code: def test_rich_progress_bar_with_refresh_rate(
      tmp_path,
      refresh_rate,
      train_batches,
      val_batches,
      expected_call_count,
  ):
      model = BoringModel()
      trainer = Trainer(
          default_root_dir=tmp_path,
          num_sanity_val_steps=0,
          limit_train_batches=train_batches,
          limit_val_batches=val_batches,
          max_epochs=1,
          callbacks=RichProgressBar(refresh_rate=refresh_rate),
      )
  
      trainer.progress_bar_callback.on_train_start(trainer, model)
      with mock.patch.object(
          trainer.progress_bar_callback.progress,
          "update",
          wraps=trainer.progress_bar_callback.progress.update,
      ) as progress_update:
          trainer.fit(model)
          assert progress_update.call_count == expected_call_count
  
      if train_batches > 0:
          fit_main_bar = trainer.progress_bar_callback.progress.tasks[0]
          assert fit_main_bar.completed == train_batches
          assert fit_main_bar.total == train_batches
          assert fit_main_bar.visible
      if val_batches > 0:
          fit_val_bar = trainer.progress_bar_callback.progress.tasks[1]
          assert fit_val_bar.completed == val_batches
          assert fit_val_bar.total == val_batches
          assert not fit_val_bar.visible
  
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 10 for calling a global function with example usage: test_rich_progress_bar_with_refresh_rate(tmp_path, refresh_rate, train_batches, val_batches, expected_call_count) without return types