code: def test_num_stepping_batches_with_tpu_single():
      """Test stepping batches with the single-core TPU strategy."""
      trainer = Trainer(accelerator="tpu", devices=1, max_epochs=1)
      model = BoringModel()
      trainer._data_connector.attach_data(model)
      assert isinstance(trainer.strategy, SingleDeviceXLAStrategy)
      trainer.strategy.connect(model)
      expected = len(model.train_dataloader())
      assert trainer.estimated_stepping_batches == expected
  
imports: import logging
  import os
  from unittest import mock
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomIterableDataset
  from lightning.pytorch.strategies import SingleDeviceXLAStrategy
  from torch.utils.data import DataLoader
  from tests_pytorch.conftest import mock_cuda_count
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 8 for calling a global function with example usage: test_num_stepping_batches_with_tpu_single() without return types