/*
* Encog(tm) Core Unit Tests v3.0 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2011 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.persist;
import java.io.File;
import junit.framework.Assert;
import junit.framework.TestCase;
import org.encog.ml.data.MLDataSet;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.XOR;
import org.encog.neural.networks.training.propagation.TrainingContinuation;
import org.encog.neural.networks.training.propagation.resilient.ResilientPropagation;
import org.encog.util.TempDir;
public class TestPersistTrainingContinuation extends TestCase {
public final TempDir TEMP_DIR = new TempDir();
public final File EG_FILENAME = TEMP_DIR.createFile("encogtest.eg");
public final File SERIAL_FILENAME = TEMP_DIR.createFile("encogtest.ser");
public void testRPROPCont() {
MLDataSet trainingSet = XOR.createXORDataSet();
BasicNetwork net1 = XOR.createUnTrainedXOR();
BasicNetwork net2 = XOR.createUnTrainedXOR();
ResilientPropagation rprop1 = new ResilientPropagation(net1,trainingSet);
ResilientPropagation rprop2 = new ResilientPropagation(net2,trainingSet);
rprop1.iteration();
rprop1.iteration();
rprop2.iteration();
rprop2.iteration();
TrainingContinuation cont = rprop2.pause();
ResilientPropagation rprop3 = new ResilientPropagation(net2,trainingSet);
rprop3.resume(cont);
rprop1.iteration();
rprop3.iteration();
for(int i=0;i<net1.getFlat().getWeights().length;i++) {
Assert.assertEquals(net1.getFlat().getWeights()[i], net2.getFlat().getWeights()[i],0.0001);
}
}
public void testRPROPContPersistEG() {
MLDataSet trainingSet = XOR.createXORDataSet();
BasicNetwork net1 = XOR.createUnTrainedXOR();
BasicNetwork net2 = XOR.createUnTrainedXOR();
ResilientPropagation rprop1 = new ResilientPropagation(net1,trainingSet);
ResilientPropagation rprop2 = new ResilientPropagation(net2,trainingSet);
rprop1.iteration();
rprop1.iteration();
rprop2.iteration();
rprop2.iteration();
TrainingContinuation cont = rprop2.pause();
EncogDirectoryPersistence.saveObject(EG_FILENAME, cont);
TrainingContinuation cont2 = (TrainingContinuation)EncogDirectoryPersistence.loadObject(EG_FILENAME);
ResilientPropagation rprop3 = new ResilientPropagation(net2,trainingSet);
rprop3.resume(cont2);
rprop1.iteration();
rprop3.iteration();
for(int i=0;i<net1.getFlat().getWeights().length;i++) {
Assert.assertEquals(net1.getFlat().getWeights()[i], net2.getFlat().getWeights()[i],0.0001);
}
}
}