code: def _check_effect_maps(effect_maps, design_matrix):
      if len(effect_maps) != design_matrix.shape[0]:
          raise ValueError(
              "design_matrix does not match the number of maps considered. "
              f"{design_matrix.shape[0]} rows in design matrix do not match "
              f"with {len(effect_maps)} maps."
          )
  
imports: import sys
  import time
  from warnings import warn
  import numpy
  import pandas
  from joblib import Memory
  from nibabel import Nifti1Image
  from sklearn.base import clone
  from nilearn._utils import fill_doc, stringify_path
  from nilearn._utils.niimg_conversions import check_niimg
  from nilearn.glm._base import BaseGLM
  from nilearn.glm.contrasts import compute_contrast, expression_to_contrast_vector
  from nilearn.glm.first_level import FirstLevelModel, run_glm
  from nilearn.glm.first_level.design_matrix import make_second_level_design_matrix
  from nilearn.glm.regression import RegressionResults, SimpleRegressionResults
  from nilearn.image import mean_img
  from nilearn.maskers import NiftiMasker
  from nilearn.mass_univariate import permuted_ols
label_desc: Use image node_id 14 for calling a global function with example usage: _check_effect_maps(effect_maps, design_matrix) without return types