code: def test_multivariate_normal(self):
      mean_p = [0]
      var_p = [[1]]
      kl_equal = _kl.kl_multivariate_normal_distribution(
          mean_p, var_p, mean_p, var_p
      )
      assert kl_equal == 0
      # Compare with univariate implementation
      uv = _kl.kl_normal_distribution(0, 1, 0, 1)
      assert kl_equal == uv
  
      mean_q = [1]
      var_q = [[1]]
      kl_ne = _kl.kl_multivariate_normal_distribution(
          mean_p, var_p, mean_q, var_q
      )
  
      # Compare with univariate implementation
      uv = _kl.kl_normal_distribution(0, 1, 1, 1)
      assert kl_ne == uv
  
file_path: hmmlearn/lib/hmmlearn/tests/test_kl_divergence.py
imports: import numpy
  from hmmlearn import _kl_divergence
label_desc: Use image node_id 3 for calling the TestKLDivergence obj's underlying member method code with example usage: obj.test_multivariate_normal() without return types