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Java example source code file (StatsCalculationHelper.java)

This example Java source code file (StatsCalculationHelper.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

arraylist, commonsparktrainingstats, list, statscalculationhelper, util

The StatsCalculationHelper.java Java example source code

package org.deeplearning4j.spark.api.worker;

import org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats;
import org.deeplearning4j.spark.api.stats.SparkTrainingStats;

import java.util.ArrayList;
import java.util.List;

/**
 * A helper class for collecting stats in {@link ExecuteWorkerFlatMap} and {@link ExecuteWorkerMultiDataSetFlatMap}
 *
 * @author Alex Black
 */
public class StatsCalculationHelper {
    private long methodStartTime;
    private long returnTime;
    private long initalModelBefore;
    private long initialModelAfter;
    private long lastDataSetBefore;
    private long lastProcessBefore;
    private int totalExampleCount;
    //TODO: This adds more overhead than we want. Replace with a fast int collection (no boxing + conversion!)
    private List<Integer> dataSetGetTimes = new ArrayList<>();
    private List<Integer> processMiniBatchTimes = new ArrayList<>();

    public void logMethodStartTime(){
        methodStartTime = System.currentTimeMillis();
    }

    public void logReturnTime(){
        returnTime = System.currentTimeMillis();
    }

    public void logInitialModelBefore(){
        initalModelBefore = System.currentTimeMillis();
    }

    public void logInitialModelAfter(){
        initialModelAfter = System.currentTimeMillis();
    }

    public void logNextDataSetBefore(){
        lastDataSetBefore = System.currentTimeMillis();
    }

    public void logNextDataSetAfter(int numExamples){
        long now = System.currentTimeMillis();
        dataSetGetTimes.add((int)(now-lastDataSetBefore));
        totalExampleCount += numExamples;
    }

    public void logProcessMinibatchBefore(){
        lastProcessBefore = System.currentTimeMillis();
    }

    public void logProcessMinibatchAfter(){
        long now = System.currentTimeMillis();
        processMiniBatchTimes.add((int)(now-lastProcessBefore));
    }

    public CommonSparkTrainingStats build(SparkTrainingStats masterSpecificStats){
        //TODO again, do this without the lists...
        int[] dataSetGetTimesArr = new int[dataSetGetTimes.size()];
        for( int i=0; i<dataSetGetTimesArr.length; i++ ) dataSetGetTimesArr[i] = dataSetGetTimes.get(i);
        int[] processMiniBatchTimesArr = new int[processMiniBatchTimes.size()];
        for( int i=0; i<processMiniBatchTimesArr.length; i++ ) processMiniBatchTimesArr[i] = processMiniBatchTimes.get(i);

        return new CommonSparkTrainingStats.Builder()
                .trainingMasterSpecificStats(masterSpecificStats)
                .workerFlatMapTotalTimeMs((int)(returnTime-methodStartTime))
                .workerFlatMapTotalExampleCount(totalExampleCount)
                .workerFlatMapGetInitialModelTimeMs((int)(initialModelAfter-initalModelBefore))
                .workerFlatMapDataSetGetTimesMs(dataSetGetTimesArr)
                .workerFlatMapProcessMiniBatchTimesMs(processMiniBatchTimesArr)
                .workerFlatMapCountNoDataInstances(dataSetGetTimes.size() == 0 ? 1 : 0)
                .build();
    }
}

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