docstr: The val dataloader 
docstr_tok: ["The","val","dataloader"]
code: def val_dataloader(
      self, *args: Any, **kwargs: Any
  ) -> Union[DataLoader, List[DataLoader]]:
      """The val dataloader"""
      return self._data_loader(
          self.dataset_val, batch_size=self.batch_size_eval
      )
  
imports: from itertools import chain
  from pathlib import Path
  import pickle
  from typing import Any, List, Union
  import subprocess
  import mmap
  from multiprocessing.shared_memory import SharedMemory
  import numpy
  import torch
  from torch.utils.data.dataloader import DataLoader, Dataset
  from transformers import AutoTokenizer
  from datasets import load_dataset
  from pytorch_lightning import LightningDataModule
  from src.datamodules.datasets.lm_dataset import LMDataset
  from src.datamodules.fault_tolerant_sampler import RandomFaultTolerantSampler
  from src.datamodules.fault_tolerant_sampler import FaultTolerantDistributedSampler
  from src.datamodules.datasets.detokenizer import DATASET_TOKENIZATION_REGISTRY
  from src.utils.utils import get_logger
label_desc: Use image node_id 9 for calling the LMDataModule obj's underlying member method code with example usage: obj.val_dataloader() and returns: self