Favor EMA over model in train checkpoints (#9433)

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

ultralytics/engine/trainer.py

@@ -42,7 +42,6 @@ from ultralytics.utils.files import get_latest_run
 from ultralytics.utils.torch_utils import (
     EarlyStopping,
     ModelEMA,
-    de_parallel,
     init_seeds,
     one_cycle,
     select_device,
@@ -486,7 +485,7 @@ class BaseTrainer:
             {
                 "epoch": self.epoch,
                 "best_fitness": self.best_fitness,
-                "model": deepcopy(de_parallel(self.model)).half(),
+                "model": None,  # resume and final checkpoints derive from EMA
                 "ema": deepcopy(self.ema.ema).half(),
                 "updates": self.ema.updates,
                 "optimizer": self.optimizer.state_dict(),
@@ -527,7 +526,7 @@ class BaseTrainer:
         ckpt = None
         if str(model).endswith(".pt"):
             weights, ckpt = attempt_load_one_weight(model)
-            cfg = ckpt["model"].yaml
+            cfg = weights.yaml
         else:
             cfg = model
         self.model = self.get_model(cfg=cfg, weights=weights, verbose=RANK == -1)  # calls Model(cfg, weights)