code: def test_multiple_loggers_pickle(tmpdir):
      """Verify that pickling trainer with multiple loggers works."""
      logger1 = CustomLogger()
      logger2 = CustomLogger()
  
      trainer = Trainer(logger=[logger1, logger2])
      pkl_bytes = pickle.dumps(trainer)
      trainer2 = pickle.loads(pkl_bytes)
      for logger in trainer2.loggers:
          logger.log_metrics({"acc": 1.0}, 0)
  
      for logger in trainer2.loggers:
          assert logger.metrics_logged == {"acc": 1.0}
  
imports: import pickle
  from argparse import Namespace
  from copy import deepcopy
  from typing import Any, Dict, Optional
  from unittest.mock import patch
  import numpy
  import pytest
  import torch
  from lightning.fabric.utilities.logger import _convert_params, _sanitize_params
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import BoringDataModule, BoringModel
  from lightning.pytorch.loggers import Logger, TensorBoardLogger
  from lightning.pytorch.loggers.logger import DummyExperiment, DummyLogger
  from lightning.pytorch.loggers.utilities import _scan_checkpoints
  from lightning.pytorch.utilities.rank_zero import rank_zero_only
label_desc: Use image node_id 3 for calling a global function with example usage: test_multiple_loggers_pickle(tmpdir) without return types