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,-119473.007072253996739163994789123535,-59,-54.2777252197265625,-61,1
1,,,,,,,,,,,,,,,1_0,COMPLETED,BOTORCH_MODULAR,-24066.054045857399614760652184486389,8,0.314553960855270930974114662604,-44,4
2,,,,,,,,,,,,,,,2_0,COMPLETED,BOTORCH_MODULAR,-324047.719999999972060322761535644531,-100,-100,-97,1
3,,,,,,,,,,,,,,,3_0,COMPLETED,BOTORCH_MODULAR,-252983.720000000001164153218269348145,-100,-100,-52,1
4,1761908606,2,f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b,1761908608,1761908614,6,./.tests/optimization_example --int_param='-100' --float_param='-954.74270541306691484351' --choice_param='1' --int_param_two='-100' --nr_results=1,0,,4d5782e9d4bb,-100,-100,-954.742705413066914843511767685413,1,4_0,COMPLETED,BOTORCH_MODULAR,-9431035.92593592964112758636474609375,-100,-954.742705413066914843511767685413,-100,1
5,1761908622,1,f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b,1761908623,1761908629,6,./.tests/optimization_example --int_param='-100' --float_param='-1000' --choice_param='4' --int_param_two='-100' --nr_results=1,0,,4d5782e9d4bb,-100,-100,-1000,4,5_0,COMPLETED,BOTORCH_MODULAR,-10320107.72000000067055225372314453125,-100,-1000,-100,4
========================================================================
Current git-hash: 31d2e0738b1d3d941fb816614ce321579eec5e2a (last fully tested stable version 3 commits ago [de83f485f1baba61b8d986138485a09fbde31698, 8946])
Using coverage run -p because $RUN_WITH_COVERAGE is set
⠋ Importing logging...
⠋ Importing warnings...
⠋ Importing argparse...
⠋ Importing datetime...
⠋ Importing dataclass...
⠋ Importing socket...
⠋ Importing stat...
⠋ Importing pwd...
⠋ Importing base64...
⠋ Importing json...
⠋ Importing yaml...
⠋ Importing toml...
⠋ Importing csv...
⠋ Importing ast...
⠋ Importing rich.table...
⠋ Importing rich print...
⠋ Importing rich.pretty...
⠋ Importing pformat...
⠋ Importing rich.prompt...
⠋ Importing types.FunctionType...
⠋ Importing typing...
⠋ Importing ThreadPoolExecutor...
⠋ Importing submitit.LocalExecutor...
⠋ Importing submitit.Job...
⠋ Importing importlib.util...
⠋ Importing platform...
⠋ Importing inspect frame info...
⠋ Importing pathlib.Path...
⠋ Importing uuid...
⠋ Importing cowsay...
⠋ Importing shutil...
⠋ Importing itertools.combinations...
⠋ Importing os.listdir...
⠋ Importing os.path...
⠋ Importing PIL.Image...
⠋ Importing sixel...
⠋ Importing subprocess...
⠋ Importing tqdm...
⠋ Importing beartype...
⠋ Importing statistics...
⠋ Trying to import pyfiglet...
⠋ Importing helpers...
⠋ Importing pareto...
⠋ Parsing arguments...
⠸ Importing torch...
⠋ Importing numpy...
[WARNING 10-31 11:03:10] 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]`.
⠦ Importing ax...
⠋ Importing ax.core.generator_run...
⠋ Importing Cont_X_trans and Y_trans from ax.adapter.registry...
⠋ Importing ax.core.arm...
⠋ Importing ax.core.objective...
⠋ Importing ax.core.Metric...
⠋ Importing ax.exceptions.core...
⠋ Importing ax.exceptions.generation_strategy...
⠋ Importing CORE_DECODER_REGISTRY...
⠋ Trying ax.generation_strategy.generation_node...
⠋ Importing GenerationStep, GenerationStrategy from generation_strategy...
⠋ Importing GenerationNode from generation_node...
⠋ Importing ExternalGenerationNode...
⠋ Importing MaxTrials...
⠋ Importing GeneratorSpec...
⠋ Importing Models from ax.generation_strategy.registry...
⠋ Importing get_pending_observation_features...
⠋ Importing load_experiment...
⠋ Importing save_experiment...
⠋ Importing save_experiment_to_db...
⠋ Importing TrialStatus...
⠋ Importing Data...
⠋ Importing Experiment...
⠋ Importing parameter types...
⠋ Importing TParameterization...
⠋ Importing pandas...
⠋ Importing AxClient and ObjectiveProperties...
⠋ Importing RandomForestRegressor...
⠋ Importing botorch...
⠋ Importing submitit...
⠋ Importing ax logger...
⠋ Importing SQL-Storage-Stuff...
