def testZeroLearningRate(self):
    """Tests network produces zero updates with learning rate equal to zero."""
    shape = [10]
    gradients = tf.random_normal(shape)
    net = networks.Adam(learning_rate=0)
    state = net.initial_state_for_inputs(gradients)
    update, _ = net(gradients, state)

    with self.test_session() as sess:
      update_np = sess.run(update)
      self.assertAllEqual(update_np, np.zeros(shape))
Tests network produces zero updates with learning rate equal to zero.
networks_test.py