def testNonTrainable(self):
    """Tests the network doesn't contain trainable variables."""
    shape = [10, 5]
    gradients = tf.random_normal(shape)
    net = networks.Adam()
    state = net.initial_state_for_inputs(gradients)
    net(gradients, state)
    variables = snt.get_variables_in_module(net)
    self.assertEqual(len(variables), 0)
Tests the network doesn't contain trainable variables.
networks_test.py