Java example source code file (MnistDataFetcher.java)

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Java - Java tags/keywords

dataset, file, indarray, ioexception, mnist_root, mnistdatafetcher, mnistmanager, num_examples, num_examples_test, override, random, shuffle, string, temp_root, util

The MnistDataFetcher.java Java example source code

/*
 *
 *  * Copyright 2015 Skymind,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.
 *
 */

package org.deeplearning4j.datasets.fetchers;

import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Random;

import org.apache.commons.io.FileUtils;
import org.apache.commons.io.FilenameUtils;
import org.deeplearning4j.base.MnistFetcher;
import org.deeplearning4j.datasets.mnist.MnistManager;
import org.deeplearning4j.util.MathUtils;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.dataset.DataSet;
import org.nd4j.linalg.factory.Nd4j;


/**
 * Data fetcher for the MNIST dataset
 * @author Adam Gibson
 *
 */
public class MnistDataFetcher extends BaseDataFetcher {
    public static final int NUM_EXAMPLES = 60000;
    public static final int NUM_EXAMPLES_TEST = 10000;
    protected static final String TEMP_ROOT = System.getProperty("user.home");
    protected static final String MNIST_ROOT = TEMP_ROOT + File.separator + "MNIST" + File.separator;

    protected transient MnistManager man;
    protected boolean binarize = true;
    protected boolean train;
    protected int[] order;
    protected Random rng;
    protected boolean shuffle;


    /**
     * Constructor telling whether to binarize the dataset or not
     * @param binarize whether to binarize the dataset or not
     * @throws IOException
     */
    public MnistDataFetcher(boolean binarize) throws IOException {
        this(binarize,true,true,System.currentTimeMillis());
    }

    public MnistDataFetcher(boolean binarize, boolean train, boolean shuffle, long rngSeed) throws IOException {
        if(!mnistExists()) {
            new MnistFetcher().downloadAndUntar();
        }
        String images;
        String labels;
        if(train){
            images = MNIST_ROOT + MnistFetcher.trainingFilesFilename_unzipped;
            labels = MNIST_ROOT + MnistFetcher.trainingFileLabelsFilename_unzipped;
            totalExamples = NUM_EXAMPLES;
        } else {
            images = MNIST_ROOT + MnistFetcher.testFilesFilename_unzipped;
            labels = MNIST_ROOT + MnistFetcher.testFileLabelsFilename_unzipped;
            totalExamples = NUM_EXAMPLES_TEST;
        }

        try {
            man = new MnistManager(images, labels, train);
        }catch(Exception e) {
            FileUtils.deleteDirectory(new File(MNIST_ROOT));
            new MnistFetcher().downloadAndUntar();
            man = new MnistManager(images, labels, train);
        }

        numOutcomes = 10;
        this.binarize = binarize;
        cursor = 0;
        inputColumns = man.getImages().getEntryLength();
        this.train = train;
        this.shuffle = shuffle;

        if(train){
            order = new int[NUM_EXAMPLES];
        } else {
            order = new int[NUM_EXAMPLES_TEST];
        }
        for( int i=0; i<order.length; i++ ) order[i] = i;
        rng = new Random(rngSeed);
        reset();    //Shuffle order
    }

    private boolean mnistExists(){
        //Check 4 files:
        File f = new File(MNIST_ROOT,MnistFetcher.trainingFilesFilename_unzipped);
        if(!f.exists()) return false;
        f = new File(MNIST_ROOT,MnistFetcher.trainingFileLabelsFilename_unzipped);
        if(!f.exists()) return false;
        f = new File(MNIST_ROOT,MnistFetcher.testFilesFilename_unzipped);
        if(!f.exists()) return false;
        f = new File(MNIST_ROOT,MnistFetcher.testFileLabelsFilename_unzipped);
        if(!f.exists()) return false;
        return true;
    }

    public MnistDataFetcher() throws IOException {
        this(true);
    }

    @Override
    public void fetch(int numExamples) {
        if(!hasMore()) {
            throw new IllegalStateException("Unable to getFromOrigin more; there are no more images");
        }


        float[][] featureData = new float[numExamples][0];
        float[][] labelData = new float[numExamples][0];

        int actualExamples = 0;
        for( int i=0; i<numExamples; i++, cursor++ ){
            if(!hasMore()) break;

            byte[] img = man.readImageUnsafe(order[cursor]);
            int label = man.readLabel(order[cursor]);

            float[] featureVec = new float[img.length];
            featureData[actualExamples] = featureVec;
            labelData[actualExamples] = new float[10];
            labelData[actualExamples][label] = 1.0f;

            for( int j=0; j<img.length; j++ ){
                float v = ((int)img[j]) & 0xFF; //byte is loaded as signed -> convert to unsigned
                if(binarize){
                    if(v > 30.0f) featureVec[j] = 1.0f;
                    else featureVec[j] = 0.0f;
                } else {
                    featureVec[j] = v/255.0f;
                }
            }

            actualExamples++;
        }

        if(actualExamples < numExamples){
            featureData = Arrays.copyOfRange(featureData,0,actualExamples);
            labelData = Arrays.copyOfRange(labelData,0,actualExamples);
        }

        INDArray features = Nd4j.create(featureData);
        INDArray labels = Nd4j.create(labelData);
        curr = new DataSet(features,labels);
    }

    @Override
    public void reset() {
        cursor = 0;
        curr = null;
        if(shuffle) MathUtils.shuffleArray(order, rng);
    }

    @Override
    public DataSet next() {
        DataSet next = super.next();
        return next;
    }

}