trial_index,submit_time,queue_time,worker_generator_uuid,start_time,end_time,run_time,program_string,exit_code,signal,hostname,OO_Info_int_param,OO_Info_int_param_two,OO_Info_float_param,OO_Info_choice_param,arm_name,trial_status,generation_node,RESULT,int_param,float_param,int_param_two,choice_param
0,,,,,,,,,,,,,,,0_0,COMPLETED,SOBOL,-86015.35484702530084177851676940918,0,-79.0043063461780548095703125,-34,1
1,,,,,,,,,,,,,,,1_0,COMPLETED,BOTORCH_MODULAR,-122855.93461916600062977522611618042,-97,-35.861491185670139714147808263078,10,16
2,1760701474,2,9d4fc455-5268-4b41-bc70-0595dba92890,1760701476,1760701482,6,./.tests/optimization_example --int_param='-100' --float_param='10' --choice_param='16' --int_param_two='-46' --nr_results=1,0,,4bd82be51342,-100,-46,10,16,2_0,COMPLETED,BOTORCH_MODULAR,-137780.519999999989522621035575866699,-100,10,-46,16
3,1760701487,1,9d4fc455-5268-4b41-bc70-0595dba92890,1760701488,1760701494,6,./.tests/optimization_example --int_param='-62' --float_param='10' --choice_param='16' --int_param_two='-100' --nr_results=1,0,,4bd82be51342,-62,-100,10,16,3_0,COMPLETED,BOTORCH_MODULAR,-156001.320000000006984919309616088867,-62,10,-100,16
========================================================================
Current git-hash: 62196d07a39ec32920cf32a26d8f00f4ea9f36fd (last fully tested stable version 6 commits ago [208aac92c9d373d0a7ca51bdae9ece179ef45cd2, 8673])
Using coverage run -p because $RUN_WITH_COVERAGE is set
โ Importing logging...
โ Importing warnings...
โ Importing argparse...
โ Importing datetime...
โ Importing dataclass...
โ Importing socket...
โ Importing stat...
โ Importing pwd...
โ Importing base64...
โ Importing json...
โ Importing yaml...
โ Importing toml...
โ Importing csv...
โ Importing ast...
โ Importing rich.table...
โ Importing rich print...
โ Importing rich.pretty...
โ Importing pformat...
โ Importing rich.prompt...
โ Importing types.FunctionType...
โ Importing typing...
โ Importing ThreadPoolExecutor...
โ Importing submitit.LocalExecutor...
โ Importing submitit.Job...
โ Importing importlib.util...
โ Importing platform...
โ Importing inspect frame info...
โ Importing pathlib.Path...
โ Importing uuid...
โ Importing cowsay...
โ Importing shutil...
โ Importing itertools.combinations...
โ Importing os.listdir...
โ Importing os.path...
โ Importing PIL.Image...
โ Importing sixel...
โ Importing subprocess...
โ Importing tqdm...
โ Importing beartype...
โ Importing statistics...
โ Trying to import pyfiglet...
โ Importing helpers...
โ Parsing arguments...
โ ธ Importing torch...
โ Importing numpy...
[WARNING 10-17 11:44:19] 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]`.
โ ฆ Importing ax...
โ Importing ax.core.generator_run...
โ Importing Cont_X_trans and Y_trans from ax.adapter.registry...
โ Importing ax.core.arm...
โ Importing ax.core.objective...
โ Importing ax.core.Metric...
โ Importing ax.exceptions.core...
โ Importing ax.exceptions.generation_strategy...
โ Importing CORE_DECODER_REGISTRY...
โ Trying ax.generation_strategy.generation_node...
โ Importing GenerationStep, GenerationStrategy from generation_strategy...
โ Importing GenerationNode from generation_node...
โ Importing ExternalGenerationNode...
โ Importing MaxTrials...
โ Importing GeneratorSpec...
โ Importing Models from ax.generation_strategy.registry...
โ Importing get_pending_observation_features...
โ Importing load_experiment...
โ Importing save_experiment...
โ Importing save_experiment_to_db...
โ Importing TrialStatus...
โ Importing Data...
โ Importing Experiment...
โ Importing parameter types...
โ Importing TParameterization...
โ Importing pandas...
โ Importing AxClient and ObjectiveProperties...
โ Importing RandomForestRegressor...
โ Importing botorch...
โ Importing submitit...
โ Importing ax logger...
โ Importing SQL-Storage-Stuff...
Using old run's --time: 60
Using old run's --gpus: 0
Run-UUID: 4fd4f753-356e-46f9-a1f2-759ac916109f
_________________________________________________
/ \
| OmniOpt2 - More focused than a cat watching a las |
| er pointer. |
\ /
=================================================
\
\
\
|\_/|,,_____,~~`
(.".)~~ )`~}}
\o/\ /---~\\ ~}}
_// _// ~}
โ Writing worker creation log...
omniopt --continue runs/__main__tests__BOTORCH_MODULAR___nogridsearch/0 --num_parallel_jobs 1 --worker_timeout 10 --follow --gpus=0 --mem_gb=4 --num_random_steps=1 --max_eval=2 --send_anonymized_usage_stats --generate_all_jobs_at_once --live_share
โ Disabling logging...
