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Current git-hash: b0da098366dff80d0584e1ac15b9fb8c1fc98b10 (last fully tested stable version 10 commits ago [fd169efde52c08105aa8078cc890532aea608c04, 8509])
Using coverage run -p because $RUN_WITH_COVERAGE is set
[WARNING 09-10 16:02:43] 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: 334dc087-efc4-40b8-9dc0-cb5a6dc343d9
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| OmniOpt2 - Turning knobs since day one! |
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omniopt --partition=alpha --experiment_name=randomforest --mem_gb=1 --time=60 --worker_timeout=60 --max_eval=2 --num_parallel_jobs=1 --gpus=0 --num_random_steps=1 --follow --live_share --send_anonymized_usage_stats --result_names RESULT=min --run_program=ZWNobyAiUkVTVUxUOiAlYSUoeCklKHkpJXoi --cpus_per_task=1 --nodes_per_job=1 --generate_all_jobs_at_once --revert_to_random_when_seemingly_exhausted --model=RANDOMFOREST --run_mode=local --occ_type=euclid --main_process_gb=8 --max_nr_of_zero_results=1 --slurm_signal_delay_s=0 --n_estimators_randomforest=100 --parameter x fixed 123 --parameter y range 5431 1234 int false --parameter z range 0 1 float false --parameter a choice 1,2,3
Run-folder: /home/runner/work/OmniOpt/OmniOpt/runs/randomforest/0Lower bound (5431.0) was larger than upper bound (1234.0) for parameter 'y'. Switched them.See https://imageseg.scads.de/omniax/share?user_id=runner&experiment_name=randomforest&run_nr=21 for live-results.You have 4 CPUs available for the main process.No CUDA devices found.Generation strategy: SOBOL for 1 step and then RANDOMFOREST for 1 step.
Run-Program: echo "RESULT: %a%(x)%(y)%z"
Experiment parameters
โโโโโโโโณโโโโโโโโโณโโโโโโโโโโโโโโณโโโโโโโโโโโโโโณโโโโโโโโโโณโโโโโโโโณโโโโโโโโโโโโโ
โNameโType โLower boundโUpper boundโValues โType โLog Scale?โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โx โfixed โโโ123 โโโ
โy โrange โ1234 โ5431 โโint โNo โ
โz โrange โ0 โ1 โโfloatโNo โ
โa โchoiceโโโ1, 2, 3โโโ
โโโโโโโโดโโโโโโโโโดโโโโโโโโโโโโโโดโโโโโโโโโโโโโโดโโโโโโโโโโดโโโโโโโโดโโโโโโโโโโโโโ
Result-Names
โโโโโโโโโโโโโโโณโโโโโโโโโโโโโโ
โResult-NameโMin or max?โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โRESULT โ minโ
โโโโโโโโโโโโโโโดโโโโโโโโโโโโโโ
Failed Jobs parameters
โโโโโโโโโโณโโโโโโโโโณโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โparam1โparam2โparam3โerror_description โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โvalue1โvalue2โvalue3โSome error occurred during execution (this is not a real error!).โ
โโโโโโโโโโดโโโโโโโโโดโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Best RESULT, min (total: 2)
โโโโโโโโณโโโโโโโโโโโโโโโโโโโโโณโโโโณโโโโโโณโโโโโโโโโโโโโโโโโโโโ
โy โz โaโx โRESULT โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ5191โ0.8660082037903676โ2โ123โ212351910.8660082โ
โโโโโโโโดโโโโโโโโโโโโโโโโโโโโโดโโโโดโโโโโโดโโโโโโโโโโโโโโโโโโโโ
Not printing sixel graphics in CI
Runtime Infos
โโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโณโโโโโโโโโโโโณโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโ
โNumber of evaluationsโMin time โMax time โAverage timeโMedian timeโ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ 2 โ 6.00 sec โ 6.00 sec โ 6.00 sec โ 6.00 sec โ
โโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโดโโโโโโโโโโโโดโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโ
2025-09-10 16:02:45 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, Started OmniOpt2 run...
