code: public static MultiLayerNetwork importKerasSequentialModelAndWeights(String modelHdf5Filename,
                                                                           int[] inputShape,
                                                                           boolean enforceTrainingConfig)
              throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
          KerasSequentialModel kerasModel = new KerasSequentialModel().modelBuilder().modelHdf5Filename(modelHdf5Filename)
                  .enforceTrainingConfig(enforceTrainingConfig).inputShape(inputShape).buildSequential();
          return kerasModel.getMultiLayerNetwork();
      }
docs: Load Keras Sequential model saved using model.save_model(...).
  
  @param modelHdf5Filename     path to HDF5 archive storing Keras Sequential model
  @param inputShape            optional input shape for models that come without such (e.g. notop = false models)
  @param enforceTrainingConfig whether to enforce training configuration options
  @return MultiLayerNetwork
  @throws IOException IO exception
  @see MultiLayerNetwork