code: def test_multiple_fast_inv(rng):
      shape = (10, 20, 20)
      X = rng.standard_normal(size=shape)
      X_inv_ref = np.zeros(shape)
      for i in range(shape[0]):
          X[i] = np.dot(X[i], X[i].T)
          X_inv_ref[i] = spl.inv(X[i])
      X_inv = multiple_fast_inverse(X)
  
      assert_almost_equal(X_inv_ref, X_inv)
  
imports: import numpy
  import pytest
  import scipy.linalg
  import scipy.stats
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from scipy.stats import norm
  from nilearn._utils.data_gen import generate_fake_fmri
  from nilearn.glm._utils import full_rank, multiple_fast_inverse, multiple_mahalanobis, pad_contrast, positive_reciprocal, z_score
  from nilearn.glm.first_level import FirstLevelModel, make_first_level_design_matrix
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 8 for calling a global function with example usage: test_multiple_fast_inv(rng) without return types