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fix multiple dirs in DDP mode (#113)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
This commit is contained in:
Ayush Chaurasia 2022-12-29 15:02:17 +05:30 committed by GitHub
parent 34829a6b29
commit 100e21ee80
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7 changed files with 18 additions and 16 deletions
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2
ultralytics/yolo/engine/model.py
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@ -126,6 +126,7 @@ class YOLO:
"""
overrides = self.overrides.copy()
overrides.update(kwargs)
overrides["mode"] = "predict"
predictor = self.PredictorClass(overrides=overrides)
# check size type
@ -151,6 +152,7 @@ class YOLO:
overrides = self.overrides.copy()
overrides.update(kwargs)
overrides["mode"] = "val"
args = get_config(config=DEFAULT_CONFIG, overrides=overrides)
args.data = data or args.data
args.task = self.task

6
ultralytics/yolo/engine/predictor.py
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@ -46,9 +46,9 @@ class BasePredictor:
def __init__(self, config=DEFAULT_CONFIG, overrides={}):
self.args = get_config(config, overrides)
project = overrides.get("project") or self.args.task
name = overrides.get("name") or self.args.mode
self.save_dir = increment_path(Path("runs") / project / name, exist_ok=self.args.exist_ok)
project = self.args.project or f"runs/{self.args.task}"
name = self.args.name or f"{self.args.mode}"
self.save_dir = increment_path(Path(project) / name, exist_ok=self.args.exist_ok)
(self.save_dir / 'labels' if self.args.save_txt else self.save_dir).mkdir(parents=True, exist_ok=True)
self.done_setup = False

9
ultralytics/yolo/engine/trainer.py
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@ -24,7 +24,7 @@ import ultralytics.yolo.utils as utils
import ultralytics.yolo.utils.callbacks as callbacks
from ultralytics import __version__
from ultralytics.yolo.data.utils import check_dataset, check_dataset_yaml
from ultralytics.yolo.utils import LOGGER, ROOT, TQDM_BAR_FORMAT, colorstr
from ultralytics.yolo.utils import LOGGER, RANK, ROOT, TQDM_BAR_FORMAT, colorstr
from ultralytics.yolo.utils.checks import check_file, print_args
from ultralytics.yolo.utils.configs import get_config
from ultralytics.yolo.utils.dist import ddp_cleanup, generate_ddp_command
@ -32,7 +32,6 @@ from ultralytics.yolo.utils.files import get_latest_run, increment_path, save_ya
from ultralytics.yolo.utils.torch_utils import ModelEMA, de_parallel, init_seeds, one_cycle, strip_optimizer
DEFAULT_CONFIG = ROOT / "yolo/utils/configs/default.yaml"
RANK = int(os.getenv('RANK', -1))
class BaseTrainer:
@ -48,9 +47,9 @@ class BaseTrainer:
self.callbacks = defaultdict(list)
# dirs
project = overrides.get("project") or self.args.task
name = overrides.get("name") or self.args.mode
self.save_dir = increment_path(Path("runs") / project / name, exist_ok=self.args.exist_ok)
project = self.args.project or f"runs/{self.args.task}"
name = self.args.name or f"{self.args.mode}"
self.save_dir = increment_path(Path(project) / name, exist_ok=self.args.exist_ok if RANK == -1 else True)
self.wdir = self.save_dir / 'weights' # weights dir
self.wdir.mkdir(parents=True, exist_ok=True) # make dir
self.last, self.best = self.wdir / 'last.pt', self.wdir / 'best.pt' # checkpoint paths

9
ultralytics/yolo/engine/validator.py
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@ -8,7 +8,7 @@ from tqdm import tqdm
from ultralytics.nn.autobackend import AutoBackend
from ultralytics.yolo.data.utils import check_dataset, check_dataset_yaml
from ultralytics.yolo.engine.trainer import DEFAULT_CONFIG
from ultralytics.yolo.utils import LOGGER, TQDM_BAR_FORMAT
from ultralytics.yolo.utils import LOGGER, RANK, TQDM_BAR_FORMAT
from ultralytics.yolo.utils.files import increment_path
from ultralytics.yolo.utils.ops import Profile
from ultralytics.yolo.utils.torch_utils import check_imgsz, de_parallel, select_device, smart_inference_mode
@ -32,9 +32,10 @@ class BaseValidator:
self.speed = None
self.jdict = None
project = self.args.project if self.args.project != "runs/train" else self.args.task
name = self.args.name if self.args.name != "exp" else self.args.mode
self.save_dir = increment_path(Path("runs") / project / name, exist_ok=self.args.exist_ok)
project = self.args.project or f"runs/{self.args.task}"
name = self.args.name or f"{self.args.mode}"
self.save_dir = save_dir or increment_path(Path(project) / name,
exist_ok=self.args.exist_ok if RANK == -1 else True)
(self.save_dir / 'labels' if self.args.save_txt else self.save_dir).mkdir(parents=True, exist_ok=True)
@smart_inference_mode()

4
ultralytics/yolo/utils/configs/default.yaml
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@ -15,8 +15,8 @@ nosave: False
cache: False # True/ram, disk or False
device: '' # cuda device, i.e. 0 or 0,1,2,3 or cpu
workers: 8
project: 'runs/train'
name: 'exp'
project: null
name: null
exist_ok: False
pretrained: False
optimizer: 'SGD' # choices=['SGD', 'Adam', 'AdamW', 'RMSProp']

2
ultralytics/yolo/v8/classify/train.py
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@ -45,7 +45,7 @@ class ClassificationTrainer(BaseTrainer):
return batch
def get_validator(self):
return v8.classify.ClassificationValidator(self.test_loader, self.device, logger=self.console)
return v8.classify.ClassificationValidator(self.test_loader, self.save_dir, logger=self.console)
def criterion(self, preds, batch):
loss = torch.nn.functional.cross_entropy(preds, batch["cls"])

2
ultralytics/yolo/v8/detect/val.py
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@ -171,7 +171,7 @@ class DetectionValidator(BaseValidator):
pad=0.5,
rect=self.args.rect,
workers=self.args.workers,
prefix=colorstr(f'{val}: '),
prefix=colorstr(f'{self.args.mode}: '),
shuffle=False,
seed=self.args.seed)[0] if self.args.v5loader else \
build_dataloader(self.args, batch_size, img_path=dataset_path, stride=gs, mode="val")[0]