code: public static MultiLayerNetwork importKerasSequentialModelAndWeights(String modelJsonFilename,
                                                                           String weightsHdf5Filename,
                                                                           boolean enforceTrainingConfig)
              throws IOException, InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
          KerasSequentialModel kerasModel = new KerasSequentialModel().modelBuilder().modelJsonFilename(modelJsonFilename)
                  .weightsHdf5FilenameNoRoot(weightsHdf5Filename).enforceTrainingConfig(enforceTrainingConfig)
                  .buildSequential();
          return kerasModel.getMultiLayerNetwork();
      }
docs: Load Keras Sequential model for which the configuration and weights were
  saved separately using calls to model.to_json() and model.save_weights(...).
  
  @param modelJsonFilename     path to JSON file storing Keras Sequential model configuration
  @param weightsHdf5Filename   path to HDF5 archive storing Keras model weights
  @param enforceTrainingConfig whether to enforce training configuration options
  @return MultiLayerNetwork
  @throws IOException IO exception
  @see MultiLayerNetwork