code: def test_fetch_atlas_fsl(
      name,
      label_fname,
      fname,
      is_symm,
      split,
      atlas_data,
      fsl_fetcher,
      tmp_path,
      affine_eye,
  ):
      # Create directory which will contain fake atlas data
      atlas_dir = tmp_path / "fsl" / "data" / "atlases"
      nifti_dir = atlas_dir / name
      nifti_dir.mkdir(parents=True)
      # Write labels and sample atlas image in directory
      _write_sample_atlas_metadata(
          atlas_dir,
          f"{name}{label_fname}",
          is_symm=is_symm,
      )
      target_atlas_nii = nifti_dir / f"{name}-{fname}.nii.gz"
      nibabel.Nifti1Image(atlas_data, affine_eye * 3).to_filename(
          target_atlas_nii
      )
      # Check that the fetch lead to consistent results
      atlas_instance = fsl_fetcher(
          fname,
          data_dir=tmp_path,
          symmetric_split=split,
      )
      _test_atlas_instance_should_match_data(
          atlas_instance,
          is_symm=is_symm or split,
      )
  
      assert atlas_instance.description != ""
  
      # check for typo in label names
      for label in atlas_instance.labels:
          # no extra whitespace
          assert label.strip() == label
  
imports: import itertools
  import os
  import re
  from pathlib import Path
  import nibabel
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_array_equal
  from nilearn._utils import data_gen
  from nilearn._utils.testing import serialize_niimg
  from nilearn.conftest import _rng
  from nilearn.datasets import atlas
  from nilearn.datasets._utils import fetch_files
  from nilearn.datasets.tests._testing import dict_to_archive
  from nilearn.image import get_data
label_desc: Use image node_id 8 for calling a global function with example usage: test_fetch_atlas_fsl(name, label_fname, fname, is_symm, split, atlas_data, fsl_fetcher, tmp_path, affine_eye) without return types