code: def val_dataloader(self):
      if self.val_batch_size is not None:
          batch_size = self.val_batch_size
      else:
          batch_size = self.batch_size
  
      return DataLoader(
          self.eval_dataset,
          batch_size=batch_size,
          num_workers=self.workers,
          pin_memory=self.pin_memory,
      )
  
file_path: NeuralCompression/projects/illm/open_images_datamodule.py
imports: import logging
  from pathlib import Path
  from typing import Callable, List, Optional
  from default_transforms import default_train_transform, default_val_transform
  from lightning.pytorch import LightningDataModule
  from PIL.Image import Image
  from torch import Tensor
  from torch.utils.data import DataLoader
  from neuralcompression.data import OpenImagesV6
label_desc: Use image node_id 4 for calling the OpenImagesDataModule obj's underlying member method code with example usage: obj.val_dataloader() and returns: DataLoader