code: def test_multi_nifti_masker_generate_report_imgs_and_mask(affine_eye):
      """Smoke test for generate_report method with images and mask."""
      shape = (9, 9, 5)
      imgs, _ = generate_fake_fmri(shape, affine=affine_eye, length=2)
      mask = Nifti1Image(np.ones(shape), affine_eye)
      masker = MultiNiftiMasker(
          mask_img=mask,
          # to test resampling lines with imgs
          target_affine=affine_eye,
          target_shape=shape,
      )
      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 26 for calling a global function with example usage: test_multi_nifti_masker_generate_report_imgs_and_mask(affine_eye) without return types