code: def test_tpu_grad_norm(tmpdir):
      """Test if grad_norm works on TPU."""
      trainer_options = {
          "default_root_dir": tmpdir,
          "enable_progress_bar": False,
          "max_epochs": 4,
          "accelerator": "tpu",
          "devices": 1,
          "limit_train_batches": 0.4,
          "limit_val_batches": 0.4,
          "gradient_clip_val": 0.5,
      }
  
      model = BoringModel()
      tpipes.run_model_test(trainer_options, model, with_hpc=False)
  
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 8 for calling a global function with example usage: test_tpu_grad_norm(tmpdir) without return types