norse.torch.functional.lif_refrac_feed_forward_step

norse.torch.functional.lif_refrac_feed_forward_step(input_tensor: Tensor, state: LIFRefracFeedForwardState, p: LIFRefracParameters = LIFRefracParameters(lif=LIFParameters(tau_syn_inv=tensor(200.), tau_mem_inv=tensor(100.), v_leak=tensor(0.), v_th=tensor(1.), v_reset=tensor(0.), method='super', alpha=tensor(100.)), rho_reset=tensor(5.)), dt: float = 0.001) → Tuple[Tensor, LIFRefracFeedForwardState]

Computes a single euler-integration step of a feed forward

LIF neuron-model with a refractory period.

Parameters:

input_tensor (torch.Tensor): the input spikes at the current time step s (LIFRefracFeedForwardState): state at the current time step p (LIFRefracParameters): parameters of the lif neuron dt (float): Integration timestep to use