code: def test_contrast_padding(rng):
      n, p, q = 100, 80, 10
      X, Y = rng.standard_normal(size=(p, q)), rng.standard_normal(
          size=(p, n)
      )
      labels, results = run_glm(Y, X, "ar1")
  
      con_val = [1, 1]
  
      with pytest.warns(
          UserWarning,
          match="The rest of the contrast was padded with zeros.",
      ):
          compute_contrast(labels, results, con_val).z_score()
  
      con_val = np.eye(q)[:3, :3]
      compute_contrast(
          labels, results, con_val, stat_type="F"
      ).z_score()
  
imports: import numpy
  import pytest
  import scipy.stats
  from numpy.testing import assert_almost_equal
  from sklearn.datasets import make_regression
  from sklearn.linear_model import LinearRegression
  from nilearn.glm.contrasts import Contrast, _compute_fixed_effects_params, compute_contrast, compute_fixed_effect_contrast, expression_to_contrast_vector
  from nilearn.glm.first_level import run_glm
label_desc: Use image node_id 19 for calling a global function with example usage: test_contrast_padding(rng) without return types