norse.torch.functional.iaf.iaf_feed_forward_step(input_tensor: torch.Tensor, state: norse.torch.functional.iaf.IAFFeedForwardState, p: norse.torch.functional.iaf.IAFParameters = IAFParameters(v_th=tensor(1.), v_reset=tensor(0.), method='super', alpha=tensor(100.)), dt: float = 0.001) Tuple[torch.Tensor, norse.torch.functional.iaf.IAFFeedForwardState][source]

Feedforward step of an integrate-and-fire neuron, computing a single step

\[\dot{v} = v\]

together with the jump condition

\[z = \Theta(v - v_{\text{th}})\]

and transition equation

\[v = (1-z) v + z v_{\text{reset}}\]

input_tensor (torch.Tensor): the input spikes at the current time step state (IAFFeedForwardState): current state of the LIF neuron p (IAFParameters): parameters of a leaky integrate and fire neuron dt (float): Integration timestep to use (unused, but added for compatibility)