com.tencent.angel.ml.matrix.psf.aggr.Amax Maven / Gradle / Ivy
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* Copyright (C) 2017 THL A29 Limited, a Tencent company. All rights reserved.
*
* Licensed under the BSD 3-Clause License (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/BSD-3-Clause
*
* 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.
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package com.tencent.angel.ml.matrix.psf.aggr;
import com.tencent.angel.ml.matrix.psf.aggr.enhance.ScalarAggrResult;
import com.tencent.angel.ml.matrix.psf.aggr.enhance.ScalarPartitionAggrResult;
import com.tencent.angel.ml.matrix.psf.aggr.enhance.UnaryAggrFunc;
import com.tencent.angel.ml.matrix.psf.get.base.GetResult;
import com.tencent.angel.ml.matrix.psf.get.base.PartitionGetResult;
import com.tencent.angel.ps.impl.matrix.ServerDenseDoubleRow;
import java.nio.DoubleBuffer;
import java.util.List;
/**
* `Amax` will aggregate the maximum absolute value of the `rowId` row in `matrixId` matrix.
* For example, if the content of `rowId` row in `matrixId` matrix is [0.3, -11.0, 2.0, 10.1],
* the aggregate result of `Amax` is 11.0 .
*/
public final class Amax extends UnaryAggrFunc {
public Amax(int matrixId, int rowId) {
super(matrixId, rowId);
}
public Amax() {
super();
}
@Override
protected double doProcessRow(ServerDenseDoubleRow row) {
double amax = Double.MIN_VALUE;
DoubleBuffer data = row.getData();
int size = row.size();
for (int i = 0; i < size; i++) {
amax = Math.max(amax, Math.abs(data.get(i)));
}
return amax;
}
@Override
public GetResult merge(List partResults) {
double max = Double.MIN_VALUE;
for (PartitionGetResult partResult : partResults) {
if (partResult != null) {
max = Math.max(max, ((ScalarPartitionAggrResult) partResult).result);
}
}
return new ScalarAggrResult(max);
}
}
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