class_docstr: Set up Pytorch DataSet and DataLoader objects to prepare data for single-modal/multimodal training,
  validation, testing, and prediction. We organize the multimodal data using pd.DataFrame.
  For some modalities, e.g, image, that cost much memory, we only store their disk path to do lazy loading.
  This class inherits from the Pytorch Lightning's LightningDataModule:
  https://lightning.ai/docs/pytorch/stable/data/datamodule.html
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docstr: Create the dataloader for prediction.
  This method is registered by Pytorch Lightning's LightningDataModule.
  Refer to: https://lightning.ai/docs/pytorch/stable/data/datamodule.html#predict-dataloader
  
  Returns
  -------
  A Pytorch DataLoader object.
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code: def predict_dataloader(self):
      """
      Create the dataloader for prediction.
      This method is registered by Pytorch Lightning's LightningDataModule.
      Refer to: https://lightning.ai/docs/pytorch/stable/data/datamodule.html#predict-dataloader
  
      Returns
      -------
      A Pytorch DataLoader object.
      """
      loader = DataLoader(
          self.predict_dataset,
          batch_size=self.per_gpu_batch_size,
          num_workers=self.num_workers,
          pin_memory=False,
          collate_fn=get_collate_fn(
              df_preprocessor=self.df_preprocessor,
              data_processors=self.data_processors,
              per_gpu_batch_size=self.per_gpu_batch_size,
          ),
          persistent_workers=self.num_workers > 0,
      )
      return loader
  
file_path: autogluon/multimodal/src/autogluon/multimodal/data/datamodule.py
imports: from typing import Dict, List, Optional, Union
  import pandas
  from lightning.pytorch import LightningDataModule
  from torch.utils.data import DataLoader, Dataset
  from ..constants import PREDICT, TEST, TRAIN, VALIDATE
  from .dataset import BaseDataset
  from .preprocess_dataframe import MultiModalFeaturePreprocessor
  from .utils import get_collate_fn
label_desc: Use image node_id 7 for calling the BaseDataModule obj's underlying member method code with example usage: obj.predict_dataloader() and returns: loader