code: @Override public float progress(){
      if(UKV.get(dest()) == null)return 0;
      DeepLearningModel m = UKV.get(dest());
      if (m != null && m.model_info()!=null ) {
        final float p = (float) Math.min(1, (m.epoch_counter / m.model_info().get_params().epochs));
        return cv_progress(p);
      }
      return 0;
    }
docs: Report the relative progress of building a Deep Learning model (measured by how many epochs are done)
  @return floating point number between 0 and 1