code: def test_non_parametric_inference_with_flm_objects():
      """See https://github.com/nilearn/nilearn/issues/3579 ."""
      shapes, rk = [(7, 8, 9, 15)], 3
      (
          mask,
          fmri_data,
          design_matrices,
      ) = generate_fake_fmri_data_and_design(shapes, rk)
  
      masker = NiftiMasker(mask)
      masker.fit()
      single_run_model = FirstLevelModel(mask_img=masker).fit(
          fmri_data[0], design_matrices=design_matrices[0]
      )
      single_run_model.compute_contrast("x")
  
      second_level_input = [single_run_model, single_run_model]
  
      design_matrix = pd.DataFrame(
          [1] * len(second_level_input),
          columns=["intercept"],
      )
  
      non_parametric_inference(
          second_level_input=second_level_input,
          design_matrix=design_matrix,
          first_level_contrast="x",
          n_perm=N_PERM,
      )
  
imports: import os
  from pathlib import Path
  import numpy
  import pandas
  import pytest
  from nibabel import Nifti1Image, load
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from scipy import stats
  from nilearn._utils import testing
  from nilearn._utils.data_gen import generate_fake_fmri_data_and_design, write_fake_bold_img, write_fake_fmri_data_and_design
  from nilearn.glm.first_level import FirstLevelModel, run_glm
  from nilearn.glm.second_level import SecondLevelModel, non_parametric_inference
  from nilearn.glm.second_level.second_level import _check_confounds, _check_design_matrix, _check_effect_maps, _check_first_level_contrast, _check_input_as_first_level_model, _check_output_type, _check_second_level_input, _infer_effect_maps, _process_second_level_input_as_dataframe, _process_second_level_input_as_firstlevelmodels, _sort_input_dataframe
  from nilearn.image import concat_imgs, get_data, new_img_like, smooth_img
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 3 for calling a global function with example usage: test_non_parametric_inference_with_flm_objects() without return types