run_benchmark_global.py

import os, shutil
from multiprocessing import Pool
from pathlib import Path
PY3="python3"

GPU = "0"
os.environ["CUDA_VISIBLE_DEVICES"] = GPU

PREPROCESSING_DIR="/benchmark/experiments/RoReg/preprocessing/"

base_command = (f'{PY3}' + ' Test.py --RD --RM --ET yohoo')

# datasets = (['urban05', 'apartment', 'gazebo_summer', 'gazebo_winter', 'hauptgebaude', 'plain', 'stairs',
#             'wood_autumn', 'wood_summer', 'long_office_household', 'pioneer_slam', 'pioneer_slam3', 'box_met',
#              'p2at_met', 'planetary_map'])

datasets = (['wood_summer', 'long_office_household', 'pioneer_slam', 'pioneer_slam3', 'box_met',
             'p2at_met', 'planetary_map'])

commands = []

for dataset in datasets:
    full_command = (base_command + f' --testset {dataset}')

    time_command = f'command time --verbose -o {PREPROCESSING_DIR}/roreg_stats/{dataset}_time.txt ' + full_command
    nvidia_command = (f'nvidia-smi --query-gpu=timestamp,memory.used -i 0 --format=csv -lms 1 > {PREPROCESSING_DIR}'
                      f'/roreg_stats/{dataset}_memory.txt')

    full_command_stats = f'parallel -j2 -u --halt now,success=1 ::: \'{time_command}\' \'{nvidia_command}\''
    commands.append(full_command_stats)

if not os.path.exists(PREPROCESSING_DIR+"/roreg_stats"):
    os.makedirs(PREPROCESSING_DIR+"/roreg_stats")

# save config in result directory
txt_commands = os.path.join(PREPROCESSING_DIR, "readme_roreg.md")
with open(txt_commands, 'w') as f:
    for item in commands:
        f.write("%s\n" % item)

pool = Pool(1)
pool.map(os.system, commands)