class_docstr: A class that allows to mix different types of adapters in a single model.
  
  Note: This class should usually not be initialized directly. Instead, use `get_peft_model` with the argument
  `mixed=True`.
  
  Args:
      model (:obj:`nn.Module`):
          The model to be tuned.
      config (:obj:`PeftConfig`):
          The config of the model to be tuned. The adapter type must be compatible.
      adapter_name (:obj:`str`):
          The name of the first adapter.
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code: def disable_adapter_layers(self):
      for active_adapter in self.active_adapters:
          val = getattr(
              self.peft_config[active_adapter], "bias", "none"
          )
          if val != "none":
              msg = (
                  f"Careful, disabling adapter layers with bias configured to be '{val}' does not produce the same "
                  "output as the the base model would without adaption."
              )
              warnings.warn(msg)
      self._set_adapter_layers(enabled=False)
  
imports: from __future__ import annotations
  import warnings
  from typing import Any, Optional, Union
  from torch import nn
  from tqdm import tqdm
  from peft.tuners import adalora, loha, lokr, lora, oft
  from peft.tuners.tuners_utils import BaseTuner, BaseTunerLayer, check_target_module_exists
  from peft.utils import TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING, ModulesToSaveWrapper, PeftType, _get_submodules, get_auto_gptq_quant_linear
label_desc: Use image node_id 10 for calling the MixedModel obj's underlying member method code with example usage: obj.disable_adapter_layers() without return types