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.ml.psf.optimizer;
  
  import com.tencent.angel.ml.matrix.psf.update.base.PartitionUpdateParam;
  import com.tencent.angel.ml.matrix.psf.update.base.UpdateFunc;
  import com.tencent.angel.ml.matrix.psf.update.enhance.MMUpdateParam;
  import com.tencent.angel.ps.storage.partition.RowBasedPartition;
  
  
  public abstract class OptMMUpdateFunc extends UpdateFunc {
  
    public OptMMUpdateFunc() {
      super(null);
    }
  
    public OptMMUpdateFunc(int matrixId, int[] rowIds, double[] scalars) {
      super(new MMUpdateParam(matrixId, rowIds, scalars));
    }
  
    @Override
    public void partitionUpdate(PartitionUpdateParam partParam) {
      RowBasedPartition part = (RowBasedPartition)psContext.getMatrixStorageManager()
          .getPart(partParam.getMatrixId(), partParam.getPartKey().getPartitionId());
  
      assert part != null;
      MMUpdateParam.MMPartitionUpdateParam vs2 = (MMUpdateParam.MMPartitionUpdateParam) partParam;
  
      update(part, vs2.getRowIds()[0], vs2.getScalars());
    }
  
    abstract void update(RowBasedPartition partition, int factor, double[] scalars);
  }
  