OmniOpt2

Experiment overview

Setting	Value
Model for non-random steps	BOTORCH_MODULAR
Max. nr. evaluations	2
Number random steps	1
Nr. of workers (parameter)	1

Best RESULT1, min (total: 2)

RESULT2	int_param	float_param	int_param_two	choice_param	RESULT1
2.4320510804859348	-17	-45.96849374546333	-92	8	1.5327858714890752

Job Summary per Generation Node

Generation Node	Total	COMPLETED
SOBOL	1	1
BOTORCH_MODULAR	1	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

Number of evaluations

Failed	Succeeded	Running	Total
0	2	0	2

Result names and types

name	min/max
RESULT1	min
RESULT2	max

Last progressbar status

2026-08-09 20:47:26 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): BOTORCH_MODULAR, 2 done, ▁█, finishing jobs, finished 1 job

Git-Version

Commit: 75fb0beff736f58928627480ad8135357bb70044 (9418-7-g75fb0beff)

config_objectives not found


========================================================================


Current git-hash: 75fb0beff736f58928627480ad8135357bb70044 (last fully tested stable version 7 commits ago [b54799bbb6092ee7a47e6c8cafaff1661ff693b6, 9418])
Using coverage run -p because $RUN_WITH_COVERAGE is set
[INFO 08-09 20:46:23] ax.storage.sqa_store.with_db_settings_base: Ax SQL storage initialized with SQLAlchemy 2.0.51
Run-UUID: 76e9dad2-3880-472e-9e7d-974c1b5cbb55
/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.")
  _________________________________
| OmniOpt2 - Optimizing with style! |
  =================================
                                 \
                                  \
                                   \
                                    \
                                              ,.
                                             (_|,.
                                             ,' /, )_______   _
                                         __j o``-'        `.'-)'
                                         (")                 \'
                                         `-j                |
                                           `-._(           /
                                              |_\  |--^.  /
                                             /_]'|_| /_)_/
                                                 /_]'  /_]'
omniopt --live_share --send_anonymized_usage_stats --partition alpha --experiment_name multiple_evals_per_arm --mem_gb=4 --time 1200 --worker_timeout=5 --max_eval 2 --num_parallel_jobs 1 --gpus 0 --run_program Li8udGVzdHMvb3B0aW1pemF0aW9uX2V4YW1wbGUgIC0taW50X3BhcmFtPSclKGludF9wYXJhbSknIC0tZmxvYXRfcGFyYW09JyUoZmxvYXRfcGFyYW0pJyAtLWNob2ljZV9wYXJhbT0nJShjaG9pY2VfcGFyYW0pJyAtLWludF9wYXJhbV90d289JyUoaW50X3BhcmFtX3R3byknIC0tbnJfcmVzdWx0cz0y --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 --num_random_steps 1 --model BOTORCH_MODULAR --auto_exclude_defective_hosts --result_names RESULT1=min RESULT2=max --generate_all_jobs_at_once --revert_to_random_when_seemingly_exhausted --nr_evals_per_arm=2 --beartype --show_generate_time_table --disable_notifications
Run-folder: /home/runner/work/OmniOpt/OmniOpt/runs/multiple_evals_per_arm/0
See https://imageseg.scads.de/omniax/share?user_id=runner&experiment_name=multiple_evals_per_arm&run_nr=40 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=2
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         │
└───────────────┴────────┴─────────────┴─────────────┴───────────────────────┴───────┴────────────┘
config_objectives not found
Your console does not support sixel-images. Will not print Pareto-frontier as a 
matplotlib-sixel-plot for RESULT1/RESULT2.
Pareto-Front for RESULT1/RESULT2:
┏━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓
┃ trial_index ┃ int_param ┃    float_param     ┃ int_param_two ┃ choice_param ┃      RESULT1       ┃      RESULT2       ┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
│      1      │    -17    │ -45.96849374546333 │      -92      │      8       │ 1.5327858714890752 │ 2.4320510804859348 │
└─────────────┴───────────┴────────────────────┴───────────────┴──────────────┴────────────────────┴────────────────────┘
Failed Jobs parameters
┏━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ param1 ┃ param2 ┃ param3 ┃ error_description                                                 ┃
┡━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ value1 │ value2 │ value3 │ Some error occurred during execution (this is not a real error!). │
└────────┴────────┴────────┴───────────────────────────────────────────────────────────────────┘
Not printing sixel graphics in CI
Not printing sixel graphics in CI
Runtime Infos
┏━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ Number of evaluations ┃  Min time  ┃  Max time  ┃ Average time ┃ Median time ┃
┡━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│           2           │ 12.00 sec  │ 12.00 sec  │  12.00 sec   │  12.00 sec  │
└───────────────────────┴────────────┴────────────┴──────────────┴─────────────┘
Model generation times
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Iteration ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│         1 │   0.050 │    1 │        0.050 │
│         2 │  23.985 │    1 │       23.985 │
├───────────┼─────────┼──────┼──────────────┤
│   Average │  12.018 │      │              │
│    Median │  12.018 │      │              │
│     Total │  24.035 │      │              │
│       Max │  23.985 │      │              │
│       Min │   0.050 │      │              │
└───────────┴─────────┴──────┴──────────────┘
Job submission durations
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃   Batch ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│       1 │   0.298 │    1 │        0.298 │
│       2 │   0.122 │    1 │        0.122 │
├─────────┼─────────┼──────┼──────────────┤
│ Average │   0.210 │      │              │
│  Median │   0.210 │      │              │
│   Total │   0.420 │      │              │
│     Max │   0.298 │      │              │
│     Min │   0.122 │      │              │
└─────────┴─────────┴──────┴──────────────┘

