MultiLayerNetwork net;
//two hidden layers of 3 neurons each
final int[] LSTMLayers = new int[]{3,3};
        NeuralNetConfiguration.ListBuilder list = new NeuralNetConfiguration.Builder()
                .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1)
                .learningRate(learningRate)
                .regularization(true).l2(0.0000001)
                .seed(76692)
                .weightInit(WeightInit.XAVIER)
                .updater(Updater.ADAM).adamMeanDecay(0.99).adamVarDecay(0.9999)
                .list();
        int layerIdx = 0;
        for (; layerIdx < LSTMLayers.length; layerIdx++) {
            list = list.layer(layerIdx, new GravesLSTM.Builder().nIn(nIn).nOut(LSTMLayers[layerIdx])
                    .activation("softsign").build());
            nIn = LSTMLayers[layerIdx];
        }
        list.layer(layerIdx++, new RnnOutputLayer.Builder(LossFunctions.LossFunction.MCXENT).activation("softmax")
                .nIn(nIn).nOut(nOut).build());
        MultiLayerConfiguration conf = list.pretrain(false).backprop(true).build();