code: def multimodel_mixup(batch, model, mixup_fn):
      """
      Mixup for different models.
      For image data, use the mixup_fn from timm.
      For other types of data, the simplest way as choosing will be used.
  
      Parameters
      -------
      batch
          The origin data need to be mixed-up.
      model
          The model used on the task.It is used to get the useful column in batch.
      mixup_fn
          The mixup_fn from timm. It can mixup image and produce target label with lambda.
  
      Returns
      -------
      batch
          The mixed-up batch.
      mixup_label
          The mixed-up labels.
      """
      mixup_label = batch[model.label_key]
      if hasattr(model, "image_key"):
          batch[model.image_key], mixup_label = mixup_fn(
              batch[model.image_key], batch[model.label_key]
          )
      else:
          lam = None
          for permodel in model.model:
              if hasattr(permodel, "image_key"):
                  if lam is None:
                      (
                          batch[permodel.image_key],
                          mixup_label,
                          lam,
                      ) = mixup_fn(
                          batch[permodel.image_key],
                          batch[permodel.label_key],
                      )
                  else:
                      batch[permodel.image_key], _, _ = mixup_fn(
                          batch[permodel.image_key],
                          batch[permodel.label_key],
                          lam,
                      )
          for permodel in model.model:
              if hasattr(permodel, "categorical_key"):
                  mixup_others(batch[permodel.categorical_key], lam)
              if hasattr(permodel, "numerical_key"):
                  mixup_others(batch[permodel.numerical_key], lam)
              if hasattr(permodel, "text_token_ids_key"):
                  mixup_others(batch[permodel.text_token_ids_key], lam)
  
      return batch, mixup_label
  
file_path: autogluon/multimodal/src/autogluon/multimodal/data/mixup.py
imports: import numpy
  import torch
  from timm.data.mixup import Mixup, cutmix_bbox_and_lam, mixup_target
label_desc: Use image node_id 2 for calling a global function with example usage: multimodel_mixup(batch, model, mixup_fn) and returns: batch,  mixup_label