code: def test_copy_parent_rvs(self):
      with self.test_session() as sess:
          x = Normal(0.0, 1.0)
          y = tf.constant(3.0)
          z = x * y
          z_new = ed.copy(
              z, scope="no_copy_parent_rvs", copy_parent_rvs=False
          )
          self.assertEqual(len(ed.random_variables()), 1)
          z_new = ed.copy(
              z, scope="copy_parent_rvs", copy_parent_rvs=True
          )
          self.assertEqual(len(ed.random_variables()), 2)
  
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 Bernoulli, Categorical, Mixture, Normal
label_desc: Use image node_id 4 for calling the test_copy_class obj's underlying member method code with example usage: obj.test_copy_parent_rvs() without return types