updates

train.py

@@ -204,6 +204,7 @@ def train():
     model.nc = nc  # attach number of classes to model
     model.arc = opt.arc  # attach yolo architecture
     model.hyp = hyp  # attach hyperparameters to model
+    if hasattr(dataset, 'labels'):
         model.class_weights = labels_to_class_weights(dataset.labels, nc).to(device)  # attach class weights
     torch_utils.model_info(model, report='summary')  # 'full' or 'summary'
     nb = len(dataloader)