code: @Override
    public void lcompute() {
      _res = new DeepLearningTask(_model_info, _sync_fraction);
      _res.setCompleter(this);
      _res.asyncExec(0, _fr, true /*run_local*/);
    }
docs: Do the local computation: Perform one DeepLearningTask (with run_local=true) iteration.
  Pass over all the data (will be replicated in dfork() here), and use _sync_fraction random rows.
  This calls DeepLearningTask's reduce() between worker threads that update the same local model_info via Hogwild!
  Once the computation is done, reduce() will be called