org.nd4j.linalg.learning.config.Nadam Java Examples

The following examples show how to use org.nd4j.linalg.learning.config.Nadam. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.

Example #1

Source File: NadamSpace.java From deeplearning4j with Apache License 2.0

6 votes

@Override
public IUpdater getValue(double[] parameterValues) {
    double lr = learningRate == null ? Nadam.DEFAULT_NADAM_LEARNING_RATE : learningRate.getValue(parameterValues);
    ISchedule lrS = learningRateSchedule == null ? null : learningRateSchedule.getValue(parameterValues);
    double b1 = beta1 == null ? Nadam.DEFAULT_NADAM_LEARNING_RATE : beta1.getValue(parameterValues);
    double b2 = beta2 == null ? Nadam.DEFAULT_NADAM_LEARNING_RATE : beta2.getValue(parameterValues);
    double eps = epsilon == null ? Nadam.DEFAULT_NADAM_LEARNING_RATE : epsilon.getValue(parameterValues);
    if(lrS == null){
        return new Nadam(lr, b1, b2, eps);
    } else {
        Nadam a = new Nadam(lrS);
        a.setBeta1(b1);
        a.setBeta2(b2);
        a.setEpsilon(eps);
        return a;
    }
}

Example #2

Source File: NadamLearnerTestCase.java From jstarcraft-ai with Apache License 2.0

5 votes

@Override
protected GradientUpdater<?> getOldFunction(long[] shape) {
    Nadam configuration = new Nadam();
    GradientUpdater<?> oldFunction = new NadamUpdater(configuration);
    int length = (int) (shape[0] * configuration.stateSize(shape[1]));
    INDArray view = Nd4j.zeros(length);
    oldFunction.setStateViewArray(view, shape, 'c', true);
    return oldFunction;
}

Example #3

Source File: NadamUpdater.java From nd4j with Apache License 2.0

4 votes

public NadamUpdater(Nadam config) {
    this.config = config;
}

Example #4

Source File: NadamUpdater.java From deeplearning4j with Apache License 2.0

4 votes

public NadamUpdater(Nadam config) {
    this.config = config;
}

Example #5

Source File: TestKryo.java From deeplearning4j with Apache License 2.0

4 votes

@Test
public void testSerializationConfigurations() {

    SerializerInstance si = sc.env().serializer().newInstance();

    //Check network configurations:
    Map<Integer, Double> m = new HashMap<>();
    m.put(0, 0.5);
    m.put(10, 0.1);
    MultiLayerConfiguration mlc = new NeuralNetConfiguration.Builder()
                    .updater(new Nadam(new MapSchedule(ScheduleType.ITERATION,m))).list().layer(0, new OutputLayer.Builder().nIn(10).nOut(10).build())
                    .build();

    testSerialization(mlc, si);


    ComputationGraphConfiguration cgc = new NeuralNetConfiguration.Builder()
                    .dist(new UniformDistribution(-1, 1))
                    .updater(new Adam(new MapSchedule(ScheduleType.ITERATION,m)))
                    .graphBuilder()
                    .addInputs("in").addLayer("out", new OutputLayer.Builder().nIn(10).nOut(10).build(), "in")
                    .setOutputs("out").build();

    testSerialization(cgc, si);


    //Check main layers:
    Layer[] layers = new Layer[] {new OutputLayer.Builder().nIn(10).nOut(10).build(),
                    new RnnOutputLayer.Builder().nIn(10).nOut(10).build(), new LossLayer.Builder().build(),
                    new CenterLossOutputLayer.Builder().nIn(10).nOut(10).build(),
                    new DenseLayer.Builder().nIn(10).nOut(10).build(),
                    new ConvolutionLayer.Builder().nIn(10).nOut(10).build(), new SubsamplingLayer.Builder().build(),
                    new Convolution1DLayer.Builder(2, 2).nIn(10).nOut(10).build(),
                    new ActivationLayer.Builder().activation(Activation.TANH).build(),
                    new GlobalPoolingLayer.Builder().build(), new GravesLSTM.Builder().nIn(10).nOut(10).build(),
                    new LSTM.Builder().nIn(10).nOut(10).build(), new DropoutLayer.Builder(0.5).build(),
                    new BatchNormalization.Builder().build(), new LocalResponseNormalization.Builder().build()};

    for (Layer l : layers) {
        testSerialization(l, si);
    }

    //Check graph vertices
    GraphVertex[] vertices = new GraphVertex[] {new ElementWiseVertex(ElementWiseVertex.Op.Add),
                    new L2NormalizeVertex(), new LayerVertex(null, null), new MergeVertex(), new PoolHelperVertex(),
                    new PreprocessorVertex(new CnnToFeedForwardPreProcessor(28, 28, 1)),
                    new ReshapeVertex(new int[] {1, 1}), new ScaleVertex(1.0), new ShiftVertex(1.0),
                    new SubsetVertex(1, 1), new UnstackVertex(0, 2), new DuplicateToTimeSeriesVertex("in1"),
                    new LastTimeStepVertex("in1")};

    for (GraphVertex gv : vertices) {
        testSerialization(gv, si);
    }
}