confBuilder = netBuilder.lrPolicyDecayRate(0.5).list() .layer(0, new DenseLayer.Builder().nIn(numInputs).nOut(numHiddenNodes) .weightInit(WEIGHT_INIT)
graphBuilder.setUseRegularization(true); NeuralNetConfiguration.Builder graphConfiguration = graphBuilder.lrPolicyDecayRate(0.5) .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1) .learningRate(args().learningRate)
confBuilder = netBuilder.lrPolicyDecayRate(0.5).list() .layer(0, new DenseLayer.Builder().nIn(numInputs).nOut(numHiddenNodes) .weightInit(WEIGHT_INIT)
graphBuilder.setUseRegularization(true); NeuralNetConfiguration.Builder graphConfiguration = graphBuilder.lrPolicyDecayRate(0.5) .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1) .learningRate(args().learningRate)
builder.learningRateSchedule(learningRateSchedule.getValue(values)); if (lrPolicyDecayRate != null) builder.lrPolicyDecayRate(lrPolicyDecayRate.getValue(values)); if (lrPolicyPower != null) builder.lrPolicyPower(lrPolicyPower.getValue(values));
graphBuilder.setUseRegularization(true); NeuralNetConfiguration.Builder graphConfiguration = graphBuilder.lrPolicyDecayRate(0.5) .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1) .learningRate(args().learningRate)
.activation(Activation.RELU).optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT) .learningRate(1e-2).biasLearningRate(2 * 1e-2).learningRateDecayPolicy(LearningRatePolicy.Step) .lrPolicyDecayRate(0.96).lrPolicySteps(320000).updater(new Nesterovs(1e-2, 0.9)) .weightInit(WeightInit.XAVIER).regularization(true).l2(2e-4).graphBuilder();
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); }