code: def test_rich_progress_bar_can_be_pickled():
      bar = RichProgressBar()
      trainer = Trainer(
          callbacks=[bar],
          max_epochs=1,
          limit_train_batches=1,
          limit_val_batches=1,
          limit_test_batches=1,
          limit_predict_batches=1,
          logger=False,
          enable_model_summary=False,
      )
      model = BoringModel()
      pickle.dumps(bar)
      trainer.fit(model)
      pickle.dumps(bar)
      trainer.validate(model)
      pickle.dumps(bar)
      trainer.test(model)
      pickle.dumps(bar)
      trainer.predict(model)
      pickle.dumps(bar)
  
imports: import pickle
  from collections import defaultdict
  from unittest import mock
  from unittest.mock import DEFAULT, Mock
  import pytest
  from lightning.pytorch import Trainer
  from lightning.pytorch.callbacks import ProgressBar, RichProgressBar
  from lightning.pytorch.callbacks.progress.rich_progress import RichProgressBarTheme
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset, RandomIterableDataset
  from lightning.pytorch.loggers import CSVLogger
  from lightning.pytorch.loggers.logger import DummyLogger
  from tests_pytorch.helpers.runif import RunIf
  from torch.utils.data import DataLoader
label_desc: Use image node_id 18 for calling a global function with example usage: test_rich_progress_bar_can_be_pickled() without return types