/*
* Encog(tm) Core 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.neural.networks.training.concurrent.performers;
import java.util.concurrent.atomic.AtomicBoolean;
import org.encog.ml.train.MLTrain;
import org.encog.neural.NeuralNetworkError;
import org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager;
import org.encog.neural.networks.training.concurrent.jobs.TrainingJob;
import org.encog.util.Stopwatch;
import org.encog.util.concurrency.EngineConcurrency;
/**
* This performer allows jobs to be performed by the CPU.
*
*/
public class ConcurrentTrainingPerformerCPU implements
ConcurrentTrainingPerformer, Runnable {
/**
* True, if this performer is ready for more work.
*/
private final AtomicBoolean ready = new AtomicBoolean(true);
/**
* The current job.
*/
private TrainingJob currentJob;
/**
* The manager.
*/
private ConcurrentTrainingManager manager;
/**
* The job number.
*/
private final int number;
/**
* Construct the performer.
* @param number
*/
public ConcurrentTrainingPerformerCPU(final int number) {
this.number = number;
}
/**
* {@inheritDoc}
*/
@Override
public final ConcurrentTrainingManager getManager() {
return this.manager;
}
public final int getNumber() {
return this.number;
}
/**
* {@inheritDoc}
*/
@Override
public final void perform(final TrainingJob job) {
if (!this.ready.get()) {
throw new NeuralNetworkError(
"Performer is already performing a job.");
}
this.ready.set(false);
this.currentJob = job;
final PerformerTask task = new PerformerTask(this);
EngineConcurrency.getInstance().processTask(task);
}
/**
* {@inheritDoc}
*/
@Override
public final boolean ready() {
return this.ready.get();
}
/**
* {@inheritDoc}
*/
@Override
public final void run() {
final Stopwatch watch = new Stopwatch();
try {
watch.start();
this.currentJob.createTrainer(this.manager.isSingleThreaded());
final MLTrain train = this.currentJob.getTrain();
int interation = 1;
while (this.currentJob.shouldContinue()) {
train.iteration();
interation++;
}
watch.stop();
} catch (final Throwable t) {
this.currentJob.setError(t);
} finally {
this.ready.set(true);
this.manager.jobDone(watch.getElapsedMilliseconds(), this);
}
}
/**
* {@inheritDoc}
*/
@Override
public final void setManager(final ConcurrentTrainingManager manager) {
this.manager = manager;
}
/**
* {@inheritDoc}
*/
@Override
public final String toString() {
return "[CPU-Performer: " + this.number + "]";
}
}