code: def test_verbose_arg(capsys, n_jobs, verbose):
      """Test controlling output with the ``verbose`` argument."""
      from sklearn.svm import SVC
  
      X, y = make_data()
      clf = SVC()
  
      # shows progress bar and prints other messages to the console
      with use_log_level(True):
          for estimator_object in [
              SlidingEstimator,
              GeneralizingEstimator,
          ]:
              estimator = estimator_object(
                  clf, n_jobs=n_jobs, verbose=verbose
              )
              estimator = estimator.fit(X, y)
              estimator.score(X, y)
              estimator.predict(X)
  
              stdout, stderr = capsys.readouterr()
              if isinstance(verbose, bool) and not verbose:
                  assert all(
                      channel == "" for channel in (stdout, stderr)
                  )
              else:
                  assert any(
                      len(channel) > 0 for channel in (stdout, stderr)
                  )
  
file_path: mne-python/mne/decoding/tests/test_search_light.py
imports: import platform
  from inspect import signature
  import numpy
  import pytest
  from numpy.testing import assert_array_equal, assert_equal
  from mne.decoding.search_light import GeneralizingEstimator, SlidingEstimator
  from mne.decoding.transformer import Vectorizer
  from mne.utils import _record_warnings, check_version, use_log_level
label_desc: Use image node_id 4 for calling a global function with example usage: test_verbose_arg(capsys, n_jobs, verbose) without return types