class_docstr: Load LoRA layers into [`UNet2DConditionModel`] and
  [`CLIPTextModel`](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel).
class_docstr_tok: ["Load","LoRA","layers","into","[","`","UNet2DConditionModel","`","]","and","[","`","CLIPTextModel","`","]","(","https",":","\/\/huggingface.co\/docs\/transformers\/model_doc\/clip","#","transformers.CLIPTextModel",")","."]
docstr: Unloads the LoRA parameters.
  
  Examples:
  
  ```python
  >>> # Assuming `pipeline` is already loaded with the LoRA parameters.
  >>> pipeline.unload_lora_weights()
  >>> ...
  ```
docstr_tok: ["Unloads","the","LoRA","parameters",".","Examples",":","``","`","python",">",">",">","#","Assuming","`","pipeline","`","is","already","loaded","with","the","LoRA","parameters",".",">",">",">","pipeline.unload_lora_weights","(",")",">",">",">","...","``","`"]
code: def unload_lora_weights(self):
      """
      Unloads the LoRA parameters.
  
      Examples:
  
      ```python
      >>> # Assuming `pipeline` is already loaded with the LoRA parameters.
      >>> pipeline.unload_lora_weights()
      >>> ...
      ```
      """
      unet = (
          getattr(self, self.unet_name)
          if not hasattr(self, "unet")
          else self.unet
      )
  
      if not USE_PEFT_BACKEND:
          if version.parse(__version__) > version.parse("0.23"):
              logger.warning(
                  "You are using `unload_lora_weights` to disable and unload lora weights. If you want to iteratively enable and disable adapter weights,"
                  "you can use `pipe.enable_lora()` or `pipe.disable_lora()`. After installing the latest version of PEFT."
              )
  
          for _, module in unet.named_modules():
              if hasattr(module, "set_lora_layer"):
                  module.set_lora_layer(None)
      else:
          recurse_remove_peft_layers(unet)
          if hasattr(unet, "peft_config"):
              del unet.peft_config
  
      # Safe to call the following regardless of LoRA.
      self._remove_text_encoder_monkey_patch()
  
imports: import inspect
  import os
  from contextlib import nullcontext
  from pathlib import Path
  from typing import Callable, Dict, List, Optional, Union
  import safetensors
  import torch
  from huggingface_hub import model_info
  from huggingface_hub.constants import HF_HUB_OFFLINE
  from huggingface_hub.utils import validate_hf_hub_args
  from packaging import version
  from torch import nn
  from ..None import __version__
  from ..models.modeling_utils import _LOW_CPU_MEM_USAGE_DEFAULT, load_model_dict_into_meta
  from ..utils import USE_PEFT_BACKEND, _get_model_file, convert_state_dict_to_diffusers, convert_state_dict_to_peft, convert_unet_state_dict_to_peft, delete_adapter_layers, deprecate, get_adapter_name, get_peft_kwargs, is_accelerate_available, is_transformers_available, logging, recurse_remove_peft_layers, scale_lora_layers, set_adapter_layers, set_weights_and_activate_adapters
  from .lora_conversion_utils import _convert_kohya_lora_to_diffusers, _maybe_map_sgm_blocks_to_diffusers
label_desc: Use image node_id 14 for calling the LoraLoaderMixin obj's underlying member method code with example usage: obj.unload_lora_weights() without return types