code: def test_multi_nifti_maps_masker_report_warning(affine_eye):
      """Test calling generate report on multiple subjects raises warning."""
      shape = (13, 11, 12)
      n_regions = 9
      length = 3
  
      maps_img, _ = generate_maps(shape, n_regions, affine=affine_eye)
      imgs, _ = generate_fake_fmri(
          shape, affine=affine_eye, length=length
      )
  
      masker = MultiNiftiMapsMasker(maps_img)
  
      with pytest.warns(
          UserWarning,
          match="A list of 4D subject images were provided to fit. ",
      ):
          masker.fit([imgs, imgs]).generate_report()
  
imports: from collections import Counter
  import numpy
  import pytest
  from nibabel import Nifti1Image
  from numpy.testing import assert_almost_equal
  from nilearn._utils.data_gen import generate_fake_fmri, generate_labeled_regions, generate_maps, generate_random_img
  from nilearn.image import get_data, new_img_like
  from nilearn.maskers import MultiNiftiLabelsMasker, MultiNiftiMapsMasker, MultiNiftiMasker, NiftiLabelsMasker, NiftiMapsMasker, NiftiMasker, NiftiSpheresMasker
label_desc: Use image node_id 29 for calling a global function with example usage: test_multi_nifti_maps_masker_report_warning(affine_eye) without return types