Implementing an LSTM Model

We will extend our RNN model to be able to use longer sequences by introducing the LSTM unit in this recipe.

Getting ready

Long Short Term Memory(LSTM) is a variant of the traditional RNN.LSTM is a way to address the vanishing/exploding gradient problem that variable length RNNs have.To address this issue, LSTM cells introduce an internal forget gate,which can modify a flow of information from one cell to the next. To conceptualize how this works, we will walk through an unbiased version of LSTM one equation at a time.The first step is the same as for the regular RNN:

In order to figure out which values we want to forget or pass through, we will evaluate candidate values as follows.These values are often referred to as the memory cells:

Now we modify the candidate memory cells by a forget matrix, which is calculated as follows:

We now combine the forget memory with the prior memory step and add it to the candidate memory cells to arrive at the new memory values:

Now...