本文整理了Java中org.deeplearning4j.nn.multilayer.MultiLayerNetwork.getListeners()方法的一些代码示例，展示了MultiLayerNetwork.getListeners()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。MultiLayerNetwork.getListeners()方法的具体详情如下：
包路径：org.deeplearning4j.nn.multilayer.MultiLayerNetwork
类名称：MultiLayerNetwork
方法名：getListeners

MultiLayerNetwork.getListeners介绍

暂无

代码示例

代码示例来源：origin: org.deeplearning4j/deeplearning4j-parallel-wrapper

modelListeners = new ArrayList<>(((MultiLayerNetwork) model).getListeners());
  model.setListeners(Collections.emptyList());
} else if (model instanceof ComputationGraph) {

代码示例来源：origin: org.deeplearning4j/deeplearning4j-parallel-wrapper_2.11

modelListeners = new ArrayList<>(((MultiLayerNetwork) model).getListeners());
  model.setListeners(Collections.emptyList());
} else if (model instanceof ComputationGraph) {

代码示例来源：origin: org.deeplearning4j/deeplearning4j-parallel-wrapper

public EarlyStoppingParallelTrainer(EarlyStoppingConfiguration<T> earlyStoppingConfiguration, T model,
        DataSetIterator train, MultiDataSetIterator trainMulti, EarlyStoppingListener<T> listener,
        int workers, int prefetchBuffer, int averagingFrequency, boolean reportScoreAfterAveraging,
        boolean useLegacyAveraging) {
  this.esConfig = earlyStoppingConfiguration;
  this.train = train;
  this.trainMulti = trainMulti;
  this.iterator = (train != null ? train : trainMulti);
  this.listener = listener;
  this.model = model;
  // adjust UI listeners
  AveragingIterationListener trainerListener = new AveragingIterationListener(this);
  if (model instanceof MultiLayerNetwork) {
    Collection<IterationListener> listeners = ((MultiLayerNetwork) model).getListeners();
    Collection<IterationListener> newListeners = new LinkedList<>(listeners);
    newListeners.add(trainerListener);
    model.setListeners(newListeners);
  } else if (model instanceof ComputationGraph) {
    Collection<IterationListener> listeners = ((ComputationGraph) model).getListeners();
    Collection<IterationListener> newListeners = new LinkedList<>(listeners);
    newListeners.add(trainerListener);
    model.setListeners(newListeners);
  }
  this.wrapper = new ParallelWrapper.Builder<>(model).workers(workers).prefetchBuffer(prefetchBuffer)
          .averagingFrequency(averagingFrequency)
          //.useLegacyAveraging(useLegacyAveraging)
          .reportScoreAfterAveraging(reportScoreAfterAveraging).build();
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-parallel-wrapper_2.11

public EarlyStoppingParallelTrainer(EarlyStoppingConfiguration<T> earlyStoppingConfiguration, T model,
        DataSetIterator train, MultiDataSetIterator trainMulti, EarlyStoppingListener<T> listener,
        int workers, int prefetchBuffer, int averagingFrequency, boolean reportScoreAfterAveraging,
        boolean useLegacyAveraging) {
  this.esConfig = earlyStoppingConfiguration;
  this.train = train;
  this.trainMulti = trainMulti;
  this.iterator = (train != null ? train : trainMulti);
  this.listener = listener;
  this.model = model;
  // adjust UI listeners
  AveragingIterationListener trainerListener = new AveragingIterationListener(this);
  if (model instanceof MultiLayerNetwork) {
    Collection<IterationListener> listeners = ((MultiLayerNetwork) model).getListeners();
    Collection<IterationListener> newListeners = new LinkedList<>(listeners);
    newListeners.add(trainerListener);
    model.setListeners(newListeners);
  } else if (model instanceof ComputationGraph) {
    Collection<IterationListener> listeners = ((ComputationGraph) model).getListeners();
    Collection<IterationListener> newListeners = new LinkedList<>(listeners);
    newListeners.add(trainerListener);
    model.setListeners(newListeners);
  }
  this.wrapper = new ParallelWrapper.Builder<>(model).workers(workers).prefetchBuffer(prefetchBuffer)
          .averagingFrequency(averagingFrequency)
          //.useLegacyAveraging(useLegacyAveraging)
          .reportScoreAfterAveraging(reportScoreAfterAveraging).build();
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

/** Set the updater for the MultiLayerNetwork */
public void setUpdater(Updater updater) {
  if (solver == null) {
    solver = new Solver.Builder().configure(conf()).listeners(getListeners()).model(this).build();
  }
  solver.getOptimizer().setUpdater(updater);
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

/** Get the updater for this MultiLayerNetwork
 * @return Updater for MultiLayerNetwork
 */
public synchronized Updater getUpdater() {
  if (solver == null) {
    solver = new Solver.Builder().configure(conf()).listeners(getListeners()).model(this).build();
    solver.getOptimizer().setUpdater(UpdaterCreator.getUpdater(this));
  }
  return solver.getOptimizer().getUpdater();
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

solver = new Solver.Builder().configure(conf()).listeners(getListeners()).model(this).build();
solver.initOptimizer();

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

solver = new Solver.Builder().configure(conf()).listeners(getListeners()).model(this)
        .build();

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

solver = new Solver.Builder().configure(conf()).listeners(getListeners()).model(this)
        .build();

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

if (solver == null) {
  try (MemoryWorkspace wsO = Nd4j.getMemoryManager().scopeOutOfWorkspaces()) {
    solver = new Solver.Builder().configure(conf()).listeners(getListeners()).model(this).build();