return None if no ex_bias

extensions-builtin/Lora/network.py

@@ -145,10 +145,10 @@ class NetworkModule:
         if orig_weight.size().numel() == updown.size().numel():
             updown = updown.reshape(orig_weight.shape)
 
-        if ex_bias is None:
-            ex_bias = 0
+        if ex_bias is not None:
+            ex_bias = ex_bias * self.multiplier()
 
-        return updown * self.calc_scale() * self.multiplier(), ex_bias * self.multiplier()
+        return updown * self.calc_scale() * self.multiplier(), ex_bias
 
     def calc_updown(self, target):
         raise NotImplementedError()

extensions-builtin/Lora/networks.py

@@ -322,7 +322,7 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
                         updown = torch.nn.functional.pad(updown, (0, 0, 0, 0, 0, 5))
 
                     self.weight += updown
-                    if getattr(self, 'bias', None) is not None:
+                    if ex_bias is not None and getattr(self, 'bias', None) is not None:
                         self.bias += ex_bias
                     continue