Examples with InMemoryStatsStorage org.deeplearning4j.ui.storage.InMemoryStatsStorage used on opensource projects

Example 1 with InMemoryStatsStorage

use of org.deeplearning4j.ui.storage.InMemoryStatsStorage in project deeplearning4j by deeplearning4j.

the class TestPlayUI method testUIMultipleSessions.

@Test
@Ignore
public void testUIMultipleSessions() throws Exception {
    for (int session = 0; session < 3; session++) {
        StatsStorage ss = new InMemoryStatsStorage();
        UIServer uiServer = UIServer.getInstance();
        uiServer.attach(ss);
        MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder().optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1).list().layer(0, new DenseLayer.Builder().activation(Activation.TANH).nIn(4).nOut(4).build()).layer(1, new OutputLayer.Builder().lossFunction(LossFunctions.LossFunction.MCXENT).activation(Activation.SOFTMAX).nIn(4).nOut(3).build()).pretrain(false).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 < 20; i++) {
            net.fit(iter);
            Thread.sleep(100);
        }
    }
    Thread.sleep(1000000);
}

Example 2 with InMemoryStatsStorage

use of org.deeplearning4j.ui.storage.InMemoryStatsStorage in project deeplearning4j by deeplearning4j.

the class TestPlayUI method testUI_RBM.

@Test
@Ignore
public void testUI_RBM() throws Exception {
    //RBM - 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 RBM.Builder().nIn(4).nOut(3).build()).layer(1, new RBM.Builder().nIn(3).nOut(3).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);
}

Example 3 with InMemoryStatsStorage

use of org.deeplearning4j.ui.storage.InMemoryStatsStorage in project deeplearning4j by deeplearning4j.

the class TestParallelEarlyStoppingUI method testParallelStatsListenerCompatibility.

@Test
//To be run manually
@Ignore
public void testParallelStatsListenerCompatibility() throws Exception {
    UIServer uiServer = UIServer.getInstance();
    MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder().optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1).updater(Updater.SGD).weightInit(WeightInit.XAVIER).list().layer(0, new DenseLayer.Builder().nIn(4).nOut(3).build()).layer(1, new OutputLayer.Builder().nIn(3).nOut(3).lossFunction(LossFunctions.LossFunction.MCXENT).build()).pretrain(false).backprop(true).build();
    MultiLayerNetwork net = new MultiLayerNetwork(conf);
    // it's important that the UI can report results from parallel training
    // there's potential for StatsListener to fail if certain properties aren't set in the model
    StatsStorage statsStorage = new InMemoryStatsStorage();
    net.setListeners(new StatsListener(statsStorage));
    uiServer.attach(statsStorage);
    DataSetIterator irisIter = new IrisDataSetIterator(50, 500);
    EarlyStoppingModelSaver<MultiLayerNetwork> saver = new InMemoryModelSaver<>();
    EarlyStoppingConfiguration<MultiLayerNetwork> esConf = new EarlyStoppingConfiguration.Builder<MultiLayerNetwork>().epochTerminationConditions(new MaxEpochsTerminationCondition(500)).scoreCalculator(new DataSetLossCalculator(irisIter, true)).evaluateEveryNEpochs(2).modelSaver(saver).build();
    IEarlyStoppingTrainer<MultiLayerNetwork> trainer = new EarlyStoppingParallelTrainer<>(esConf, net, irisIter, null, 3, 6, 2);
    EarlyStoppingResult<MultiLayerNetwork> result = trainer.fit();
    System.out.println(result);
    assertEquals(EarlyStoppingResult.TerminationReason.EpochTerminationCondition, result.getTerminationReason());
}

Example 4 with InMemoryStatsStorage

use of org.deeplearning4j.ui.storage.InMemoryStatsStorage in project deeplearning4j by deeplearning4j.

the class TestPlayUI method testUI.

@Test
@Ignore
public void testUI() throws Exception {
    StatsStorage ss = new InMemoryStatsStorage();
    PlayUIServer uiServer = (PlayUIServer) UIServer.getInstance();
    assertEquals(9000, uiServer.getPort());
    uiServer.stop();
    PlayUIServer playUIServer = new PlayUIServer();
    playUIServer.runMain(new String[] { "--uiPort", "9100", "-r", "true" });
    assertEquals(9100, playUIServer.getPort());
    playUIServer.stop();
    //        uiServer.attach(ss);
    //
    //        MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
    //                .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1)
    //                .list()
    //                .layer(0, new DenseLayer.Builder().activation(Activation.TANH).nIn(4).nOut(4).build())
    //                .layer(1, new OutputLayer.Builder().lossFunction(LossFunctions.LossFunction.MCXENT).activation(Activation.SOFTMAX).nIn(4).nOut(3).build())
    //                .pretrain(false).backprop(true).build();
    //
    //        MultiLayerNetwork net = new MultiLayerNetwork(conf);
    //        net.init();
    //        net.setListeners(new StatsListener(ss, 3), new ScoreIterationListener(1));
    //
    //        DataSetIterator iter = new IrisDataSetIterator(150, 150);
    //
    //        for (int i = 0; i < 500; i++) {
    //            net.fit(iter);
    ////            Thread.sleep(100);
    //            Thread.sleep(100);
    //        }
    //
    ////        uiServer.stop();
    Thread.sleep(100000);
}

Example 5 with InMemoryStatsStorage

use of org.deeplearning4j.ui.storage.InMemoryStatsStorage in project deeplearning4j by deeplearning4j.

the class TestPlayUI method testUICompGraph.

@Test
@Ignore
public void testUICompGraph() throws Exception {
    StatsStorage ss = new InMemoryStatsStorage();
    UIServer uiServer = UIServer.getInstance();
    uiServer.attach(ss);
    ComputationGraphConfiguration conf = new NeuralNetConfiguration.Builder().graphBuilder().addInputs("in").addLayer("L0", new DenseLayer.Builder().activation(Activation.TANH).nIn(4).nOut(4).build(), "in").addLayer("L1", new OutputLayer.Builder().lossFunction(LossFunctions.LossFunction.MCXENT).activation(Activation.SOFTMAX).nIn(4).nOut(3).build(), "L0").pretrain(false).backprop(true).setOutputs("L1").build();
    ComputationGraph net = new ComputationGraph(conf);
    net.init();
    net.setListeners(new StatsListener(ss), new ScoreIterationListener(1));
    DataSetIterator iter = new IrisDataSetIterator(150, 150);
    for (int i = 0; i < 100; i++) {
        net.fit(iter);
        Thread.sleep(100);
    }
    Thread.sleep(100000);
}