Using old run's --time: 60
Using old run's --gpus: 0
Run-UUID: c08afaa5-661b-4b7f-b1e3-b33582dc218d
_________________________________________________
/ \
| OmniOpt2 - More focused than a cat watching a las |
| er pointer. |
\ /
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/ / \/ \ \
/__|O||O|__ \
|/_ \_/\_/ _\ |
| | (____) | ||
\/\___/\__/ //
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\ //_/
\______//
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(____(____)
⠋ Writing worker creation log...
omniopt --continue runs/__main__tests__BOTORCH_MODULAR___nogridsearch/1 --num_parallel_jobs 1 --worker_timeout 10 --follow --gpus=0 --mem_gb=4 --num_random_steps=1 --max_eval=2 --parameter float_param range -1000 1000 float --send_anonymized_usage_stats --generate_all_jobs_at_once --live_share
⠋ Disabling logging...
⠋ Setting run folder...
⠋ Creating folder /var/opt/omniopt/runs/__main__tests__BOTORCH_MODULAR___nogridsearch/2...
⠋ Writing revert_to_random_when_seemingly_exhausted file ...
⠋ Writing username state file...
⠋ Writing result names file...
⠋ Writing result min/max file...
⠋ Saving state files...
Run-folder: /var/opt/omniopt/runs/__main__tests__BOTORCH_MODULAR___nogridsearch/2
Continuation from runs/__main__tests__BOTORCH_MODULAR___nogridsearch/1
⠋ Writing live_share file if it is present...
⠋ Writing job_start_time file...
⠋ Writing git information
⠋ Checking max_eval...
⠋ Calculating number of steps...
⠋ Adding excluded nodes...
⠋ Initializing ax_client...
Changed parameter 'float_param': lower from -100.0 to -1000.0, upper from 10.0 to 1000.0, digits from None to 32
⠋ Setting orchestrator...
See https://imageseg.scads.de/omniax/share?user_id=defaultuser&experiment_name=__main__tests__BOTORCH_MODULAR___nogridsearch&run_nr=745 for live-results.
You have 4 CPUs available for the main process. No CUDA devices found.
Generation strategy: BOTORCH_MODULAR for 9 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
┏━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━┓
┃ Name ┃ Type ┃ Lower bound ┃ Upper bound ┃ Values ┃ Type ┃ Log Scale? ┃
┡━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━┩
│ int_param │ rangeparameter │ -100 │ 10 │ │ int │ No │
│ float_param │ rangeparameter │ -1000 │ 1000 │ │ float │ No │
│ choice_param │ choiceparameter │ │ │ 1, 2, 4, 8, 16, hallo │ │ │
│ int_param_two │ rangeparameter │ -100 │ 10 │ │ int │ No │
└───────────────┴─────────────────┴─────────────┴─────────────┴───────────────────────┴───────┴────────────┘
Result-Names
┏━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ Result-Name ┃ Min or max? ┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ RESULT │ min │
└─────────────┴─────────────┘
⠋ Write files and show overview
BOTORCH_MODULAR, best RESULT: -10320107.72, finishing jobs, finished 1 job : 100%|██████████| 6/6 [00:30<00:00, 5.15s/it]
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 ┃ int_param_two ┃ choice_param ┃ RESULT ┃
┡━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━┩
│ -100.0 │ -100.0 │ -1000.0 │ 4.0 │ -100 │ -1000.0 │ -100 │ 4 │ -10320107.72 │
└───────────────────┴───────────────────────┴─────────────────────┴──────────────────────┴───────────┴─────────────┴───────────────┴──────────────┴──────────────┘
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 │
└───────────────────────┴───────────┴───────────┴──────────────┴─────────────┘
2025-10-31 11:03:24 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, Started OmniOpt2 run...
2025-10-31 11:03:26 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, getting new HP set (no sbatch)
2025-10-31 11:03:26 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, requested 1 jobs, got 1, 1.86 s/job
2025-10-31 11:03:26 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, eval #1/1 start
2025-10-31 11:03:26 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, starting new job
2025-10-31 11:03:26 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, started new job
2025-10-31 11:03:35 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, new result: RESULT: -9431035.925936
2025-10-31 11:03:40 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, best RESULT: -9431035.92593593, finishing jobs, finished 1 job
2025-10-31 11:03:42 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, best RESULT: -9431035.92593593, getting new HP set (no sbatch)
2025-10-31 11:03:42 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, best RESULT: -9431035.92593593, requested 1 jobs, got 1, 1.59 s/job
2025-10-31 11:03:42 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, best RESULT: -9431035.92593593, eval #1/1 start
2025-10-31 11:03:42 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, best RESULT: -9431035.92593593, starting new job
2025-10-31 11:03:42 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, best RESULT: -9431035.92593593, started new job
2025-10-31 11:03:51 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, best RESULT: -9431035.92593593, new result: RESULT: -10320107.720000
2025-10-31 11:03:55 (f16b50f3-d7dc-42b1-a4a6-9e4e7e43cd1b): BOTORCH_MODULAR, best RESULT: -10320107.72, finishing jobs, finished 1 job
This logs the CPU and RAM usage of the main worker process.
timestamp,ram_usage_mb,cpu_usage_percent
1761908591,803.8046875,28.7