thank you linter

extensions-builtin/Lora/lora.py

@@ -229,9 +229,9 @@ def load_lora(name, lora_on_disk):
         elif type(sd_module) == torch.nn.Conv2d and weight.shape[2:] == (3, 3):
             module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (3, 3), bias=False)
         else:
-            print(f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}')
+            print(f'Lora layer {key_lora} matched a layer with unsupported type: {type(sd_module).__name__}')
             continue
-            raise AssertionError(f"Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}")
+            raise AssertionError(f"Lora layer {key_lora} matched a layer with unsupported type: {type(sd_module).__name__}")
 
         with torch.no_grad():
             module.weight.copy_(weight)
@@ -243,7 +243,7 @@ def load_lora(name, lora_on_disk):
         elif lora_key == "lora_down.weight":
             lora_module.down = module
         else:
-            raise AssertionError(f"Bad Lora layer name: {key_diffusers} - must end in lora_up.weight, lora_down.weight or alpha")
+            raise AssertionError(f"Bad Lora layer name: {key_lora} - must end in lora_up.weight, lora_down.weight or alpha")
 
     if keys_failed_to_match:
         print(f"Failed to match keys when loading Lora {lora_on_disk.filename}: {keys_failed_to_match}")