code: def test_unmask_list(rng, affine_eye):
      shape = (3, 4, 5)
      mask_data = rng.uniform(size=shape) < 0.5
      mask_img = Nifti1Image(mask_data.astype(np.uint8), affine_eye)
      a = unmask(mask_data[mask_data], mask_img)
      b = unmask(
          mask_data[mask_data].tolist(), mask_img
      )  # shouldn't crash
      assert_array_equal(get_data(a), get_data(b))
  
imports: import warnings
  import numpy
  import pytest
  from nibabel import Nifti1Image
  from numpy.testing import assert_array_equal
  from sklearn.preprocessing import StandardScaler
  from nilearn import masking
  from nilearn._utils import data_gen
  from nilearn._utils.exceptions import DimensionError
  from nilearn._utils.testing import write_imgs_to_path
  from nilearn.conftest import _rng
  from nilearn.image import get_data, high_variance_confounds
  from nilearn.maskers import NiftiMasker
  from nilearn.masking import _MaskWarning, _unmask_3d, _unmask_4d, compute_background_mask, compute_brain_mask, compute_epi_mask, compute_multi_brain_mask, compute_multi_epi_mask, extrapolate_out_mask, intersect_masks, unmask, unmask_from_to_3d_array
label_desc: Use image node_id 17 for calling a global function with example usage: test_unmask_list(rng, affine_eye) without return types