NesterovsUpdater.java

/*-
 *
 *  * Copyright 2017 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.nd4j.linalg.learning;

import lombok.Data;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.impl.transforms.arithmetic.AddOp;
import org.nd4j.linalg.api.shape.Shape;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.learning.config.Nesterovs;

/**
 * Nesterov's momentum.
 * Keep track of the previous layer's gradient
 * and use it as a way of updating the gradient.
 *
 * @author Adam Gibson
 */
@Data
public class NesterovsUpdater implements GradientUpdater<Nesterovs> {

    private final Nesterovs config;

    private INDArray v;
    private char gradientReshapeOrder;

    public NesterovsUpdater(Nesterovs config) {
        this.config = config;
    }

    @Override
    public void setStateViewArray(INDArray viewArray, int[] gradientShape, char gradientOrder, boolean initialize) {
        if (!viewArray.isRowVector())
            throw new IllegalArgumentException("Invalid input: expect row vector input");
        if (initialize)
            viewArray.assign(0);

        this.v = viewArray;

        //Reshape to match the expected shape of the input gradient arrays
        this.v = Shape.newShapeNoCopy(this.v, gradientShape, gradientOrder == 'f');
        if (v == null)
            throw new IllegalStateException("Could not correctly reshape gradient view array");
        this.gradientReshapeOrder = gradientOrder;
    }

    /**
     * Get the nesterov update
     *
     * @param gradient  the gradient to get the update for
     * @param iteration
     * @return
     */
    @Override
    public void applyUpdater(INDArray gradient, int iteration) {
        if (v == null)
            throw new IllegalStateException("Updater has not been initialized with view state");

        double momentum = config.getMomentum();
        double learningRate = config.getLearningRate();

        //reference https://cs231n.github.io/neural-networks-3/#sgd 2nd equation
        //DL4J default is negative step function thus we flipped the signs:
        // x += mu * v_prev + (-1 - mu) * v
        //i.e., we do params -= updatedGradient, not params += updatedGradient

        //v = mu * v - lr * gradient
        INDArray vPrev = v.dup(gradientReshapeOrder);
        v.muli(momentum).subi(gradient.dup(gradientReshapeOrder).muli(learningRate));              //Modify state array in-place

        /*
        Next line is equivalent to:
        INDArray ret = vPrev.muli(momentum).addi(v.mul(-momentum - 1));
        gradient.assign(ret);
        */
        Nd4j.getExecutioner().exec(new AddOp(vPrev.muli(momentum), v.mul(-momentum - 1), gradient));
    }
}