2025-09-10 16:02:45 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, getting new HP set (no sbatch)
2025-09-10 16:02:45 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, requested 1 jobs, got 1, 0.02 s/job
2025-09-10 16:02:45 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, eval #1/1 start
2025-09-10 16:02:45 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, starting new job
2025-09-10 16:02:46 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, started new job
2025-09-10 16:02:55 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, new result: 312327280.0954156
2025-09-10 16:02:56 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, best RESULT: 312327280.0954156, finishing jobs, finished 1 job
2025-09-10 16:02:56 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, best RESULT: 312327280.0954156, getting new HP set (no sbatch)
2025-09-10 16:02:56 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, best RESULT: 312327280.0954156, requested 1 jobs, got 1, 0.19 s/job
2025-09-10 16:02:56 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, best RESULT: 312327280.0954156, eval #1/1 start
2025-09-10 16:02:56 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, best RESULT: 312327280.0954156, starting new job
2025-09-10 16:02:56 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, best RESULT: 312327280.0954156, started new job
2025-09-10 16:03:05 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, best RESULT: 312327280.0954156, new result: 212351910.8660082
2025-09-10 16:03:06 (dd9e6772-abe6-45fd-a440-d99b1b6309b2): SOBOL, best RESULT: 212351910.8660082, finishing jobs, finished 1 job
Job submission durations
โโโโโโโโโโโณโโโโโโโโโโณโโโโโโโณโโโโโโโโโโโโโโโ
โ Batch โ Seconds โ Jobs โ Time per job โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ 1 โ 0.215 โ 1 โ 0.215 โ
โ 2 โ 0.081 โ 1 โ 0.081 โ
โโโโโโโโโโโผโโโโโโโโโโผโโโโโโโผโโโโโโโโโโโโโโโค
โ Average โ 0.148 โ โ โ
โ Median โ 0.148 โ โ โ
โ Total โ 0.296 โ โ โ
โ Max โ 0.215 โ โ โ
โ Min โ 0.081 โ โ โ
โโโโโโโโโโโดโโโโโโโโโโดโโโโโโโดโโโโโโโโโโโโโโโ
Model generation times
โโโโโโโโโโโโโณโโโโโโโโโโณโโโโโโโณโโโโโโโโโโโโโโโ
โ Iteration โ Seconds โ Jobs โ Time per job โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ 1 โ 0.019 โ 1 โ 0.019 โ
โ 2 โ 0.191 โ 1 โ 0.191 โ
โโโโโโโโโโโโโผโโโโโโโโโโผโโโโโโโผโโโโโโโโโโโโโโโค
โ Average โ 0.105 โ โ โ
โ Median โ 0.105 โ โ โ
โ Total โ 0.210 โ โ โ
โ Max โ 0.191 โ โ โ
โ Min โ 0.019 โ โ โ
โโโโโโโโโโโโโดโโโโโโโโโโดโโโโโโโดโโโโโโโโโโโโโโโ
This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
How It Works
The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
Positive correlation: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).
Negative correlation: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).
Zero correlation: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).
Color Scale: Yellow to Purple (Viridis)
The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
Yellow (brightest): A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.
Green: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.
Blue: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.
Purple (darkest): A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.
What the Heatmap Shows
In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
/home/runner/.omniax_venvs/Python_3.12.3/x86_64/lib/python3.12/site-packages/submitit/core/plugins.py:24: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
import pkg_resources
submitit INFO (2025-09-10 16:02:46,285) - Starting with JobEnvironment(job_id=67211, hostname=runnervmf4ws1, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-09-10 16:02:46,285) - Loading pickle: /home/runner/work/OmniOpt/OmniOpt/runs/randomforest/0/single_runs/67211/67211_submitted.pkl
Parameters: {"y": 2728, "z": 0.09541559219360352, "a": 3, "x": 123}
Debug-Infos:
echo "RESULT: 312327280.09541559219360351562"
stdout:
RESULT: 312327280.09541559219360351562
stderr was empty
Result: {'RESULT': 312327280.0954156}
Final-results: {'RESULT': 312327280.0954156}
EXIT_CODE: 0
submitit INFO (2025-09-10 16:02:53,790) - Job completed successfully
submitit INFO (2025-09-10 16:02:53,790) - Exiting after successful completion