How to use

EncodedGradientsAccumulator

in

org.deeplearning4j.optimize.solvers.accumulation

.gradientsAccumulator(new EncodedGradientsAccumulator(2, 1e-3))

protected void synchronize(int consumers) {
  synchronize(consumers, false);
}

public static int getOptimalBufferSize(Model model, int numWorkers, int queueSize) {
  return getOptimalBufferSize(model.params().length(), numWorkers, queueSize);
}

  public EncodedGradientsAccumulator build() {
    if (handler == null) {
      if (boundary == null)
        handler = new EncodingHandler(threshold);
      else
        handler = new EncodingHandler(threshold, boundary);
    }
    EncodedGradientsAccumulator accumulator =
            new EncodedGradientsAccumulator(parties, handler, initialMemory, queueSize, boundary);
    return accumulator;
  }
}

  synchronize(currentConsumers.get());
} catch (Exception e) {
  throwable.setIfFirst(e);

if (this.accumulator == null) {
  log.info("Creating new GradientsAccumulator instance");
  this.accumulator = new EncodedGradientsAccumulator(workers, 1e-3);

synchronize(currentConsumers.get(), true);

if (this.accumulator == null) {
  log.info("Creating new GradientsAccumulator instance");
  this.accumulator = new EncodedGradientsAccumulator(workers, 1e-3);

synchronize(currentConsumers.get(), true);