/*
* 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.ml.factory.method;
import java.util.List;
import org.encog.EncogError;
import org.encog.engine.network.activation.ActivationFunction;
import org.encog.engine.network.activation.ActivationLinear;
import org.encog.engine.network.activation.ActivationSigmoid;
import org.encog.engine.network.activation.ActivationTANH;
import org.encog.ml.MLMethod;
import org.encog.ml.factory.MLActivationFactory;
import org.encog.ml.factory.parse.ArchitectureLayer;
import org.encog.ml.factory.parse.ArchitectureParse;
import org.encog.neural.NeuralNetworkError;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.layers.BasicLayer;
/**
* A factor to create feedforward networks.
*
*/
public class FeedforwardFactory {
/**
* Error.
*/
public static final String CANT_DEFINE_ACT
= "Can't define activation function before first layer.";
/**
* The activation function factory to use.
*/
private MLActivationFactory factory = new MLActivationFactory();
/**
* Create a feed forward network.
* @param architecture The architecture string to use.
* @param input The input count.
* @param output The output count.
* @return The feedforward network.
*/
public final MLMethod create(final String architecture, final int input,
final int output) {
if( input<=0 ) {
throw new EncogError("Must have at least one input for feedforward.");
}
if( output<=0 ) {
throw new EncogError("Must have at least one output for feedforward.");
}
final BasicNetwork result = new BasicNetwork();
final List<String> layers = ArchitectureParse.parseLayers(architecture);
ActivationFunction af = new ActivationLinear();
int questionPhase = 0;
for (final String layerStr : layers) {
int defaultCount;
// determine default
if (questionPhase == 0) {
defaultCount = input;
} else {
defaultCount = output;
}
final ArchitectureLayer layer = ArchitectureParse.parseLayer(
layerStr, defaultCount);
final boolean bias = layer.isBias();
String part = layer.getName();
if (part != null) {
part = part.trim();
} else {
part = "";
}
ActivationFunction lookup = this.factory.create(part);
if (lookup!=null) {
af = lookup;
} else {
if (layer.isUsedDefault()) {
questionPhase++;
if (questionPhase > 2) {
throw new EncogError("Only two ?'s may be used.");
}
}
if (layer.getCount() == 0) {
throw new EncogError("Unknown architecture element: "
+ architecture + ", can't parse: " + part);
}
result.addLayer(new BasicLayer(af, bias,
layer.getCount()));
}
}
result.getStructure().finalizeStructure();
result.reset();
return result;
}
}