code: def test_multi_gpu_none_backend(tmpdir):
      """Make sure when using multiple GPUs the user can't use `accelerator = None`."""
      seed_everything(42)
      trainer_options = {
          "default_root_dir": tmpdir,
          "enable_progress_bar": False,
          "max_epochs": 1,
          "limit_train_batches": 0.2,
          "limit_val_batches": 0.2,
          "accelerator": "gpu",
          "strategy": "ddp_spawn",
          "devices": 2,
      }
  
      dm = ClassifDataModule()
      model = ClassificationModel()
      tpipes.run_model_test(trainer_options, model, dm)
  
imports: import os
  from collections import namedtuple
  from unittest import mock
  from unittest.mock import patch
  import pytest
  import torch
  from lightning.fabric.plugins.environments import TorchElasticEnvironment
  from lightning.fabric.utilities.device_parser import _parse_gpu_ids
  from lightning.pytorch import Trainer, seed_everything
  from lightning.pytorch.accelerators import CPUAccelerator, CUDAAccelerator
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  import tests_pytorch.helpers.pipelines
  from tests_pytorch.helpers.datamodules import ClassifDataModule
  from tests_pytorch.helpers.runif import RunIf
  from tests_pytorch.helpers.simple_models import ClassificationModel
label_desc: Use image node_id 1 for calling a global function with example usage: test_multi_gpu_none_backend(tmpdir) without return types