code: def train_dataloader(self):
      return DataLoader(RandomDataset(32, 2000), batch_size=32)
  
imports: import os
  from functools import partial
  from unittest import mock
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.accelerators import XLAAccelerator
  from lightning.pytorch.callbacks import EarlyStopping
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.strategies import XLAStrategy
  from lightning.pytorch.strategies.launchers.xla import _XLALauncher
  from lightning.pytorch.trainer.connectors.logger_connector.result import _Sync
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from torch.utils.data import DataLoader
  import tests_pytorch.helpers.pipelines
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 1 for calling the SerialLoaderBoringModel obj's underlying member method code with example usage: obj.train_dataloader() and returns: DataLoader