code: public static SparkDl4jMultiLayer importElephasSequentialModelAndWeights(JavaSparkContext sparkContext,
                                                                       String modelHdf5Filename)
              throws IOException, UnsupportedKerasConfigurationException, InvalidKerasConfigurationException {
          MultiLayerNetwork model = KerasModelImport.importKerasSequentialModelAndWeights(
                  modelHdf5Filename, true);
  
          Map<String, Object> distributedProperties = distributedTrainingMap(modelHdf5Filename);
          TrainingMaster tm = getTrainingMaster(distributedProperties);
  
          return new SparkDl4jMultiLayer(sparkContext, model, tm);
      }
docs: Load Elephas model stored using model.save(...) in case that the underlying Keras
  model is a functional `Sequential` instance, which corresponds to a DL4J SparkDl4jMultiLayer.
  
  @param sparkContext                            Java SparkContext
  @param modelHdf5Filename                       Path to HDF5 archive storing Elephas model
  @return SparkDl4jMultiLayer                    Spark computation graph
  
  @throws IOException                            IO exception
  @throws InvalidKerasConfigurationException     Invalid Keras config
  @throws UnsupportedKerasConfigurationException Unsupported Keras config
  @see SparkDl4jMultiLayer