code: def test_multivariate_normal_tril(self):
      with self.test_session() as sess:
          N, D, w_true, X_train, y_train, X, w, b, y = self._setup()
  
          # INFERENCE. Initialize scales at identity to verify if we
          # learned an approximately zero determinant.
          qw = MultivariateNormalTriL(
              loc=tf.Variable(tf.random_normal([D])),
              scale_tril=tf.Variable(tf.diag(tf.ones(D))),
          )
          qb = MultivariateNormalTriL(
              loc=tf.Variable(tf.random_normal([1])),
              scale_tril=tf.Variable(tf.diag(tf.ones(1))),
          )
  
          inference = ed.Laplace(
              {w: qw, b: qb}, data={X: X_train, y: y_train}
          )
          inference.run(n_iter=100)
  
          self._test(sess, qw, qb, w_true)
  
file_path: edward/tests/inferences/laplace_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import edward
  import numpy
  import tensorflow
  from edward.models import MultivariateNormalDiag, MultivariateNormalTriL, Normal
label_desc: Use image node_id 4 for calling the test_laplace_class obj's underlying member method code with example usage: obj.test_multivariate_normal_tril() without return types