ultralytics 8.0.159 add Classify training resume feature (#4482)

ultralytics/models/yolo/classify/train.py

@@ -62,10 +62,10 @@ class ClassificationTrainer(BaseTrainer):
         if isinstance(self.model, torch.nn.Module):  # if model is loaded beforehand. No setup needed
             return
 
-        model = str(self.model)
+        model, ckpt = str(self.model), None
         # Load a YOLO model locally, from torchvision, or from Ultralytics assets
         if model.endswith('.pt'):
-            self.model, _ = attempt_load_one_weight(model, device='cpu')
+            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'):
@@ -76,7 +76,7 @@ class ClassificationTrainer(BaseTrainer):
             FileNotFoundError(f'ERROR: model={model} not found locally or online. Please check model name.')
         ClassificationModel.reshape_outputs(self.model, self.data['nc'])
 
-        return  # do not return ckpt. Classification doesn't support resume
+        return ckpt
 
     def build_dataset(self, img_path, mode='train', batch=None):
         return ClassificationDataset(root=img_path, args=self.args, augment=mode == 'train')
@@ -122,10 +122,6 @@ class ClassificationTrainer(BaseTrainer):
         loss_items = [round(float(loss_items), 5)]
         return dict(zip(keys, loss_items))
 
-    def resume_training(self, ckpt):
-        """Resumes training from a given checkpoint."""
-        pass
-
     def plot_metrics(self):
         """Plots metrics from a CSV file."""
         plot_results(file=self.csv, classify=True, on_plot=self.on_plot)  # save results.png