code: def test_second_level_input_as_3D_images(rng, affine_eye, tmp_path):
      """Test second level model with a list 3D image filenames as input.
  
      Should act as a regression test for:
      https://github.com/nilearn/nilearn/issues/3636
  
      """
      shape = (7, 8, 9)
      images = []
      nb_subjects = 10
      for _ in range(nb_subjects):
          data = rng.random(shape)
          images.append(Nifti1Image(data, affine_eye))
  
      filenames = testing.write_imgs_to_path(
          *images, file_path=tmp_path, create_files=True
      )
      second_level_input = filenames
      design_matrix = pd.DataFrame(
          [1] * len(second_level_input),
          columns=["intercept"],
      )
  
      second_level_model = SecondLevelModel(smoothing_fwhm=8.0)
      second_level_model = second_level_model.fit(
          second_level_input,
          design_matrix=design_matrix,
      )
  
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 6 for calling a global function with example usage: test_second_level_input_as_3D_images(rng, affine_eye, tmp_path) without return types