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}")