ultralytics 8.1.40 search in Python sets {} for speed (#9450)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/models/yolo/classify/train.py

@@ -68,7 +68,7 @@ class ClassificationTrainer(BaseTrainer):
             self.model, ckpt = attempt_load_one_weight(model, device="cpu")
             for p in self.model.parameters():
                 p.requires_grad = True  # for training
-        elif model.split(".")[-1] in ("yaml", "yml"):
+        elif model.split(".")[-1] in {"yaml", "yml"}:
             self.model = self.get_model(cfg=model)
         elif model in torchvision.models.__dict__:
             self.model = torchvision.models.__dict__[model](weights="IMAGENET1K_V1" if self.args.pretrained else None)

ultralytics/models/yolo/detect/train.py

@@ -44,7 +44,7 @@ class DetectionTrainer(BaseTrainer):
 
     def get_dataloader(self, dataset_path, batch_size=16, rank=0, mode="train"):
         """Construct and return dataloader."""
-        assert mode in ["train", "val"]
+        assert mode in {"train", "val"}, f"Mode must be 'train' or 'val', not {mode}."
         with torch_distributed_zero_first(rank):  # init dataset *.cache only once if DDP
             dataset = self.build_dataset(dataset_path, mode, batch_size)
         shuffle = mode == "train"

ultralytics/models/yolo/world/train.py

@@ -11,7 +11,7 @@ from ultralytics.utils.torch_utils import de_parallel
 
 def on_pretrain_routine_end(trainer):
     """Callback."""
-    if RANK in (-1, 0):
+    if RANK in {-1, 0}:
         # NOTE: for evaluation
         names = [name.split("/")[0] for name in list(trainer.test_loader.dataset.data["names"].values())]
         de_parallel(trainer.ema.ema).set_classes(names, cache_clip_model=False)