code: def test_sample(means, covs):
      torch.manual_seed(0)
  
      X = Normal(means, covs, covariance_type="full").sample(1)
      assert_array_almost_equal(X, [[2.044038, 1.659515, -0.229191]])
  
      X = Normal(means, covs, covariance_type="full").sample(5)
      assert_array_almost_equal(
          X,
          [
              [1.5113, 0.3447, 0.2308],
              [1.4209, 3.0784, 1.7213],
              [0.9791, 0.8686, 2.0354],
              [0.7308, 3.2258, 1.4744],
              [1.2672, 1.0083, 2.2415],
          ],
          3,
      )
  
imports: import os
  import numpy
  import torch
  import pytest
  from pomegranate.distributions import Normal
  from ._utils import _test_initialization_raises_two_parameters
  from ._utils import _test_initialization
  from ._utils import _test_predictions
  from ._utils import _test_efd_from_summaries
  from ._utils import _test_raises
  from nose.tools import assert_raises
  from numpy.testing import assert_array_almost_equal
label_desc: Use image node_id 10 for calling a global function with example usage: test_sample(means, covs) without return types