fix multiple dirs in DDP mode (#113)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing-q <1185102784@qq.com>

ultralytics/yolo/engine/model.py

@@ -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

ultralytics/yolo/engine/predictor.py

@@ -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
+        project = self.args.project or f"runs/{self.args.task}"
-        name = overrides.get("name") or self.args.mode
+        name = self.args.name or f"{self.args.mode}"
-        self.save_dir = increment_path(Path("runs") / project / name, exist_ok=self.args.exist_ok)
+        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

ultralytics/yolo/engine/trainer.py

@@ -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
+        project = self.args.project or f"runs/{self.args.task}"
-        name = overrides.get("name") or self.args.mode
+        name = self.args.name or f"{self.args.mode}"
-        self.save_dir = increment_path(Path("runs") / project / name, exist_ok=self.args.exist_ok)
+        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

ultralytics/yolo/engine/validator.py

@@ -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
+        project = self.args.project or f"runs/{self.args.task}"
-        name = self.args.name if self.args.name != "exp" else self.args.mode
+        name = self.args.name or f"{self.args.mode}"
-        self.save_dir = increment_path(Path("runs") / project / name, exist_ok=self.args.exist_ok)
+        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()

ultralytics/yolo/utils/configs/default.yaml

@@ -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'
+project: null
-name: 'exp'
+name: null
 exist_ok: False
 pretrained: False
 optimizer: 'SGD'  # choices=['SGD', 'Adam', 'AdamW', 'RMSProp']

ultralytics/yolo/v8/classify/train.py

@@ -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"])

ultralytics/yolo/v8/detect/val.py

@@ -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]