Traceback (most recent call last):
File "A:\OneTrainer\modules\ui\TrainUIController.py", line 226, in __training_thread_function
trainer.start()
File "A:\OneTrainer\modules\trainer\GenericTrainer.py", line 141, in start
self.model_setup.setup_model(self.model, self.config)
File "A:\Trainers\OneTrainer\modules\modelSetup\Krea2LoRASetup.py", line 62, in setup_model
model.transformer_lora = LoRAModuleWrapper(
^^^^^^^^^^^^^^^^^^
File "A:\Trainers\OneTrainer\modules\module\LoRAModule.py", line 916, in __init__
self.lora_modules = self.__create_modules(orig_module, config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "A:\Trainers\OneTrainer\modules\module\LoRAModule.py", line 961, in __create_modules
lora_module = self.klass(prefixed_name, child_module, *self.additional_args, **self.additional_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "A:\OneTrainer\modules\module\LoRAModule.py", line 328, in __init__
self.initialize_weights()
File "A:\OneTrainer\modules\module\LoRAModule.py", line 439, in initialize_weights
self.dora_scale = Parameter(
^^^^^^^^^^
File "A:\OneTrainer\venv\Lib\site-packages\torch\nn\parameter.py", line 57, in __new__
return torch.Tensor._make_subclass(cls, data, requires_grad)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Only Tensors of floating point and complex dtype can require gradients
```</div>
Discussed in #1601
@Koratahiu
Originally posted by gith82387234 July 8, 2026
From what I've read and my limited understanding of it, this option in the LoRa tab can greatly help with overfitting, especially when replacing concepts... However enabling this option throws an error which disappears when disabled. Is it just not compatible with LoKr or could it be broken since LoKr support is relatively new?
The error in question: