norse.torch.module.lif

A very popular neuron model that combines a norse.torch.module.leaky_integrator with spike thresholds to produce events (spikes).

See norse.torch.functional.lif for more information.

Classes

LIF([p])	A neuron layer that wraps a LIFCell in time such that the layer keeps track of temporal sequences of spikes. After application, the layer returns a tuple containing (spikes from all timesteps, state from the last timestep).
LIFCell([p])	Module that computes a single euler-integration step of a leaky integrate-and-fire (LIF) neuron-model without recurrence and without time.
LIFRecurrent(input_size, hidden_size[, p])	A neuron layer that wraps a LIFRecurrentCell in time such that the layer keeps track of temporal sequences of spikes. After application, the module returns a tuple containing (spikes from all timesteps, state from the last timestep).
LIFRecurrentCell(input_size, hidden_size[, p])	Module that computes a single euler-integration step of a leaky integrate-and-fire (LIF) neuron-model with recurrence but without time.