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Current git-hash: cb80b776bcc7f09c64c9df008280d045d3d61256 (last fully tested stable version 5 commits ago [208aac92c9d373d0a7ca51bdae9ece179ef45cd2, 8673])
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...⠋Parsing arguments...⠸Importing torch...⠋Importing numpy...
[WARNING 10-17 10:59:42] 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: 60Using old run's --gpus: 0
Run-UUID: aa83f6ab-149e-4f90-97d7-01176528c810
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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...⠋Setting global generation strategy⠋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...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=337 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: -10019211.72, finishing jobs, finished 1 job : 100%|██████████| 6/6 [00:28<00:00, 4.77s/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 │-24.0 │1000.0 │8.0 │-100 │1000.0 │-24 │8 │-10019211.72│
└───────────────────┴───────────────────────┴─────────────────────┴──────────────────────┴───────────┴─────────────┴───────────────┴──────────────┴──────────────┘
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 │
└───────────────────────┴───────────┴───────────┴──────────────┴─────────────┘
2025-10-17 10:59:45 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, Started OmniOpt2 run...
2025-10-17 10:59:46 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, getting new HP set (no sbatch)
2025-10-17 10:59:46 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, requested 1 jobs, got 1, 1.57 s/job
2025-10-17 10:59:46 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, eval #1/1 start
2025-10-17 10:59:46 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, starting new job
2025-10-17 10:59:46 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, started new job
2025-10-17 10:59:55 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, new result: -8336076.88283194
2025-10-17 11:00:00 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, best RESULT: -8336076.88283194, finishing jobs, finished 1 job
2025-10-17 11:00:01 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, best RESULT: -8336076.88283194, getting new HP set (no sbatch)
2025-10-17 11:00:01 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, best RESULT: -8336076.88283194, requested 1 jobs, got 1, 1.72 s/job
2025-10-17 11:00:01 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, best RESULT: -8336076.88283194, eval #1/1 start
2025-10-17 11:00:01 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, best RESULT: -8336076.88283194, starting new job
2025-10-17 11:00:02 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, best RESULT: -8336076.88283194, started new job
2025-10-17 11:00:11 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, best RESULT: -8336076.88283194, new result: -10019211.72
2025-10-17 11:00:13 (d7740630-b280-46b4-a949-f8daa41ef8e0): BOTORCH_MODULAR, best RESULT: -10019211.72, finishing jobs, finished 1 job
Job submission durations
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Batch ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 0.175 │ 1 │ 0.175 │
│ 2 │ 0.112 │ 1 │ 0.112 │
├─────────┼─────────┼──────┼──────────────┤
│ Average │ 0.143 │ │ │
│ Median │ 0.143 │ │ │
│ Total │ 0.287 │ │ │
│ Max │ 0.175 │ │ │
│ Min │ 0.112 │ │ │
└─────────┴─────────┴──────┴──────────────┘
Model generation times
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Iteration ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 1.565 │ 1 │ 1.565 │
│ 2 │ 1.723 │ 1 │ 1.723 │
├───────────┼─────────┼──────┼──────────────┤
│ Average │ 1.644 │ │ │
│ Median │ 1.644 │ │ │
│ Total │ 3.289 │ │ │
│ Max │ 1.723 │ │ │
│ Min │ 1.565 │ │ │
└───────────┴─────────┴──────┴──────────────┘
