code: def xla_launch(fn):
      # TODO: the accelerator should be optional to just launch processes, but this requires lazy initialization
      accelerator = XLAAccelerator()
      strategy = XLAStrategy(
          accelerator=accelerator,
          parallel_devices=XLAAccelerator.get_parallel_devices(
              XLAAccelerator.auto_device_count()
          ),
      )
      launcher = _XLALauncher(strategy=strategy)
      wrapped = partial(wrap_launch_function, fn, strategy)
      return launcher.launch(wrapped, strategy)
  
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 16 for calling a global function with example usage: xla_launch(fn) and returns: launcher