Example usage for org.apache.mahout.common MemoryUtil startMemoryLogger

List of usage examples for org.apache.mahout.common MemoryUtil startMemoryLogger

Introduction

In this page you can find the example usage for org.apache.mahout.common MemoryUtil startMemoryLogger.

Prototype

public static void startMemoryLogger(long rateInMillis) 

Source Link

Document

Constructs and starts a memory logger thread.

Usage

From source file:com.elex.dmp.lda.CachingCVB0PerplexityMapper.java

License:Apache License

@Override
protected void setup(Context context) throws IOException, InterruptedException {
    MemoryUtil.startMemoryLogger(5000);

    log.info("Retrieving configuration");
    Configuration conf = context.getConfiguration();
    float eta = conf.getFloat(CVB0Driver.TERM_TOPIC_SMOOTHING, Float.NaN);
    float alpha = conf.getFloat(CVB0Driver.DOC_TOPIC_SMOOTHING, Float.NaN);
    long seed = conf.getLong(CVB0Driver.RANDOM_SEED, 1234L);
    random = RandomUtils.getRandom(seed);
    numTopics = conf.getInt(CVB0Driver.NUM_TOPICS, -1);
    int numTerms = conf.getInt(CVB0Driver.NUM_TERMS, -1);
    int numUpdateThreads = conf.getInt(CVB0Driver.NUM_UPDATE_THREADS, 1);
    int numTrainThreads = conf.getInt(CVB0Driver.NUM_TRAIN_THREADS, 4);
    maxIters = conf.getInt(CVB0Driver.MAX_ITERATIONS_PER_DOC, 10);
    float modelWeight = conf.getFloat(CVB0Driver.MODEL_WEIGHT, 1.0f);
    testFraction = conf.getFloat(CVB0Driver.TEST_SET_FRACTION, 0.1f);

    log.info("Initializing read model");
    TopicModel readModel;//  ww  w  . jav a2s.  c  o  m
    Path[] modelPaths = CVB0Driver.getModelPaths(conf);
    if (modelPaths != null && modelPaths.length > 0) {
        readModel = new TopicModel(conf, eta, alpha, null, numUpdateThreads, modelWeight, modelPaths);
    } else {
        log.info("No model files found");
        readModel = new TopicModel(numTopics, numTerms, eta, alpha, RandomUtils.getRandom(seed), null,
                numTrainThreads, modelWeight);
    }

    log.info("Initializing model trainer");
    modelTrainer = new ModelTrainer(readModel, null, numTrainThreads, numTopics, numTerms);

    log.info("Initializing topic vector");
    topicVector = new DenseVector(new double[numTopics]);
}