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_par…	int_param_…	choice_pa…	RESULT1
2.6684728…	-8	-56.33866…	10	8	1.29567895…

Job Summary per Generation Node

Generation Node	Total	COMPLETED
SOBOL	1	1
BOTORCH_MODULAR	1	1

Experiment parameters

		Lower	Upper			Log
Name	Type	bound	bound	Values	Type	Scale?
int_param	range	-100	10		int	No
float_pa…	range	-100	10		float	No
choice_p…	choice			1, 2, 4,
				8, 16,
				hallo
int_para…	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

2026-10-30 15:17:00 (b8591098-6724-4182-a3ff-978c46129128): BOTORCH_MODULAR, 2 done, █▁, finishing jobs, finished 1 job

Git-Version

Commit: 62893ae80f6fd2c5fdcce1c4d576e2a43605f0bd (10061-3-g62893ae80)

Run-UUID: 1633ceb9-405b-4184-b891-9bddf614d687
  _________________________________________________
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| OmniOpt2 - Hyperparameter tuning: the art of maki |
| ng educated guesses look scientific!              |
 \                                                 /
  =================================================
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                                                         `-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 --force_local_execution --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
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=100 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
┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━┓
┃           ┃        ┃ Lower      ┃ Upper     ┃            ┃       ┃ Log       ┃
┃ Name      ┃ Type   ┃ bound      ┃ bound     ┃ Values     ┃ Type  ┃ Scale?    ┃
┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━┩
│ int_param │ range  │ -100       │ 10        │            │ int   │ No        │
│ float_pa… │ range  │ -100       │ 10        │            │ float │ No        │
│ choice_p… │ choice │            │           │ 1, 2, 4,   │       │           │
│           │        │            │           │ 8, 16,     │       │           │
│           │        │            │           │ hallo      │       │           │
│ int_para… │ range  │ -100       │ 10        │            │ int   │ No        │
└───────────┴────────┴────────────┴───────────┴────────────┴───────┴───────────┘
Result-Names
┏━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ Result-Name ┃ Min or max? ┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ RESULT1     │         min │
│ RESULT2     │         min │
└─────────────┴─────────────┘
Pareto-Front for RESULT1/RESULT2:
┏━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┓
┃ trial_i… ┃ int_par… ┃ float_p… ┃ int_para… ┃ choice_… ┃  RESULT1  ┃ RESULT2  ┃
┡━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━┩
│    0     │    -8    │ -56.338… │    10     │    8     │ 1.295678… │ 2.66847… │
├──────────┼──────────┼──────────┼───────────┼──────────┼───────────┼──────────┤
│    1     │   -93    │ -93.537… │    -87    │    2     │ 1.426645… │ 2.65601… │
└──────────┴──────────┴──────────┴───────────┴──────────┴───────────┴──────────┘
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  │ 13.00 sec  │  12.50 sec   │  12.50 sec  │
└───────────────────────┴────────────┴────────────┴──────────────┴─────────────┘
Model generation times
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Iteration ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│         1 │   0.031 │    1 │        0.031 │
│         2 │   0.612 │    1 │        0.612 │
├───────────┼─────────┼──────┼──────────────┤
│   Average │   0.322 │      │              │
│    Median │   0.322 │      │              │
│     Total │   0.643 │      │              │
│       Max │   0.612 │      │              │
│       Min │   0.031 │      │              │
└───────────┴─────────┴──────┴──────────────┘
Job submission durations
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃   Batch ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│       1 │   0.153 │    1 │        0.153 │
│       2 │   0.107 │    1 │        0.107 │
├─────────┼─────────┼──────┼──────────────┤
│ Average │   0.130 │      │              │
│  Median │   0.130 │      │              │
│   Total │   0.260 │      │              │
│     Max │   0.153 │      │              │
│     Min │   0.107 │      │              │
└─────────┴─────────┴──────┴──────────────┘

╭──────────────────────────── OmniOpt2 Run Summary ────────────────────────────╮
│                                                                              │
│  ✅  Optimization complete!                                                  │
│                                                                              │
│    📊 Trials: 2 succeeded / 0 failed / 2 done / 2 submitted                  │
│    ⏱️  Duration: 49s                                                         │
│    🏆 Best RESULT1: 1.2956789554                                             │
│    🏆 Best RESULT2: 2.6684728476                                             │
│    📁 Results: /home/runner/work/OmniOpt/OmniOpt/runs/multiple_evals_per_ar  │
│    🤖 Model: BOTORCH_MODULAR                                                 │
│                                                                              │
╰──────────────────────────────────────────────────────────────────────────────╯

