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: import base64
  from dataclasses import dataclass
  from io import BytesIO
  from os import path
  from typing import Dict, Optional
  import numpy
  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.serve import ServableModule, ServableModuleValidator
  from lightning.pytorch.utilities.model_helpers import get_torchvision_model
  from PIL import Image
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