code: def apply_model_adaptation(
      model: nn.Module, config: DictConfig
  ) -> nn.Module:
      """
      Apply an adaptation to the model for efficient fine-tuning.
  
      Parameters
      ----------
      model
          A PyTorch model.
      config:
          A DictConfig object. The optimization config should be accessible by "config.optimization".
      """
      if (
          OmegaConf.select(config, "optimization.efficient_finetune")
          in PEFT_ADDITIVE_STRATEGIES
      ):
          model = inject_adaptation_to_linear_layer(
              model=model,
              efficient_finetune=OmegaConf.select(
                  config, "optimization.efficient_finetune"
              ),
              lora_r=config.optimization.lora.r,
              lora_alpha=config.optimization.lora.alpha,
              module_filter=config.optimization.lora.module_filter,
              filter=config.optimization.lora.filter,
              extra_trainable_params=OmegaConf.select(
                  config, "optimization.extra_trainable_params"
              ),
          )
          model.name_to_id = (
              model.get_layer_ids()
          )  # Need to update name to id dictionary.
  
      return model
  
file_path: autogluon/multimodal/src/autogluon/multimodal/utils/model.py
imports: import functools
  import json
  import logging
  import warnings
  from typing import Dict, List, Optional, Tuple, Union
  import timm
  from omegaconf import DictConfig, OmegaConf
  from torch import Tensor, nn
  from ..constants import ALL_MODALITIES, AUTOMM, CATEGORICAL, CATEGORICAL_MLP, CLIP, DOCUMENT, DOCUMENT_TRANSFORMER, FT_TRANSFORMER, FUSION_MLP, FUSION_NER, FUSION_TRANSFORMER, HF_TEXT, IMAGE, MMDET_IMAGE, MMOCR_TEXT_DET, MMOCR_TEXT_RECOG, NER, NER_TEXT, NUMERICAL, NUMERICAL_MLP, OVD, PEFT_ADDITIVE_STRATEGIES, SAM, SEMANTIC_SEGMENTATION_IMG, T_FEW, TEXT, TEXT_NER, TIMM_IMAGE, XYXY
  from ..data import MultiModalFeaturePreprocessor
  from ..models import CategoricalMLP, CLIPForImageText, DocumentTransformer, FT_Transformer, HFAutoModelForNER, HFAutoModelForTextPrediction, MMDetAutoModelForObjectDetection, MMOCRAutoModelForTextDetection, MMOCRAutoModelForTextRecognition, MultimodalFusionMLP, MultimodalFusionNER, MultimodalFusionTransformer, NumericalMLP, OVDModel, SAMForSemanticSegmentation, TFewModel, TimmAutoModelForImagePrediction
  from ..models.utils import inject_adaptation_to_linear_layer
label_desc: Use image node_id 4 for calling a global function with example usage: apply_model_adaptation(model, config) and returns: model