com.tencent.angel.sona.psf.optim.AsyncAdamFunc Maven / Gradle / Ivy

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/*
 * Tencent is pleased to support the open source community by making Angel available.
 *
 * Copyright (C) 2017-2018 THL A29 Limited, a Tencent company. All rights reserved.
 *
 * 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
 *
 * https://opensource.org/licenses/Apache-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 com.tencent.angel.sona.psf.optim;

import com.tencent.angel.ml.math2.ufuncs.OptFuncs;
import com.tencent.angel.ml.math2.ufuncs.Ufuncs;
import com.tencent.angel.ml.math2.vector.Vector;
import com.tencent.angel.ml.matrix.psf.update.base.UpdateParam;

public class AsyncAdamFunc extends AsyncOptimFunc {

  public AsyncAdamFunc(UpdateParam param) {
    super(param);
  }

  public AsyncAdamFunc() {
    super(null);
  }

  @Override
  public void update(Vector[] vectors, Vector grad, double[] doubles, int[] ints) {
    double eta = doubles[0];
    double gamma = doubles[1];
    double beta = doubles[2];

    int numUpdates = ints[2];
    double powBeta = Math.pow(beta, numUpdates);
    double powGamma = Math.pow(gamma, numUpdates);

    Vector weight = vectors[0];
    Vector velocity = vectors[1];
    Vector square = vectors[2];

    OptFuncs.iexpsmoothing(velocity, grad, beta);
    OptFuncs.iexpsmoothing2(square, grad, gamma);

    velocity = Ufuncs.indexget(velocity, grad);

    Vector delta = OptFuncs.adamdelta(velocity, square, powBeta, powGamma);
    delta.imul(eta);
    weight.isub(delta);
  }
}