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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docstr: This method merges the layers into the base model. This is needed if someone wants to use the base model as a
  standalone model.
  
  Args:
      progressbar (`bool`):
          whether to show a progressbar indicating the unload and merge process
      safe_merge (`bool`):
          whether to activate the safe merging check to check if there is any potential Nan in the adapter
          weights
      adapter_names (`List[str]`, *optional*):
          The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
          to `None`.
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code: def merge_and_unload(
      self,
      progressbar: bool = False,
      safe_merge: bool = False,
      adapter_names: Optional[list[str]] = None,
  ) -> nn.Module:
      r"""
      This method merges the layers into the base model. This is needed if someone wants to use the base model as a
      standalone model.
  
      Args:
          progressbar (`bool`):
              whether to show a progressbar indicating the unload and merge process
          safe_merge (`bool`):
              whether to activate the safe merging check to check if there is any potential Nan in the adapter
              weights
          adapter_names (`List[str]`, *optional*):
              The list of adapter names that should be merged. If None, all active adapters will be merged. Defaults
              to `None`.
      """
      return self._unload_and_optionally_merge(
          progressbar=progressbar,
          safe_merge=safe_merge,
          adapter_names=adapter_names,
      )
  
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 16 for calling the MixedModel obj's underlying member method code with example usage: obj.merge_and_unload(progressbar, safe_merge, adapter_names) and returns: self