package org.encog.neural.networks.training.concurrent;
import junit.framework.TestCase;
import org.encog.ml.train.strategy.end.EndMaxErrorStrategy;
import org.encog.neural.networks.XOR;
import org.encog.neural.networks.training.concurrent.jobs.BPROPJob;
import org.encog.neural.networks.training.concurrent.jobs.RPROPJob;
import org.encog.neural.networks.training.concurrent.jobs.TrainingJob;
public class TestConcurrent extends TestCase {
private void internalTest(boolean splitCores) {
ConcurrentTrainingManager ctm = ConcurrentTrainingManager.getInstance();
ctm.clearPerformers();
ctm.detectPerformers(splitCores);
// create a RPROP job
TrainingJob job1 = new RPROPJob(
XOR.createUnTrainedXOR(),
XOR.createXORDataSet(),true);
job1.getStrategies().add(new EndMaxErrorStrategy(0.01));
ctm.addTrainingJob(job1);
// create a BPROP job
TrainingJob job2 = new BPROPJob(
XOR.createUnTrainedXOR(),
XOR.createXORDataSet(),true, 0.07, 0.07);
job2.getStrategies().add(new EndMaxErrorStrategy(0.01));
ctm.addTrainingJob(job2);
ctm.start();
ctm.join();
XOR.verifyXOR(job1.getNetwork(), 0.1);
XOR.verifyXOR(job2.getNetwork(), 0.1);
}
public void testSingleThreaded() {
internalTest(true);
}
public void testMultiThreaded() {
internalTest(false);
}
}