code: def test_multi_nifti_masker_generate_report_imgs(
      reports, expected, affine_eye
  ):
      """Smoke test for generate_report method with image data."""
      shape = (9, 9, 5)
      imgs, _ = generate_fake_fmri(shape, affine=affine_eye, length=2)
      masker = MultiNiftiMasker(reports=reports)
      masker.fit([imgs, imgs])
      assert isinstance(masker._reporting_data, expected)
      masker.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 24 for calling a global function with example usage: test_multi_nifti_masker_generate_report_imgs(reports, expected, affine_eye) without return types