/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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.
*/
package org.apache.mahout.classifier.rbm.network;
import org.apache.mahout.classifier.rbm.layer.Layer;
import org.apache.mahout.math.Vector;
/**
* The Class DBMStateIterator is a helper class for iterating DBM-states
*/
public class DBMStateIterator{
/**
* Sample (iterate) until the specified layer's activation is stable for at least the specified number of times in a row or until
* the dbm was sampling for at most five (experimental) times this number.
*
* @param layer the layer
* @param dbm the deep boltzmann machine
* @param leastStableIterations the least number of stable iterations
*/
public static void iterateUntilStableLayer(Layer layer,DeepBoltzmannMachine dbm, int leastStableIterations) {
int counter = 0;
int counter2 = 0;
Vector activations = layer.getActivations().clone();
//TODO check: experimental counter2<leastStableIterations*5; how many iterations should the classifier need
while(counter<leastStableIterations&&counter2<leastStableIterations*5) {
for(int i = 1; i<dbm.getLayerCount();i++)
dbm.exciteLayer(i);
for(int i = 1; i<dbm.getLayerCount();i++)
dbm.updateLayer(i);
if(activations.getDistanceSquared(layer.getActivations())==0) {
counter++;
}
else {
activations = layer.getActivations().clone();
counter = 0;
}
counter2++;
}
}
}