norse.torch.functional.lif_refrac_feed_forward_step

norse.torch.functional.lif_refrac_feed_forward_step#

norse.torch.functional.lif_refrac_feed_forward_step(input_tensor: torch.Tensor, state: norse.torch.functional.lif_refrac.LIFRefracFeedForwardState, p: norse.torch.functional.lif_refrac.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[torch.Tensor, norse.torch.functional.lif_refrac.LIFRefracFeedForwardState][source]#

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