code: def test_nifti_masker_empty_mask_warning(affine_eye):
      X = Nifti1Image(np.ones((2, 2, 2, 5)), affine_eye)
      with pytest.raises(
          ValueError,
          match="The mask is invalid as it is empty: it masks all data",
      ):
          NiftiMasker(mask_strategy="epi").fit_transform(X)
  
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 16 for calling a global function with example usage: test_nifti_masker_empty_mask_warning(affine_eye) without return types