code: def test_strategy_pickle():
      strategy = SingleDeviceStrategy("cpu")
      optimizer = MockOptimizer()
  
      strategy.optimizers = [optimizer]
      assert isinstance(strategy.optimizers[0], MockOptimizer)
      assert isinstance(
          strategy._lightning_optimizers[0], LightningOptimizer
      )
  
      state = pickle.dumps(strategy)
      # dumping did not get rid of the lightning optimizers
      assert isinstance(
          strategy._lightning_optimizers[0], LightningOptimizer
      )
      strategy_reloaded = pickle.loads(state)
      # loading restores the lightning optimizers
      assert isinstance(
          strategy_reloaded._lightning_optimizers[0], LightningOptimizer
      )
  
imports: import pickle
  from unittest.mock import MagicMock, Mock
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.core.optimizer import LightningOptimizer
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.strategies import SingleDeviceStrategy
  from torch.utils.data import DataLoader
  from tests_pytorch.helpers.dataloaders import CustomNotImplementedErrorDataloader
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 3 for calling a global function with example usage: test_strategy_pickle() without return types