╭─────────────────────────────────────────────────────────────── OmniOpt2 Run Summary ───────────────────────────────────────────────────────────────╮
│                                                                                                                                                    │
│  ✅  Optimization complete!                                                                                                                        │
│                                                                                                                                                    │
│    📊 Trials: 2 succeeded / 0 failed / 2 done / 2 submitted                                                                                        │
│    ⏱️  Duration: 76s (1m16s)                                                                                                                       │
│    🏆 Best RESULT1: 1.5327858714890752                                                                                                             │
│    🏆 Best RESULT2: 2.537620994                                                                                                                    │
│    📁 Results: /home/runner/work/OmniOpt/OmniOpt/runs/multiple_evals_per_arm/0/results.csv                                                         │
│    🤖 Model: BOTORCH_MODULAR                                                                                                                       │
│                                                                                                                                                    │
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

2026-08-09 20:46:26 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): SOBOL, Started OmniOpt2 run...
2026-08-09 20:46:26 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): SOBOL, getting new HP set (no sbatch)
2026-08-09 20:46:26 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): SOBOL, requested 1 jobs, got 1, 0.05 s/job
2026-08-09 20:46:26 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): SOBOL, eval #1/1 start                    
2026-08-09 20:46:26 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): SOBOL, starting new job                   
2026-08-09 20:46:27 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): SOBOL, started new job                    
2026-08-09 20:46:42 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): SOBOL, new result: RESULT1: 1.586485 (SEM: 0.331364), RESULT2: 2.537621 (SEM: 0.109577)
2026-08-09 20:46:44 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): SOBOL, 1 done, finishing jobs, finished 1 job                                          
2026-08-09 20:47:08 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): BOTORCH_MODULAR, 1 done, getting new HP set (no sbatch)                                
2026-08-09 20:47:08 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): BOTORCH_MODULAR, 1 done, requested 1 jobs, got 1, 23.99 s/job                          
2026-08-09 20:47:08 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): BOTORCH_MODULAR, 1 done, eval #1/1 start                                               
2026-08-09 20:47:08 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): BOTORCH_MODULAR, 1 done, starting new job                                              
2026-08-09 20:47:08 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): BOTORCH_MODULAR, 1 done, started new job                                               
2026-08-09 20:47:23 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): BOTORCH_MODULAR, 1 done, new result: RESULT1: 1.532786 (SEM: 0.076087), RESULT2: 2.432051 (SEM: 0.398702)
2026-08-09 20:47:26 (471cd8bc-18b9-42ef-8b05-750c1946e9bd): BOTORCH_MODULAR, 2 done, ▁█, finishing jobs, finished 1 job

         Job submission durations          
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃   Batch ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│       1 │   0.298 │    1 │        0.298 │
│       2 │   0.122 │    1 │        0.122 │
├─────────┼─────────┼──────┼──────────────┤
│ Average │   0.210 │      │              │
│  Median │   0.210 │      │              │
│   Total │   0.420 │      │              │
│     Max │   0.298 │      │              │
│     Min │   0.122 │      │              │
└─────────┴─────────┴──────┴──────────────┘

