Class  Description 

Bidirectional 
Bidirectional is a "wrapper" layer: it wraps any unidirectional RNN layer to make it bidirectional.
Note that multiple different modes are supported  these specify how the activations should be combined from the forward and backward RNN networks. 
Bidirectional.Builder  
LastTimeStep 
LastTimeStep is a "wrapper" layer: it wraps any RNN layer, and extracts out the last time step during forward pass,
and returns it as a row vector (per example).

SimpleRnn 
Simple RNN  aka "vanilla" RNN is the simplest type of recurrent neural network layer.

SimpleRnn.Builder 
Enum  Description 

Bidirectional.Mode 
This Mode enumeration defines how the activations for the forward and backward networks should be combined.
ADD: out = forward + backward (elementwise addition) MUL: out = forward * backward (elementwise multiplication) AVERAGE: out = 0.5 * (forward + backward) CONCAT: Concatenate the activations. Where 'forward' is the activations for the forward RNN, and 'backward' is the activations for the backward RNN. 