Examples with SimpleMatrix org.ejml.simple.SimpleMatrix used on opensource projects

Example 66 with SimpleMatrix

use of org.ejml.simple.SimpleMatrix in project CoreNLP by stanfordnlp.

the class SentimentCostAndGradient method scaleAndRegularize.

private static double scaleAndRegularize(TwoDimensionalMap<String, String, SimpleMatrix> derivatives, TwoDimensionalMap<String, String, SimpleMatrix> currentMatrices, double scale, double regCost, boolean dropBiasColumn) {
    // the regularization cost
    double cost = 0.0;
    for (TwoDimensionalMap.Entry<String, String, SimpleMatrix> entry : currentMatrices) {
        SimpleMatrix D = derivatives.get(entry.getFirstKey(), entry.getSecondKey());
        SimpleMatrix regMatrix = entry.getValue();
        if (dropBiasColumn) {
            regMatrix = new SimpleMatrix(regMatrix);
            regMatrix.insertIntoThis(0, regMatrix.numCols() - 1, new SimpleMatrix(regMatrix.numRows(), 1));
        }
        D = D.scale(scale).plus(regMatrix.scale(regCost));
        derivatives.put(entry.getFirstKey(), entry.getSecondKey(), D);
        cost += regMatrix.elementMult(regMatrix).elementSum() * regCost / 2.0;
    }
    return cost;
}

Example 67 with SimpleMatrix

use of org.ejml.simple.SimpleMatrix in project CoreNLP by stanfordnlp.

the class SentimentModel method randomTransformMatrix.

SimpleMatrix randomTransformMatrix() {
    SimpleMatrix binary = new SimpleMatrix(numHid, numHid * 2 + 1);
    // bias column values are initialized zero
    binary.insertIntoThis(0, 0, randomTransformBlock());
    binary.insertIntoThis(0, numHid, randomTransformBlock());
    return binary.scale(op.trainOptions.scalingForInit);
}

Example 68 with SimpleMatrix

use of org.ejml.simple.SimpleMatrix in project CoreNLP by stanfordnlp.

the class ConvertMatlabModel method main.

