should fix the issue with missing layers in chechpoint merger

modules/extras.py

@@ -209,7 +209,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
 
     for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
-            theta_0[key] = theta_func(theta_0[key], theta_1[key], theta_2[key] if theta_2 else None, (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
+            t2 = (theta_2 or {}).get(key)
+            if t2 is None:
+                t2 = torch.zeros_like(theta_0[key])
+
+            theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
+
             if save_as_half:
                 theta_0[key] = theta_0[key].half()