def METHOD_NAME():
    grad = tf.Variable([[0.1]])
    model = tf.keras.Sequential(
        [
            tf.keras.layers.Dense(
                1,
                kernel_initializer=tf.keras.initializers.Constant([[1.0]]),
                use_bias=False,
            )
        ]
    )
    model.build(input_shape=[1, 1])
    opt = Lookahead("adam", sync_period=10, slow_step_size=0.4)
    _ = opt.apply_gradients(list(zip([grad], model.variables)))
    np.testing.assert_allclose(opt.lr.read_value(), 1e-3)
    opt.lr = 1e-4
    np.testing.assert_allclose(opt.lr.read_value(), 1e-4)