test_autoencoder.py 文件源码

def test_monitor_ae():
    """Test the monitor keyword."""
    # Use the iris features.
    X = iris.data
    X = MinMaxScaler().fit_transform(X)

    ae = Autoencoder(hidden_units=(3, 2,),
                     n_epochs=7500,
                     random_state=4556,
                     learning_rate=DEFAULT_LEARNING_RATE,
                     keep_prob=1.0,
                     hidden_activation=tf.nn.sigmoid,
                     encoding_activation=tf.nn.sigmoid,
                     output_activation=tf.nn.sigmoid)

    def _monitor(epoch, est, stats):
        assert epoch <= 1000, "The autoencoder has been running too long!"
        if stats['loss'] < 0.2:
            assert epoch > 10, "The autoencoder returned too soon!"
            return True
        else:
            return False
    ae.fit(X, monitor=_monitor)