edu.snu.dolphin.bsp.examples.ml.sub.LinearModelCodec.java Source code

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Here is the source code for edu.snu.dolphin.bsp.examples.ml.sub.LinearModelCodec.java

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/*
 * Copyright (C) 2015 Seoul National University
 *
 * 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 edu.snu.dolphin.bsp.examples.ml.sub;

import edu.snu.dolphin.bsp.examples.ml.data.LinearModel;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.Vector;
import org.apache.reef.io.serialization.Codec;

import javax.inject.Inject;
import java.io.*;

public class LinearModelCodec implements Codec<LinearModel> {

    @Inject
    public LinearModelCodec() {
    }

    @Override
    public byte[] encode(final LinearModel model) {
        final ByteArrayOutputStream baos = new ByteArrayOutputStream(
                Integer.SIZE + Double.SIZE * model.getParameters().size());
        try (final DataOutputStream daos = new DataOutputStream(baos)) {
            daos.writeInt(model.getParameters().size());
            for (int i = 0; i < model.getParameters().size(); i++) {
                daos.writeDouble(model.getParameters().get(i));
            }
        } catch (final IOException e) {
            throw new RuntimeException(e.getCause());
        }
        return baos.toByteArray();
    }

    @Override
    public LinearModel decode(final byte[] data) {
        final ByteArrayInputStream bais = new ByteArrayInputStream(data);
        final LinearModel model;
        try (final DataInputStream dais = new DataInputStream(bais)) {
            final int vecSize = dais.readInt();
            final Vector v = new DenseVector(vecSize);
            for (int i = 0; i < vecSize; i++) {
                v.set(i, dais.readDouble());
            }
            model = new LinearModel(v);
        } catch (final IOException e) {
            throw new RuntimeException(e.getCause());
        }
        return model;
    }
}