Examples with GaussianReconstructionDistribution org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution used on opensource projects

Example 6 with GaussianReconstructionDistribution

use of org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution in project deeplearning4j by deeplearning4j.

the class TestPlayUI method testUI_VAE.

@Test
@Ignore
public void testUI_VAE() throws Exception {
    //Variational autoencoder - for unsupervised layerwise pretraining
    StatsStorage ss = new InMemoryStatsStorage();
    UIServer uiServer = UIServer.getInstance();
    uiServer.attach(ss);
    MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder().optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1).learningRate(1e-5).list().layer(0, new VariationalAutoencoder.Builder().nIn(4).nOut(3).encoderLayerSizes(10, 11).decoderLayerSizes(12, 13).weightInit(WeightInit.XAVIER).pzxActivationFunction("identity").reconstructionDistribution(new GaussianReconstructionDistribution()).activation(Activation.LEAKYRELU).updater(Updater.SGD).build()).layer(1, new VariationalAutoencoder.Builder().nIn(3).nOut(3).encoderLayerSizes(7).decoderLayerSizes(8).weightInit(WeightInit.XAVIER).pzxActivationFunction("identity").reconstructionDistribution(new GaussianReconstructionDistribution()).activation(Activation.LEAKYRELU).updater(Updater.SGD).build()).layer(2, new OutputLayer.Builder().nIn(3).nOut(3).build()).pretrain(true).backprop(true).build();
    MultiLayerNetwork net = new MultiLayerNetwork(conf);
    net.init();
    net.setListeners(new StatsListener(ss), new ScoreIterationListener(1));
    DataSetIterator iter = new IrisDataSetIterator(150, 150);
    for (int i = 0; i < 50; i++) {
        net.fit(iter);
        Thread.sleep(100);
    }
    Thread.sleep(100000);
}