code: def input_parameters(masker_class, data_img_3d, affine_eye):
      n_regions = 9
      shape = (13, 11, 12)
      labels = ["background"]
      labels += [f"region_{i}" for i in range(1, n_regions + 1)]
      if masker_class in (NiftiMasker, MultiNiftiMasker):
          return {"mask_img": data_img_3d}
      if masker_class in (NiftiLabelsMasker, MultiNiftiLabelsMasker):
          labels_img = generate_labeled_regions(
              shape, n_regions=n_regions, affine=affine_eye
          )
          return {"labels_img": labels_img, "labels": labels}
      if masker_class in (NiftiMapsMasker, MultiNiftiMapsMasker):
          label_img, _ = generate_maps(
              shape, n_regions=n_regions, affine=affine_eye
          )
          return {"maps_img": label_img}
      if masker_class is NiftiSpheresMasker:
          return {"seeds": [(1, 1, 1)]}
  
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 5 for calling a global function with example usage: input_parameters(masker_class, data_img_3d, affine_eye) and returns: dict, dict, dict, dict