code: def test_dict_learning_check_values_epoch_argument_smoke(
      mask_img, n_epochs
  ):
      """Smoke test to check different values of the epoch argument."""
      data, components, _ = _make_canica_test_data()
  
      masker = NiftiMasker(mask_img=mask_img).fit()
      mask = get_data(mask_img) != 0
      flat_mask = mask.ravel()
      dict_init = masker.inverse_transform(components[:, flat_mask])
  
      dict_learning = DictLearning(
          n_components=4,
          random_state=0,
          dict_init=dict_init,
          mask=mask_img,
          smoothing_fwhm=0.0,
          n_epochs=n_epochs,
          alpha=1,
      )
      dict_learning.fit(data)
  
imports: import numpy
  import pytest
  from nibabel import Nifti1Image
  from nilearn._utils.testing import write_imgs_to_path
  from nilearn.conftest import _affine_eye
  from nilearn.decomposition.dict_learning import DictLearning
  from nilearn.decomposition.tests.test_canica import _make_canica_test_data
  from nilearn.image import get_data, iter_img
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 3 for calling a global function with example usage: test_dict_learning_check_values_epoch_argument_smoke(mask_img, n_epochs) without return types