org.apache.mahout.classifier.rbm.model.RBMModel.java Source code

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Here is the source code for org.apache.mahout.classifier.rbm.model.RBMModel.java

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/**
 * 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.model;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.mahout.classifier.rbm.layer.Layer;
import org.apache.mahout.common.distance.DistanceMeasure;
import org.apache.mahout.common.distance.EuclideanDistanceMeasure;
import org.apache.mahout.math.Vector;

import com.google.common.io.Closeables;

/**
 * The Class RBMModel.
 */
public abstract class RBMModel {

    /** The visible layer. */
    protected Layer visibleLayer;

    /** The hidden layer. */
    protected Layer hiddenLayer;

    /**
     * Gets the visible layer.
     *
     * @return the visible layer
     */
    public Layer getVisibleLayer() {
        return visibleLayer;
    }

    /**
     * Gets the hidden layer.
     *
     * @return the hidden layer
     */
    public Layer getHiddenLayer() {
        return hiddenLayer;
    }

    /**
     * Excite hidden layer.
     *
     * @param inputFactor factor which should be multiplied with the inputs of the units, usually 1
     * @param addInput true if input should be added to the input of the hidden layer
     */
    public abstract void exciteHiddenLayer(double inputFactor, boolean addInput);

    /**
     * Excite visible layer.
     *
     * @param inputFactor factor which should be multiplied with the inputs of the units, usually 1
     * @param addInput true if input should be added to the input of the hidden layer
     */
    public abstract void exciteVisibleLayer(double inputFactor, boolean addInput);

    /**
     * Serialize.
     *
     * @param output output path where the model should be serialized to
     * @param conf the conf
     * @throws IOException Signals that an I/O exception has occurred.
     */
    public abstract void serialize(Path output, Configuration conf) throws IOException;

    /**
     * Materialize.
     *
     * @param input the path to the model
     * @param conf the hadoop configuration
     * @return the model
     * @throws IOException Signals that an I/O exception has occurred.
     */
    public static RBMModel materialize(Path input, Configuration conf) throws IOException {
        FileSystem fs = input.getFileSystem(conf);
        String rbmType = "";
        FSDataInputStream in = fs.open(input);

        try {
            char chr;
            while ((chr = in.readChar()) != ' ')
                rbmType += chr;

        } finally {
            Closeables.closeQuietly(in);
        }

        try {
            return (RBMModel) Class.forName(rbmType).getMethod("materialize", Path.class, Configuration.class)
                    .invoke(null, input, conf);
        } catch (Exception e) {
            e.printStackTrace();
            return null;
        }
    }

    /**
     * Sets the visible layer.
     *
     * @param visibleLayer the new visible layer
     */
    public void setVisibleLayer(Layer visibleLayer) {
        this.visibleLayer = visibleLayer;
    }

    /**
     * Gets the reconstruction error by doing one time gibbs sampling and computing the euclidean distance
     * between the input and the reconstruction.
     *
     * @param input the input
     * @return the reconstruction error
     */
    public double getReconstructionError(Vector input) {
        this.visibleLayer.setActivations(input);
        exciteHiddenLayer(1, false);
        getHiddenLayer().updateNeurons();
        exciteVisibleLayer(1, false);
        DistanceMeasure dm = new EuclideanDistanceMeasure();

        return dm.distance(input, visibleLayer.getExcitations());
    }

    /**
     * Update hidden layer according to their excitations.
     */
    public void updateHiddenLayer() {
        hiddenLayer.updateNeurons();
    }

    /**
     * Update visible layer.according to their excitations
     */
    public void updateVisibleLayer() {
        visibleLayer.updateNeurons();
    }

    /**
     * Gets the reconstruction error of the current visible layers data.
     *
     * @return the reconstruction error
     */
    public double getReconstructionError() {
        Vector input = this.visibleLayer.getActivations().clone();
        exciteHiddenLayer(1, false);
        updateHiddenLayer();
        exciteVisibleLayer(1, false);

        DistanceMeasure dm = new EuclideanDistanceMeasure();
        return dm.distance(input, visibleLayer.getExcitations());
    }

    /* (non-Javadoc)
     * @see java.lang.Object#clone()
     */
    public abstract RBMModel clone();
}