Example usage for org.deeplearning4j.nn.multilayer MultiLayerNetwork getUpdater

Introduction

In this page you can find the example usage for org.deeplearning4j.nn.multilayer MultiLayerNetwork getUpdater.

Prototype

public Updater getUpdater() 

Source Link

Document

Get the updater for this MultiLayerNetwork

Usage

From source file:org.audiveris.omr.classifier.ModelSystemSerializer.java

License:Open Source License

/**
 * Load a multi layer network from a file system
 *
 * @param root        the root path of file system
 * @param loadUpdater true for loading updater
 * @return the loaded multi layer network
 * @throws IOException/*ww w  .  ja  v a 2  s.c  om*/
 */
public static MultiLayerNetwork restoreMultiLayerNetwork(Path root, boolean loadUpdater) throws IOException {
    boolean gotConfig = false;
    boolean gotCoefficients = false;
    boolean gotOldUpdater = false;
    boolean gotUpdaterState = false;
    boolean gotPreProcessor = false;

    String json = "";
    INDArray params = null;
    Updater updater = null;
    INDArray updaterState = null;
    DataSetPreProcessor preProcessor = null;

    final Path config = root.resolve("configuration.json");

    if (Files.exists(config)) {
        //restoring configuration
        InputStream stream = Files.newInputStream(config);
        BufferedReader reader = new BufferedReader(new InputStreamReader(stream));
        String line = "";
        StringBuilder js = new StringBuilder();

        while ((line = reader.readLine()) != null) {
            js.append(line).append("\n");
        }

        json = js.toString();

        reader.close();
        stream.close();
        gotConfig = true;
    }

    final Path coefficients = root.resolve("coefficients.bin");

    if (Files.exists(coefficients)) {
        InputStream stream = Files.newInputStream(coefficients);
        DataInputStream dis = new DataInputStream(new BufferedInputStream(stream));
        params = Nd4j.read(dis);

        dis.close();
        gotCoefficients = true;
    }

    if (loadUpdater) {
        //This can be removed a few releases after 0.4.1...
        final Path oldUpdaters = root.resolve(OLD_UPDATER_BIN);

        if (Files.exists(oldUpdaters)) {
            InputStream stream = Files.newInputStream(oldUpdaters);
            ObjectInputStream ois = new ObjectInputStream(stream);

            try {
                updater = (Updater) ois.readObject();
            } catch (ClassNotFoundException e) {
                throw new RuntimeException(e);
            }

            gotOldUpdater = true;
        }

        final Path updaterStateEntry = root.resolve(UPDATER_BIN);

        if (updaterStateEntry != null) {
            InputStream stream = Files.newInputStream(updaterStateEntry);
            DataInputStream dis = new DataInputStream(stream);
            updaterState = Nd4j.read(dis);

            dis.close();
            gotUpdaterState = true;
        }
    }

    final Path prep = root.resolve("preprocessor.bin");

    if (Files.exists(prep)) {
        InputStream stream = Files.newInputStream(prep);
        ObjectInputStream ois = new ObjectInputStream(stream);

        try {
            preProcessor = (DataSetPreProcessor) ois.readObject();
        } catch (ClassNotFoundException e) {
            throw new RuntimeException(e);
        }

        gotPreProcessor = true;
    }

    if (gotConfig && gotCoefficients) {
        MultiLayerConfiguration confFromJson = MultiLayerConfiguration.fromJson(json);
        MultiLayerNetwork network = new MultiLayerNetwork(confFromJson);
        network.init(params, false);

        if (gotUpdaterState && (updaterState != null)) {
            network.getUpdater().setStateViewArray(network, updaterState, false);
        } else if (gotOldUpdater && (updater != null)) {
            network.setUpdater(updater);
        }

        return network;
    } else {
        throw new IllegalStateException("Model wasn't found within file: gotConfig: [" + gotConfig
                + "], gotCoefficients: [" + gotCoefficients + "], gotUpdater: [" + gotUpdaterState + "]");
    }
}

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From source file:org.knime.ext.dl4j.base.nodes.learn.AbstractDLLearnerNodeModel.java

License:Open Source License

/**
 * Attempts to transfer the {@link Updater} from one {@link MultiLayerNetwork} to another. This is important if you
 * want to further train a pretrained net as some {@link Updater}s contain a history of gradients from training.
 *
 * @param from the network to get the updater from
 * @param to the network to transfer the updater to
 *///from   w ww.  j  a v  a2 s . co m
protected void transferUpdater(final MultiLayerNetwork from, final MultiLayerNetwork to) {
    final org.deeplearning4j.nn.api.Updater updater = from.getUpdater();

    if (updater == null) {
        logger.warn("Could not transfer updater between nets as there is no updater set in the source net");
    } else {
        to.setUpdater(updater);
        logger.info("Successfully transfered updater between nets.");
    }
}

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