code: def train_dataloader(self, *args, **kwargs):
      trainset = torchvision.datasets.CIFAR10(
          root=DATASETS_PATH,
          train=True,
          download=True,
          transform=self.transform,
      )
      return torch.utils.data.DataLoader(
          trainset, batch_size=2, shuffle=True, num_workers=0
      )
  
imports: from os import path
  import torch
  import torchvision
  import torchvision.transforms
  from lightning.pytorch import LightningDataModule, LightningModule, cli_lightning_logo
  from lightning.pytorch.cli import LightningCLI
  from lightning.pytorch.profilers.pytorch import PyTorchProfiler
  from lightning.pytorch.utilities.model_helpers import get_torchvision_model
label_desc: Use image node_id 1 for calling the CIFAR10DataModule obj's underlying member method code with example usage: obj.train_dataloader() and returns: torch