hxtorch.spiking.modules.synapse

Implementing SNN modules

Classes

Bounds(lower, torch.Tensor]] =, upper, …)	Class defining bounds of a finite value range and how to deal with the bounds in simulation. :param lower: The lower bound. :param upper: The upper bound. :param device: The device, the tensors containing the bounds are transfered to. :param hardware_aware: When set to True, the saturation effect is considered in the backward pass of the simulation; Else, the backward function is set to be the identity function and torch.clamp() is used instead of a surrogate. :param surrogate: Callable that implements a surrogate function for the clamp function. Is needed in case of of a hardware aware backpropagation.
EventPropSynapse(in_features, out_features, …)
LIFObservables	alias of hxtorch.spiking.handle.Handle_current_membrane_cadc_membrane_madc_spikes
Parameter([data, requires_grad])	A kind of Tensor that is to be considered a module parameter.
PlasticityRule(kernel, timer)
Projection(*prj_args, **prj_kwargs)	Base class for projections on BSS-2
ProjectionConnection(idx_pre, idx_post, weight)
Synapse(in_features, out_features, …[, …])	Synapse layer
SynapseHandle	alias of hxtorch.spiking.handle.Handle_graded_spikes