/** @param args */
public static void main(String[] args) throws Exception {
// batches of 10, 60000 examples total
DataSetIterator iter = new MnistDataSetIterator(80, 48000);
Conf c = new Conf();
c.setFinetuneEpochs(1000);
c.setFinetuneLearningRate(1e-1);
c.setPretrainLearningRate(1e-2);
c.setPretrainEpochs(1000);
c.setLayerSizes(new int[] {600, 400, 200});
c.setnIn(784);
c.setDropOut(5e-1);
c.setSparsity(1e-1);
c.setUseAdaGrad(true);
c.setnOut(10);
c.setSplit(100);
c.setMultiLayerClazz(DBN.class);
c.setUseRegularization(true);
c.setL2(2e-4);
c.setRenderEpochsByLayer(Collections.singletonMap(0, 10));
c.setDeepLearningParams(new Object[] {1, 1e-1, 1});
ActorNetworkRunner runner =
args.length < 1
? new ActorNetworkRunner("master", iter)
: new ActorNetworkRunner(
"master",
iter,
(BaseMultiLayerNetwork) SerializationUtils.readObject(new File(args[0])));
runner.setModelSaver(new DefaultModelSaver(new File("mnist-example.ser")));
runner.setup(c);
runner.train();
}
/**
* Sets in and outs based on data
*
* @param data the data to use
*/
public void initFromData(DataSet data) {
setnIn(data.numInputs());
setnOut(data.numOutcomes());
}