updates

train.py

@@ -134,11 +134,12 @@ def train():
     if opt.transfer or opt.prebias:  # transfer learning edge (yolo) layers
         nf = int(model.module_defs[model.yolo_layers[0] - 1]['filters'])  # yolo layer size (i.e. 255)
 
-        for p in optimizer.param_groups:
-            # lower param count allows more aggressive training settings: i.e. SGD ~0.1 lr0, ~0.9 momentum
-            p['lr'] *= 100  # lr gain
-            if p.get('momentum') is not None:  # for SGD but not Adam
-                p['momentum'] *= 0.9
+        if opt.prebias:
+            for p in optimizer.param_groups:
+                # lower param count allows more aggressive training settings: i.e. SGD ~0.1 lr0, ~0.9 momentum
+                p['lr'] *= 100  # lr gain
+                if p.get('momentum') is not None:  # for SGD but not Adam
+                    p['momentum'] *= 0.9
 
         for p in model.parameters():
             if opt.prebias and p.numel() == nf:  # train (yolo biases)