           Model generation times            
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Iteration ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│         1 │   0.050 │    1 │        0.050 │
│         2 │  23.985 │    1 │       23.985 │
├───────────┼─────────┼──────┼──────────────┤
│   Average │  12.018 │      │              │
│    Median │  12.018 │      │              │
│     Total │  24.035 │      │              │
│       Max │  23.985 │      │              │
│       Min │   0.050 │      │              │
└───────────┴─────────┴──────┴──────────────┘

Arguments Overview

Key	Value
config_yaml	None
config_toml	None
config_json	None
num_random_steps	1
max_eval	2
run_program	[['Li8udGVzdHMvb3B0aW1pemF0aW9uX2V4YW1wbGUgIC0taW50X3BhcmFtPSclKGludF9wYXJhbSknIC0tZmxvYXRfcGFyYW09Jy…
experiment_name	multiple_evals_per_arm
mem_gb	4
parameter	[['int_param', 'range', '-100', '10', 'int'], ['float_param', 'range', '-100', '10', 'float'],
	['choice_param', 'choice', '1,2,4,8,16,hallo'], ['int_param_two', 'range', '-100', '10', 'int']]
continue_previous_job	None
experiment_constraints	None
run_dir	runs
seed	None
verbose_tqdm	False
model	BOTORCH_MODULAR
gridsearch	False
occ	False
show_sixel_scatter	False
show_sixel_general	False
show_sixel_trial_index_result	False
follow	False
send_anonymized_usage_stats	True
ui_url	None
root_venv_dir	/home/runner
exclude	None
main_process_gb	8
max_nr_of_zero_results	10
abbreviate_job_names	False
orchestrator_file	None
checkout_to_latest_tested_version	False
live_share	True
disable_tqdm	False
disable_previous_job_constraint	False
workdir
occ_type	euclid
result_names	['RESULT1=min', 'RESULT2=max']
minkowski_p	2
signed_weighted_euclidean_weights
generation_strategy	None
generate_all_jobs_at_once	True
revert_to_random_when_seemingly_exhausted	True
load_data_from_existing_jobs	[]
n_estimators_randomforest	100
max_attempts_for_generation	20
external_generator	None
username	None
max_failed_jobs	None
num_cpus_main_job	None
calculate_pareto_front_of_job	[]
show_generate_time_table	True
force_choice_for_ranges	False
max_abandoned_retrial	20
share_password	None
dryrun	False
db_url	None
run_program_once	None
worker_generator_path	None
save_to_database	False
range_max_difference	1000000
skip_search	False
nr_evals_per_arm	2
disable_notifications	True
dump_config	None
dont_warm_start_refitting	False
refit_on_cv	False
fit_out_of_design	False
fit_abandoned	False
dont_jit_compile	False
num_restarts	20
raw_samples	1024
max_num_of_parallel_sruns	16
no_transform_inputs	False
no_normalize_y	False
transforms	[]
number_of_generators	1
num_parallel_jobs	1
worker_timeout	5
slurm_use_srun	False
time	1200
partition	alpha
reservation	None
force_local_execution	False
slurm_signal_delay_s	0
nodes_per_job	1
cpus_per_task	1
account	None
gpus	0
dependency	None
run_mode	local
verbose	False
verbose_break_run_search_table	False
debug	False
flame_graph	False
memray	False
no_sleep	False
tests	False
show_worker_percentage_table_at_end	False
auto_exclude_defective_hosts	True
run_tests_that_fail_on_taurus	False
raise_in_eval	False
show_ram_every_n_seconds	0
show_generation_and_submission_sixel	False
just_return_defaults	False
prettyprint	False
runtime_debug	False
debug_stack_regex
debug_stack_trace_regex	None
show_func_name	False
beartype	True

This logs the CPU and RAM usage of the main worker process.

timestamp,ram_usage_mb,cpu_usage_percent
1786308384,881.7734375,26.7

! No notable correlations between parameters were found (threshold: |r| > 0.3).

Top-5 Best Results

Parameter Sensitivity Ranking

Parameters ranked by absolute Pearson correlation with each result. Stronger correlations (|r| ≥ 0.7) suggest the parameter has more influence on the outcome.

Parameter statistics

Parameter	Min	Max	Mean	Std Dev	Count
run_time	12	12	12	0	2
RESULT2	2.4321	2.5376	2.4848	0.0528	2
RESULT1	1.5328	1.5865	1.5596	0.0268	2
int_param	-66	-17	-41.5	24.5	2
float_param	-46.7105	-45.9685	-46.3395	0.371	2
int_param_two	-92	-10	-51	41	2
choice_param	1	8	4.5	3.5	2