Examples with ScoreIterationListener org.deeplearning4j.optimize.listeners.ScoreIterationListener used on opensource projects

Example 76 with ScoreIterationListener

use of org.deeplearning4j.optimize.listeners.ScoreIterationListener in project deeplearning4j by deeplearning4j.

the class TestFlowListener method testUI.

@Test
public void testUI() throws Exception {
    // Number of input channels
    int nChannels = 1;
    // The number of possible outcomes
    int outputNum = 10;
    // Test batch size
    int batchSize = 64;
    DataSetIterator mnistTrain = new MnistDataSetIterator(batchSize, true, 12345);
    MultiLayerConfiguration conf = // Training iterations as above
    new NeuralNetConfiguration.Builder().seed(12345).iterations(1).regularization(true).l2(0.0005).learningRate(0.01).weightInit(WeightInit.XAVIER).optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).updater(Updater.NESTEROVS).momentum(0.9).list().layer(0, new ConvolutionLayer.Builder(5, 5).nIn(nChannels).stride(1, 1).nOut(20).activation(Activation.IDENTITY).build()).layer(1, new SubsamplingLayer.Builder(SubsamplingLayer.PoolingType.MAX).kernelSize(2, 2).stride(2, 2).build()).layer(2, new ConvolutionLayer.Builder(5, 5).stride(1, 1).nOut(50).activation(Activation.IDENTITY).build()).layer(3, new SubsamplingLayer.Builder(SubsamplingLayer.PoolingType.MAX).kernelSize(2, 2).stride(2, 2).build()).layer(4, new DenseLayer.Builder().activation(Activation.RELU).nOut(500).build()).layer(5, new OutputLayer.Builder(LossFunctions.LossFunction.NEGATIVELOGLIKELIHOOD).nOut(outputNum).activation(Activation.SOFTMAX).build()).setInputType(//See note below
    InputType.convolutionalFlat(28, 28, 1)).backprop(true).pretrain(false).build();
    MultiLayerNetwork net = new MultiLayerNetwork(conf);
    net.init();
    net.setListeners(new FlowIterationListener(1), new ScoreIterationListener(1));
    for (int i = 0; i < 50; i++) {
        net.fit(mnistTrain.next());
        Thread.sleep(1000);
    }
    Thread.sleep(100000);
}