hxtorch.spiking.modules.hx_module_wrapper.HXModule
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class
hxtorch.spiking.modules.hx_module_wrapper.HXModule(experiment: Experiment, func: Union[Callable, torch.autograd.Function], execution_instance: Optional[ExecutionInstance] = None) Bases:
hxtorch.spiking.modules.hx_module.HXTorchFunctionMixin,hxtorch.spiking.modules.hx_module.HXHardwareEntityMixin,hxtorch.spiking.modules.hx_module.HXBaseExperimentModulePyTorch module supplying basic functionality for elements of SNNs that do have a representation on hardware
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__init__(experiment: Experiment, func: Union[Callable, torch.autograd.Function], execution_instance: Optional[ExecutionInstance] = None) → None - Parameters
experiment – Experiment to append layer to.
func – Callable function implementing the module’s forward functionality or a torch.autograd.Function implementing the module’s forward and backward operation. TODO: Inform about func args
execution_instance – Execution instance to place to.
Methods
__init__(experiment, func[, execution_instance])- param experiment
Experiment to append layer to.
Attributes
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extra_args: Tuple[Any]
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extra_kwargs: Dict[str, Any]
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training: bool
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