Constructing input layers for the network

LSTM layers will have gated cells that are capable of capturing long-term dependencies, unlike regular RNN. Let's discuss how we can add a special LSTM layer in our network configuration. We can use a multilayer network or computation graph to create the model.

In this recipe, we will discuss how to create input layers for our LSTM neural network. In the following example, we will construct a computation graph and add custom layers to it.

How to do it...

1. Configure the neural network using ComputationGraph, as shown here:

ComputationGraphConfiguration.GraphBuilder builder = new NeuralNetConfiguration.Builder()
 .seed(RANDOM_SEED)
 .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT...