content: /*
   * 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.vector.Vector;
  import com.tencent.angel.ml.matrix.psf.update.base.UpdateParam;
  
  public class AsyncAdagradFunc extends AsyncOptimFunc {
  
    public AsyncAdagradFunc(UpdateParam param) {
      super(param);
    }
  
    public AsyncAdagradFunc() {
      this(null);
    }
  
    @Override
    public void update(Vector[] vectors, Vector grad, double[] doubles, int[] ints) {
      double eta = doubles[0];
      double factor = doubles[1];
  
      Vector weight = vectors[0];
      Vector square = vectors[1];
  
      OptFuncs.iexpsmoothing2(square, grad, factor);
      grad = OptFuncs.adagraddelta(grad, square, 0.0, eta);
      weight.isub(grad);
    }
  }
  