โ Setting run folder...
โ Creating folder /var/opt/omniopt/runs/__main__tests__BOTORCH_MODULAR___nogridsearch/1...
โ Writing revert_to_random_when_seemingly_exhausted file ...
โ Writing username state file...
โ Writing result names file...
โ Writing result min/max file...
โ Saving state files...
Run-folder: /var/opt/omniopt/runs/__main__tests__BOTORCH_MODULAR___nogridsearch/1
Continuation from runs/__main__tests__BOTORCH_MODULAR___nogridsearch/0
โ Writing live_share file if it is present...
โ Writing job_start_time file...
โ Writing git information
โ Checking max_eval...
โ Calculating number of steps...
โ Adding excluded nodes...
โ Setting global generation strategy
โ Initializing ax_client...
โ Setting orchestrator...
Warning: The disk space is almost full. This may lead to error messages and you not being able to push jobs. If you want to see results anyway, check https://imageseg.scads.de/omniax/tutorials?tutorial=oo_share#run-locally-in-docker on how to install it locally (with docker). If you run on HPC, you may want to install this into a Research Cloud at the TU Dresden.
See https://imageseg.scads.de/omniax/share?user_id=defaultuser&experiment_name=__main__tests__BOTORCH_MODULAR___nogridsearch&run_nr=339 for live-results.
You have 4 CPUs available for the main process. No CUDA devices found.
Generation strategy: BOTORCH_MODULAR for 5 steps.
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
โโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโณโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโณโโโโโโโโโโโโโ
โ Name โ Type โ Lower bound โ Upper bound โ Values โ Type โ Log Scale? โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ int_param โ rangeparameter โ -100 โ 10 โ โ int โ No โ
โ float_param โ rangeparameter โ -100 โ 10 โ โ float โ No โ
โ choice_param โ choiceparameter โ โ โ 1, 2, 4, 8, 16, hallo โ โ โ
โ int_param_two โ rangeparameter โ -100 โ 10 โ โ int โ No โ
โโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโดโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโดโโโโโโโโโโโโโ
Result-Names
โโโโโโโโโโโโโโโณโโโโโโโโโโโโโโ
โ Result-Name โ Min or max? โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ RESULT โ min โ
โโโโโโโโโโโโโโโดโโโโโโโโโโโโโโ
โ Write files and show overview
BOTORCH_MODULAR, best RESULT: -156001.32, finishing jobs, finished 1 job : 100%|โโโโโโโโโโ| 4/4 [00:26<00:00, 6.52s/it]
Best RESULT, min (total: 2 + inserted jobs: 2)
โโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโณโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโณโโโโโโโโโโโโโ
โ OO_Info_int_param โ OO_Info_int_param_two โ OO_Info_float_param โ OO_Info_choice_param โ int_param โ float_param โ int_param_two โ choice_param โ RESULT โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ -62.0 โ -100.0 โ 10.0 โ 16.0 โ -62 โ 10.0 โ -100 โ 16 โ -156001.32 โ
โโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโดโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโดโโโโโโโโโโโโโ
Runtime Infos
โโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโณโโโโโโโโโโโโณโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโ
โ Number of evaluations โ Min time โ Max time โ Average time โ Median time โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ 2 โ 6.00 sec โ 6.00 sec โ 6.00 sec โ 6.00 sec โ
โโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโดโโโโโโโโโโโโดโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโ
2025-10-17 11:44:33 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, Started OmniOpt2 run...
2025-10-17 11:44:34 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, getting new HP set (no sbatch)
2025-10-17 11:44:34 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, requested 1 jobs, got 1, 1.19 s/job
2025-10-17 11:44:34 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, eval #1/1 start
2025-10-17 11:44:34 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, starting new job
2025-10-17 11:44:34 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, started new job
2025-10-17 11:44:43 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, new result: -137780.52
2025-10-17 11:44:45 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, best RESULT: -137780.52, finishing jobs, finished 1 job
2025-10-17 11:44:46 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, best RESULT: -137780.52, getting new HP set (no sbatch)
2025-10-17 11:44:47 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, best RESULT: -137780.52, requested 1 jobs, got 1, 1.01 s/job
2025-10-17 11:44:47 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, best RESULT: -137780.52, eval #1/1 start
2025-10-17 11:44:47 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, best RESULT: -137780.52, starting new job
2025-10-17 11:44:47 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, best RESULT: -137780.52, started new job
2025-10-17 11:44:56 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, best RESULT: -137780.52, new result: -156001.32
2025-10-17 11:44:59 (9d4fc455-5268-4b41-bc70-0595dba92890): BOTORCH_MODULAR, best RESULT: -156001.32, finishing jobs, finished 1 job
timestamp,ram_usage_mb,cpu_usage_percent
1760701473,809.453125,9.4