code: def test_optimizer_step_calls_mark_step():
      plugin = XLAPrecision(precision="32-true")
      optimizer = Mock()
      with mock.patch("torch_xla.core.xla_model") as xm_mock:
          plugin.optimizer_step(
              optimizer=optimizer, model=Mock(), closure=Mock()
          )
      optimizer.step.assert_called_once()
      xm_mock.mark_step.assert_called_once()
  
file_path: pytorch-lightning/tests/tests_pytorch/plugins/precision/test_xla.py
imports: import os
  import re
  from unittest import mock
  from unittest.mock import Mock
  import pytest
  import torch
  from lightning.pytorch.plugins import XLAPrecision
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 1 for calling a global function with example usage: test_optimizer_step_calls_mark_step() without return types