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BUGFIX: Dataloading CPU bottleneck (#11195)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Andreas Moldskred 2024-05-02 18:21:18 -07:00 • committed by GitHub
parent 835100163e
commit dda7869205
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2 changed files with 3 additions and 2 deletions
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3
ultralytics/data/build.py
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@ -20,7 +20,7 @@ from ultralytics.data.loaders import (
autocast_list,
)
from ultralytics.data.utils import IMG_FORMATS, VID_FORMATS
from ultralytics.utils import RANK, colorstr
from ultralytics.utils import NUM_THREADS, RANK, colorstr
from ultralytics.utils.checks import check_file
from .dataset import GroundingDataset, YOLODataset, YOLOMultiModalDataset
@ -81,6 +81,7 @@ def seed_worker(worker_id): # noqa
worker_seed = torch.initial_seed() % 2**32
np.random.seed(worker_seed)
random.seed(worker_seed)
os.sched_setaffinity(0, range(NUM_THREADS)) # fix https://github.com/ultralytics/ultralytics/pull/11195
def build_yolo_dataset(cfg, img_path, batch, data, mode="train", rect=False, stride=32, multi_modal=False):

2
ultralytics/utils/__init__.py
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@ -36,7 +36,7 @@ FILE = Path(__file__).resolve()
ROOT = FILE.parents[1] # YOLO
ASSETS = ROOT / "assets" # default images
DEFAULT_CFG_PATH = ROOT / "cfg/default.yaml"
NUM_THREADS = min(8, max(1, os.cpu_count() - 1)) # number of YOLOv5 multiprocessing threads
NUM_THREADS = min(8, max(1, os.cpu_count() - 1)) # number of YOLO multiprocessing threads
AUTOINSTALL = str(os.getenv("YOLO_AUTOINSTALL", True)).lower() == "true" # global auto-install mode
VERBOSE = str(os.getenv("YOLO_VERBOSE", True)).lower() == "true" # global verbose mode
TQDM_BAR_FORMAT = "{l_bar}{bar:10}{r_bar}" if VERBOSE else None # tqdm bar format