.updater(Updater.ADADELTA) .convolutionMode(ConvolutionMode.Same) .regularization(true).dropOut(0.2) .learningRate(learnRate) .graphBuilder()
netBuilder.dropOut(dropOutRate); netBuilder.setUseDropConnect(true);
netBuilder.dropOut(dropOutRate); netBuilder.setUseDropConnect(true);
builder.l2(l2.getValue(values)); if (dropOut != null) builder.dropOut(dropOut.getValue(values)); if (momentum != null) builder.momentum(momentum.getValue(values));
.dropOut(0.5).l2(5 * 1e-4).miniBatch(false) .list().layer(0, new ConvolutionLayer.Builder(new int[] {11, 11}, new int[] {4, 4},
netBuilder.dropOut(dropOutRate); netBuilder.setUseDropConnect(true);
netBuilder.dropOut(dropOutRate); netBuilder.setUseDropConnect(true);
netBuilder.dropOut(dropOutRate); netBuilder.setUseDropConnect(true);
/** * Deliver access to the internal builder * * @return NeuralNetworkConfiguration */ public org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder builder() { Builder builder = new Builder(); // Set dist to null if Disabled was chosen as dl4j backend defaults to null builder .l1(l1) .l2(l2) .optimizationAlgo(optimizationAlgo) .seed(seed) .weightInit(weightInit) .dist(dist.getBackend()) .biasInit(biasInit) .updater(updater.getBackend()) .biasUpdater(biasUpdater.getBackend()) .dropOut(dropout.getBackend()) .miniBatch(miniBatch) .minimize(minimize) .weightNoise(weightNoise.getBackend()) .gradientNormalization(gradientNormalization.getBackend()) .gradientNormalizationThreshold(gradientNormalizationThreshold) .inferenceWorkspaceMode(inferenceWorkspaceMode) .trainingWorkspaceMode(trainingWorkspaceMode); builder.setPretrain(pretrain); return builder; }
public void initializeBuilder(String... inputNames) { if (inputNames.length == 0) { inputNames = new String[]{"input"}; } NeuralNetConfiguration.Builder graphBuilder = new NeuralNetConfiguration.Builder() .seed(args().seed) .iterations(1) .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT) .learningRate(args().learningRate) .updater(Updater.ADAGRAD) .epsilon(BUILDER_EPSILON) .lrPolicyDecayRate(0.5) .weightInit(WEIGHT_INIT); if (args().regularizationRate != null) { graphBuilder.l2(args().regularizationRate); graphBuilder.regularization(args().regularizationRate != null); } if (args().dropoutRate != null) { graphBuilder.dropOut(args().dropoutRate); graphBuilder.setUseDropConnect(true); } modelCapacity=args().modelCapacity; reductionRate=args().reductionRate; build = graphBuilder.graphBuilder().addInputs(inputNames); }