norse.torch.functional.lif_mc_feed_forward_step(input_tensor: Tensor, state: LIFFeedForwardState, g_coupling: Tensor, p: LIFParameters = (tensor(200.), tensor(100.), tensor(0.), tensor(1.), tensor(0.), 'super', tensor(100.)), dt: float = 0.001) Tuple[Tensor, LIFFeedForwardState][source]#

Computes a single euler-integration feed forward step of a LIF multi-compartment neuron-model.

input_tensor (torch.Tensor): the (weighted) input spikes at the

current time step

s (LIFFeedForwardState): current state of the neuron g_coupling (torch.Tensor): conductances between the neuron compartments p (LIFParameters): neuron parameters dt (float): Integration timestep to use