2026-10-30 15:16:25 (b8591098-6724-4182-a3ff-978c46129128): SOBOL, Started OmniOpt2 run...
2026-10-30 15:16:25 (b8591098-6724-4182-a3ff-978c46129128): SOBOL, getting new HP set (no sbatch)
2026-10-30 15:16:25 (b8591098-6724-4182-a3ff-978c46129128): SOBOL, requested 1 jobs, got 1, 0.03 s/job
2026-10-30 15:16:25 (b8591098-6724-4182-a3ff-978c46129128): SOBOL, eval #1/1 start                    
2026-10-30 15:16:25 (b8591098-6724-4182-a3ff-978c46129128): SOBOL, starting new job                   
2026-10-30 15:16:25 (b8591098-6724-4182-a3ff-978c46129128): SOBOL, started new job                    
2026-10-30 15:16:41 (b8591098-6724-4182-a3ff-978c46129128): SOBOL, new result: RESULT1: 1.295679 (SEM: 0.007539), RESULT2: 2.668473 (SEM: 0.275717)
2026-10-30 15:16:42 (b8591098-6724-4182-a3ff-978c46129128): SOBOL, 1 done, finishing jobs, finished 1 job                                          
2026-10-30 15:16:43 (b8591098-6724-4182-a3ff-978c46129128): BOTORCH_MODULAR, 1 done, getting new HP set (no sbatch)                                
2026-10-30 15:16:43 (b8591098-6724-4182-a3ff-978c46129128): BOTORCH_MODULAR, 1 done, requested 1 jobs, got 1, 0.61 s/job                           
2026-10-30 15:16:43 (b8591098-6724-4182-a3ff-978c46129128): BOTORCH_MODULAR, 1 done, eval #1/1 start                                               
2026-10-30 15:16:43 (b8591098-6724-4182-a3ff-978c46129128): BOTORCH_MODULAR, 1 done, starting new job                                              
2026-10-30 15:16:43 (b8591098-6724-4182-a3ff-978c46129128): BOTORCH_MODULAR, 1 done, started new job                                               
2026-10-30 15:16:58 (b8591098-6724-4182-a3ff-978c46129128): BOTORCH_MODULAR, 1 done, new result: RESULT1: 1.426645 (SEM: 0.083131), RESULT2: 2.656018 (SEM: 0.214141)
2026-10-30 15:17:00 (b8591098-6724-4182-a3ff-978c46129128): BOTORCH_MODULAR, 2 done, █▁, finishing jobs, finished 1 job

         Job submission durations          
┏━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃   Batch ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│       1 │   0.153 │    1 │        0.153 │
│       2 │   0.107 │    1 │        0.107 │
├─────────┼─────────┼──────┼──────────────┤
│ Average │   0.130 │      │              │
│  Median │   0.130 │      │              │
│   Total │   0.260 │      │              │
│     Max │   0.153 │      │              │
│     Min │   0.107 │      │              │
└─────────┴─────────┴──────┴──────────────┘

           Model generation times            
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Iteration ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│         1 │   0.031 │    1 │        0.031 │
│         2 │   0.612 │    1 │        0.612 │
├───────────┼─────────┼──────┼──────────────┤
│   Average │   0.322 │      │              │
│    Median │   0.322 │      │              │
│     Total │   0.643 │      │              │
│       Max │   0.612 │      │              │
│       Min │   0.031 │      │              │
└───────────┴─────────┴──────┴──────────────┘

Arguments Overview

Key	Value
install	False
config_yaml	None
config_toml	None
config_json	None
num_random_steps	1
max_eval	2
run_program	[['Li8udGVzdHMvb3B0aW1pemF0aW9uX2V4…
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
modules
venv
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
wait_until_ended	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
local_cpu_monitor	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_exha…	True
load_data_from_existing_jobs	[]
n_estimators_randomforest	100
max_attempts_for_generation	20
external_generator	None
optuna_sampler	None
optuna_pruner	none
optuna_n_startup_trials	10
optuna_multivariate	False
optuna_group	False
optuna_constraints	False
optuna_n_ei_candidates	0
optuna_storage	None
optuna_study_name	omniopt_study
optuna_no_load_if_exists	False
optuna_extra_iters	1
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
dump_config	None
formula	None
formula_mode	auto
formula_python_path	/home/runner/.omniax_venvs/Python_3…
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	True
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
1793373380,796.78515625,28.3

! 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	13	12.5	0.5	2
RESULT1	1.2957	1.4266	1.3612	0.0655	2
RESULT2	2.656	2.6685	2.6622	0.0062	2
int_param	-93	-8	-50.5	42.5	2
float_param	-93.5371	-56.3387	-74.9379	18.5992	2
int_param_two	-87	10	-38.5	48.5	2
choice_param	2	8	5	3	2