class_docstr: DeepChem Lightning Dataset Module to be used with the DCLightningModule and a Lightning trainer.
  
  This module wraps over the the deepchem pytorch dataset and dataloader providing a generic interface to run training.
  https://pytorch-lightning.readthedocs.io/en/stable/extensions/datamodules.html
  
  Notes
  -----
  This class requires PyTorch to be installed.
docstr: Returns the train dataloader from train dataset.
  
  Returns
  -------
  dataloader: train dataloader to be used with DCLightningModule.
code: def train_dataloader(self):
      """Returns the train dataloader from train dataset.
  
      Returns
      -------
      dataloader: train dataloader to be used with DCLightningModule.
      """
      dataloader = torch.utils.data.DataLoader(
          self.train_dataset,
          batch_size=None,
          collate_fn=self.collate_fn,
          shuffle=False,
          num_workers=self.num_workers,
      )
      return dataloader
  
file_path: deepchem/deepchem/models/lightning/dc_lightning_dataset_module.py
imports: from typing import Callable
  import deepchem
  import lightning
  import torch
label_desc: Use image node_id 3 for calling the DCLightningDatasetModule obj's underlying member method code with example usage: obj.train_dataloader() and returns: dataloader