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)
def eye_color(person): random_variables = {x.name: x for x in ed.random_variables()} if person + '/' in random_variables: return random_variables[person + '/'] else: return Categorical(probs=tf.ones(3) / 3, name=person)