hxtorch.spiking.modules.sparse_synapse.Projection

class hxtorch.spiking.modules.sparse_synapse.Projection(in_features: int, out_features: int, experiment: Experiment, func: Union[Callable, torch.autograd.Function], execution_instance: ExecutionInstance)

Bases: hxtorch.spiking.modules.hx_module.HXModule

Base class for projections on BSS-2

__init__(in_features: int, out_features: int, experiment: Experiment, func: Union[Callable, torch.autograd.Function], execution_instance: ExecutionInstance) → None
Parameters

  • experiment – Experiment to append layer to.

  • in_features – Size of input dimension.

  • out_features – Size of output dimension.

  • 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__(in_features, out_features, …)

param experiment

Experiment to append layer to.

extra_repr()

Add additional information

Attributes

extra_args: Tuple[Any]
extra_kwargs: Dict[str, Any]
extra_repr() → str

Add additional information

in_features: int
out_features: int
training: bool
weight: torch.Tensor