hxtorch.spiking.modules

Modules

hxtorch.spiking.modules.batch_dropout	Implementing BatchDropout Module
hxtorch.spiking.modules.hx_module	Implementing the base module HXModule
hxtorch.spiking.modules.hx_module_wrapper	Implementing a module wrapper to wrap multiple modules as one
hxtorch.spiking.modules.input_neuron	Implementing input neuron module
hxtorch.spiking.modules.neuron	Implementing SNN modules
hxtorch.spiking.modules.sparse_synapse	Implementing SNN modules
hxtorch.spiking.modules.synapse	Implementing SNN modules
hxtorch.spiking.modules.types	Define module types

Classes

AELIF(size, experiment, leak, reset, …)	Layer of neurons with configurable dynamics up to adaptive exponential leaky integrate-and-fire complexity.
BatchDropout(size, dropout, experiment)	Batch dropout layer
EventPropLIF(size, experiment, leak, reset, …)
EventPropSynapse(in_features, out_features, …)
HXBaseExperimentModule(experiment)
HXModule(experiment, execution_instance, …)	PyTorch module supplying basic functionality for elements of SNNs that do have a representation on hardware
HXModuleWrapper(experiment, **modules)	Class to wrap HXModules
InputNeuron(size, experiment, …)	Spike source generating spikes at the times [ms] given in the spike_times array.
InputPopulation(size, experiment, …)	Base type for external input populations
LI(size, experiment, leak, tau_mem, tau_syn, …)	Layer of leaky integrator neurons
LIF(size, experiment, leak, reset, …)	Layer of leaky integrate-and-fire neurons.
NeuronExp(size, experiment, leak, reset, …)	Neuron layer with exponential Euler intergration scheme.
Population(size, experiment, …)	Base class for on-chip populations on BSS-2
Projection(in_features, out_features, …)	Base class for projections on BSS-2
ReadoutNeuronExp(size, experiment, leak, …)	Neuron layer with exponential Euler intergration scheme.
SparseSynapse(connections, experiment, …)	Sparse synapse layer
Synapse(in_features, out_features, …)	Synapse layer