Search in sources :

Example 6 with UIServer

use of org.deeplearning4j.ui.api.UIServer 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);
}
Also used : InMemoryStatsStorage(org.deeplearning4j.ui.storage.InMemoryStatsStorage) StatsStorage(org.deeplearning4j.api.storage.StatsStorage) InMemoryStatsStorage(org.deeplearning4j.ui.storage.InMemoryStatsStorage) IrisDataSetIterator(org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator) UIServer(org.deeplearning4j.ui.api.UIServer) ComputationGraphConfiguration(org.deeplearning4j.nn.conf.ComputationGraphConfiguration) ComputationGraph(org.deeplearning4j.nn.graph.ComputationGraph) StatsListener(org.deeplearning4j.ui.stats.StatsListener) ScoreIterationListener(org.deeplearning4j.optimize.listeners.ScoreIterationListener) IrisDataSetIterator(org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator) DataSetIterator(org.nd4j.linalg.dataset.api.iterator.DataSetIterator) Ignore(org.junit.Ignore) Test(org.junit.Test)

Example 7 with UIServer

use of org.deeplearning4j.ui.api.UIServer 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);
}
Also used : OutputLayer(org.deeplearning4j.nn.conf.layers.OutputLayer) InMemoryStatsStorage(org.deeplearning4j.ui.storage.InMemoryStatsStorage) StatsStorage(org.deeplearning4j.api.storage.StatsStorage) IrisDataSetIterator(org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator) UIServer(org.deeplearning4j.ui.api.UIServer) VariationalAutoencoder(org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder) StatsListener(org.deeplearning4j.ui.stats.StatsListener) GaussianReconstructionDistribution(org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution) InMemoryStatsStorage(org.deeplearning4j.ui.storage.InMemoryStatsStorage) MultiLayerConfiguration(org.deeplearning4j.nn.conf.MultiLayerConfiguration) MultiLayerNetwork(org.deeplearning4j.nn.multilayer.MultiLayerNetwork) ScoreIterationListener(org.deeplearning4j.optimize.listeners.ScoreIterationListener) IrisDataSetIterator(org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator) DataSetIterator(org.nd4j.linalg.dataset.api.iterator.DataSetIterator) Ignore(org.junit.Ignore) Test(org.junit.Test)

Example 8 with UIServer

use of org.deeplearning4j.ui.api.UIServer 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());
}
Also used : InMemoryModelSaver(org.deeplearning4j.earlystopping.saver.InMemoryModelSaver) MaxEpochsTerminationCondition(org.deeplearning4j.earlystopping.termination.MaxEpochsTerminationCondition) InMemoryStatsStorage(org.deeplearning4j.ui.storage.InMemoryStatsStorage) StatsStorage(org.deeplearning4j.api.storage.StatsStorage) IrisDataSetIterator(org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator) UIServer(org.deeplearning4j.ui.api.UIServer) StatsListener(org.deeplearning4j.ui.stats.StatsListener) EarlyStoppingConfiguration(org.deeplearning4j.earlystopping.EarlyStoppingConfiguration) MultiLayerConfiguration(org.deeplearning4j.nn.conf.MultiLayerConfiguration) InMemoryStatsStorage(org.deeplearning4j.ui.storage.InMemoryStatsStorage) MultiLayerNetwork(org.deeplearning4j.nn.multilayer.MultiLayerNetwork) DataSetLossCalculator(org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator) IrisDataSetIterator(org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator) DataSetIterator(org.nd4j.linalg.dataset.api.iterator.DataSetIterator) Ignore(org.junit.Ignore) Test(org.junit.Test)

Aggregations

UIServer (org.deeplearning4j.ui.api.UIServer)8 Ignore (org.junit.Ignore)7 Test (org.junit.Test)7 StatsStorage (org.deeplearning4j.api.storage.StatsStorage)5 IrisDataSetIterator (org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator)5 StatsListener (org.deeplearning4j.ui.stats.StatsListener)5 InMemoryStatsStorage (org.deeplearning4j.ui.storage.InMemoryStatsStorage)5 DataSetIterator (org.nd4j.linalg.dataset.api.iterator.DataSetIterator)5 MultiLayerConfiguration (org.deeplearning4j.nn.conf.MultiLayerConfiguration)4 MultiLayerNetwork (org.deeplearning4j.nn.multilayer.MultiLayerNetwork)4 ScoreIterationListener (org.deeplearning4j.optimize.listeners.ScoreIterationListener)4 OutputLayer (org.deeplearning4j.nn.conf.layers.OutputLayer)3 Persistable (org.deeplearning4j.api.storage.Persistable)2 ArrayList (java.util.ArrayList)1 StorageMetaData (org.deeplearning4j.api.storage.StorageMetaData)1 CollectionStatsStorageRouter (org.deeplearning4j.api.storage.impl.CollectionStatsStorageRouter)1 RemoteUIStatsStorageRouter (org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter)1 EarlyStoppingConfiguration (org.deeplearning4j.earlystopping.EarlyStoppingConfiguration)1 InMemoryModelSaver (org.deeplearning4j.earlystopping.saver.InMemoryModelSaver)1 DataSetLossCalculator (org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator)1