public static void main(String[] args) throws IOException {
    String basePath = "/user/socherr/scr/projects/semComp/RNTN/src/params/";
    int numSlices = 25;
    boolean useEscapedParens = false;
    for (int argIndex = 0; argIndex < args.length; ) {
        if (args[argIndex].equalsIgnoreCase("-slices")) {
            numSlices = Integer.parseInt(args[argIndex + 1]);
            argIndex += 2;
        } else if (args[argIndex].equalsIgnoreCase("-path")) {
            basePath = args[argIndex + 1];
            argIndex += 2;
        } else if (args[argIndex].equalsIgnoreCase("-useEscapedParens")) {
            useEscapedParens = true;
            argIndex += 1;
        } else {
            log.info("Unknown argument " + args[argIndex]);
            System.exit(2);
        }
    }
    SimpleMatrix[] slices = new SimpleMatrix[numSlices];
    for (int i = 0; i < numSlices; ++i) {
        slices[i] = loadMatrix(basePath + "bin/Wt_" + (i + 1) + ".bin", basePath + "Wt_" + (i + 1) + ".txt");
    }
    SimpleTensor tensor = new SimpleTensor(slices);
    log.info("W tensor size: " + tensor.numRows() + "x" + tensor.numCols() + "x" + tensor.numSlices());
    SimpleMatrix W = loadMatrix(basePath + "bin/W.bin", basePath + "W.txt");
    log.info("W matrix size: " + W.numRows() + "x" + W.numCols());
    SimpleMatrix Wcat = loadMatrix(basePath + "bin/Wcat.bin", basePath + "Wcat.txt");
    log.info("W cat size: " + Wcat.numRows() + "x" + Wcat.numCols());
    SimpleMatrix combinedWV = loadMatrix(basePath + "bin/Wv.bin", basePath + "Wv.txt");
    log.info("Word matrix size: " + combinedWV.numRows() + "x" + combinedWV.numCols());
    File vocabFile = new File(basePath + "vocab_1.txt");
    if (!vocabFile.exists()) {
        vocabFile = new File(basePath + "words.txt");
    }
    List<String> lines = Generics.newArrayList();
    for (String line : IOUtils.readLines(vocabFile)) {
        lines.add(line.trim());
    }
    log.info("Lines in vocab file: " + lines.size());
    Map<String, SimpleMatrix> wordVectors = Generics.newTreeMap();
    for (int i = 0; i < lines.size() && i < combinedWV.numCols(); ++i) {
        String[] pieces = lines.get(i).split(" +");
        if (pieces.length == 0 || pieces.length > 1) {
            continue;
        }
        wordVectors.put(pieces[0], combinedWV.extractMatrix(0, numSlices, i, i + 1));
        if (pieces[0].equals("UNK")) {
            wordVectors.put(SentimentModel.UNKNOWN_WORD, wordVectors.get("UNK"));
        }
    }
    // If there is no ",", we first try to look for an HTML escaping,
    // then fall back to "." as better than just a random word vector.
    // Same for "``" and ";"
    copyWordVector(wordVectors, "&#44", ",");
    copyWordVector(wordVectors, ".", ",");
    copyWordVector(wordVectors, "&#59", ";");
    copyWordVector(wordVectors, ".", ";");
    copyWordVector(wordVectors, "&#96&#96", "``");
    copyWordVector(wordVectors, "''", "``");
    if (useEscapedParens) {
        replaceWordVector(wordVectors, "(", "-LRB-");
        replaceWordVector(wordVectors, ")", "-RRB-");
    }
    RNNOptions op = new RNNOptions();
    op.numHid = numSlices;
    op.lowercaseWordVectors = false;
    if (Wcat.numRows() == 2) {
        op.classNames = new String[] { "Negative", "Positive" };
        // TODO: set to null once old models are updated
        op.equivalenceClasses = new int[][] { { 0 }, { 1 } };
        op.numClasses = 2;
    }
    if (!wordVectors.containsKey(SentimentModel.UNKNOWN_WORD)) {
        wordVectors.put(SentimentModel.UNKNOWN_WORD, SimpleMatrix.random_DDRM(numSlices, 1, -0.00001, 0.00001, new Random()));
    }
    SentimentModel model = SentimentModel.modelFromMatrices(W, Wcat, tensor, wordVectors, op);
    model.saveSerialized("matlab.ser.gz");
}

Example 69 with SimpleMatrix

use of org.ejml.simple.SimpleMatrix in project CoreNLP by stanfordnlp.

the class SentimentModel method readWordVectors.

void readWordVectors() {
    Embedding embedding = new Embedding(op.wordVectors, op.numHid);
    this.wordVectors = Generics.newTreeMap();
    // for (String word : rawWordVectors.keySet()) {
    for (String word : embedding.keySet()) {
        // TODO: factor out unknown word vector code from DVParser
        wordVectors.put(word, embedding.get(word));
    }
    String unkWord = op.unkWord;
    SimpleMatrix unknownWordVector = wordVectors.get(unkWord);
    wordVectors.put(UNKNOWN_WORD, unknownWordVector);
    if (unknownWordVector == null) {
        throw new RuntimeException("Unknown word vector not specified in the word vector file");
    }
}

Example 70 with SimpleMatrix

use of org.ejml.simple.SimpleMatrix in project CoreNLP by stanfordnlp.

the class SentimentModel method randomClassificationMatrix.

/**
 * Returns matrices of the right size for either binary or unary (terminal) classification
 */
SimpleMatrix randomClassificationMatrix() {
    SimpleMatrix score = new SimpleMatrix(numClasses, numHid + 1);
    double range = 1.0 / (Math.sqrt((double) numHid));
    score.insertIntoThis(0, 0, SimpleMatrix.random_DDRM(numClasses, numHid, -range, range, rand));
    // bias column goes from 0 to 1 initially
    score.insertIntoThis(0, numHid, SimpleMatrix.random_DDRM(numClasses, 1, 0.0, 1.0, rand));
    return score.scale(op.trainOptions.scalingForInit);
}