def __init__(self,
size,
initialHistory=gpu.zeros((0, 0)),
baseLayerClass=SigmoidLayer,
connectionClass=FullConnection):
"""
A recurrent layer extends the activation layer by adding a full recurrent
connection from the output of the layer to its input, delayed by a
timestep.
"""
# Properly inherit the AbstractLayer
AbstractLayer.__init__(self)
# Extract the layerSize from the provided activation layer
self.baseLayer = baseLayerClass(size)
self.layerSize = size
self.historyLayer = HistoryLayer(self.layerSize, initialHistory)
# A recurrent layer has an input port, history port and output port
self.input = self.baseLayer.input
self.output = self.baseLayer.output
# Make two connections - the recurrent connection to the history and a connection from
# the history to the activationLayer
self.recurrentConnection = connectionClass(self.output,
self.historyLayer.input)
self.historyConnection = IdentityConnection(self.historyLayer.output,
self.input)
# Keep track of how many timesteps there were, and the initial history incase of reset
self.timestep = 0
