work/OmniOpt/OmniOpt/runs/adding_old_jobs_to_new_jobs/2See https://imageseg.scads.de/omniax/share?user_id=runner&experiment_name=adding_old_jobs_to_new_jobs&run_nr=317 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 --int_param='%(int_param)' --float_param='%(float_param)' --choice_param='%(choice_param)' --int_param_two='%(int_param_two)' --nr_results=1
Experiment parameters
┏━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━┓
┃Name ┃Type ┃Lower bound┃Upper bound┃Values ┃Type ┃Log Scale?┃
┡━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━┩
│int_param │range │-100 │10 ││int │No │
│float_param │range │-100 │10 ││float│No │
│choice_param │choice│││1, 2, 4, 8, 16, hallo│││
│int_param_two│range │-100 │10 ││int │No │
└───────────────┴────────┴─────────────┴─────────────┴───────────────────────┴───────┴────────────┘
Result-Names
┏━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃Result-Name┃Min or max?┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│RESULT │ min│
└─────────────┴─────────────┘
Inserted 2 jobs from runs/adding_old_jobs_to_new_jobs/0/results.csvInserted 2 jobs from runs/adding_old_jobs_to_new_jobs/1/results.csvFailed 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 + inserted jobs: 4)
┏━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃OO_Info_int_param┃OO_Info_int_param_two┃OO_Info_float_param┃OO_Info_choice_param┃int_param┃float_param┃choice_param┃int_param_two┃RESULT ┃
┡━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│-100.0 │10.0 │-100.0 │8.0 │-100 │-100.0 │8 │10 │-221418.92│
└───────────────────┴───────────────────────┴─────────────────────┴──────────────────────┴───────────┴─────────────┴──────────────┴───────────────┴────────────┘
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 │
└───────────────────────┴───────────┴───────────┴──────────────┴─────────────┘
╭────────────────────────────────────────────────────────────────────────────────────────OmniOpt2 Run Summary────────────────────────────────────────────────────────────────────────────────────────╮│││ ✅ Optimization complete!││││ 📊 Trials: 2 succeeded / 0 failed / 6 done / 2 submitted ││ ⏱️ Duration: 46s ││ 🏆 Best RESULT: -221418.92 ││ 📁 Results: /home/runner/work/OmniOpt/OmniOpt/runs/adding_old_jobs_to_new_jobs/2/results.csv││ 🤖 Model: BOTORCH_MODULAR │││╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
2026-07-20 07:28:00 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): SOBOL, best RESULT: -154879.211841381, ▁█▅▃, Started OmniOpt2 run...
2026-07-20 07:28:03 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -154879.211841381, ▁█▅▃, getting new HP set (no sbatch)
2026-07-20 07:28:03 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -154879.211841381, ▁█▅▃, requested 1 jobs, got 1, 3.30 s/job
2026-07-20 07:28:03 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -154879.211841381, ▁█▅▃, eval #1/1 start
2026-07-20 07:28:03 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -154879.211841381, ▁█▅▃, starting new job
2026-07-20 07:28:04 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -154879.211841381, ▁█▅▃, started new job
2026-07-20 07:28:13 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -154879.211841381, ▁█▅▃, new result: RESULT: -221418.920000
2026-07-20 07:28:15 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -221418.92, ▁▅▃▂█, finishing jobs, finished 1 job
2026-07-20 07:28:17 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -221418.92, ▁▅▃▂█, getting new HP set (no sbatch)
2026-07-20 07:28:17 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -221418.92, ▁▅▃▂█, requested 1 jobs, got 1, 2.05 s/job
2026-07-20 07:28:17 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -221418.92, ▁▅▃▂█, eval #1/1 start
2026-07-20 07:28:17 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -221418.92, ▁▅▃▂█, starting new job
2026-07-20 07:28:18 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -221418.92, ▁▅▃▂█, started new job
2026-07-20 07:28:27 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -221418.92, ▁▅▃▂█, new result: RESULT: -143073.854329
2026-07-20 07:28:29 (12b528d7-f480-4bbf-8541-d47a1cef1bf4): BOTORCH_MODULAR, best RESULT: -221418.92, ▁▅▃▂█▄, finishing jobs, finished 1 job
Job submission durations
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Batch ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 0.298 │ 1 │ 0.298 │
│ 2 │ 0.109 │ 1 │ 0.109 │
├─────────┼─────────┼──────┼──────────────┤
│ Average │ 0.204 │ │ │
│ Median │ 0.204 │ │ │
│ Total │ 0.407 │ │ │
│ Max │ 0.298 │ │ │
│ Min │ 0.109 │ │ │
└─────────┴─────────┴──────┴──────────────┘
Model generation times
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Iteration ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 3.302 │ 1 │ 3.302 │
│ 2 │ 2.054 │ 1 │ 2.054 │
├───────────┼─────────┼──────┼──────────────┤
│ Average │ 2.678 │ │ │
│ Median │ 2.678 │ │ │
│ Total │ 5.355 │ │ │
│ Max │ 3.302 │ │ │
│ Min │ 2.054 │ │ │
└───────────┴─────────┴──────┴──────────────┘
Parameters ranked by absolute Pearson correlation with each result. Stronger correlations (|r| ≥ 0.7) suggest the parameter has more influence on the outcome.