diff --git a/networks/lora.py b/networks/lora.py
index cfc517ce..6e860a03 100644
--- a/networks/lora.py
+++ b/networks/lora.py
@@ -514,17 +514,25 @@ class LoRANetwork(torch.nn.Module):
             all_params.append(param_data)
 
         if self.unet_loras:
-            for lora in self.unet_loras:
-                param_data = {'params': lora.parameters()}
+            if self.stratified_lr:
+                for lora in self.unet_loras:
+                    param_data = {'params': lora.parameters()}
+                    if unet_lr is not None:
+                        param_data['lr'] = unet_lr * self.get_stratified_lr_weight(lora)
+                    elif default_lr is not None:
+                        param_data['lr'] = default_lr * self.get_stratified_lr_weight(lora)
+                    if ('lr' in param_data) and (param_data['lr']==0):
+                        continue
+                    all_params.append(param_data)
+            else:
+                params = []
+                for lora in self.unet_loras:
+                    params.extend(lora.parameters())
+                param_data = {'params': params}
                 if unet_lr is not None:
                     param_data['lr'] = unet_lr
-                elif default_lr is not None:
-                    param_data['lr'] = default_lr
-                if self.stratified_lr and ('lr' in param_data):
-                    param_data['lr'] = param_data['lr'] * self.get_stratified_lr_weight(lora)
-                    if (param_data['lr']==0):
-                        continue
                 all_params.append(param_data)
+
         return all_params
 
     def enable_gradient_checkpointing(self):