Example usage for org.apache.mahout.math MatrixWritable readMatrix

List of usage examples for org.apache.mahout.math MatrixWritable readMatrix

Introduction

In this page you can find the example usage for org.apache.mahout.math MatrixWritable readMatrix.

Prototype

public static Matrix readMatrix(DataInput in) throws IOException 

Source Link

Document

Reads a typed Matrix instance from the input stream

Usage

From source file:com.cloudera.knittingboar.messages.GradientUpdateMessage.java

License:Apache License

public void Deserialize(DataInput in) throws IOException {

    this.src_host = in.readUTF();
    this.SrcWorkerPassCount = in.readInt();
    this.gradient.setMatrix(MatrixWritable.readMatrix(in));

}

From source file:com.cloudera.knittingboar.messages.iterativereduce.ParameterVector.java

License:Apache License

public void Deserialize(byte[] bytes) throws IOException {
    // DataInput in) throws IOException {

    ByteArrayInputStream b = new ByteArrayInputStream(bytes);
    DataInput in = new DataInputStream(b);
    // this.src_host = in.readUTF();
    this.SrcWorkerPassCount = in.readInt();
    this.GlobalPassCount = in.readInt();

    this.IterationComplete = in.readInt();
    this.CurrentIteration = in.readInt();

    this.TrainedRecords = in.readInt(); // d.writeInt(this.TrainedRecords);
    this.AvgLogLikelihood = in.readFloat(); // d.writeFloat(this.AvgLogLikelihood);
    this.PercentCorrect = in.readFloat(); // d.writeFloat(this.PercentCorrect);

    this.parameter_vector = MatrixWritable.readMatrix(in);

}

From source file:com.cloudera.knittingboar.sgd.ParallelOnlineLogisticRegression.java

License:Apache License

@Override
public void readFields(DataInput in) throws IOException {
    int version = in.readInt();
    if (version == WRITABLE_VERSION) {
        learningRate = in.readDouble();/*w ww  .ja  v a  2s.  c  o  m*/
        decayFactor = in.readDouble();
        stepOffset = in.readInt();
        step = in.readInt();
        forgettingExponent = in.readDouble();
        perTermAnnealingOffset = in.readInt();
        numCategories = in.readInt();
        beta = MatrixWritable.readMatrix(in);
        prior = PolymorphicWritable.read(in, PriorFunction.class);

        updateCounts = VectorWritable.readVector(in);
        updateSteps = VectorWritable.readVector(in);
    } else {
        throw new IOException("Incorrect object version, wanted " + WRITABLE_VERSION + " got " + version);
    }

}