hxtorch.spiking.modules.hx_module.HXBaseExperimentModule

class hxtorch.spiking.modules.hx_module.HXBaseExperimentModule(experiment: Experiment)

Bases: torch.nn.modules.module.Module

__init__(experiment: Experiment) → None

Parameters: experiment – Experiment to append layer to.

Methods

`__init__`(experiment)	param experiment Experiment to append layer to.
`exec_forward`(input, output, hw_map)	Inject hardware observables into TensorHandles or execute forward in mock-mode.
`extra_repr`()	Add additional information
`forward`(*input)	Forward method registering layer operation in given experiment.

Attributes

`descriptor`
`func`	Getter for function assigned to the module

descriptor = None

exec_forward(input: Union[Tuple[TensorHandle], TensorHandle], output: TensorHandle, hw_map: Dict[grenade.network.PopulationsDescriptor, Any]) → None: Inject hardware observables into TensorHandles or execute forward in mock-mode.

extra_repr() → str: Add additional information

forward(*input: Union[Tuple[hxtorch.spiking.handle.TensorHandle], hxtorch.spiking.handle.TensorHandle]) → hxtorch.spiking.handle.TensorHandle 

Forward method registering layer operation in given experiment. Input and output references will hold corresponding data as soon as ‘hxtorch.run’ in executed.

Parameters: input – Reference to TensorHandle holding data tensors as soon as required.
Returns: Returns a Reference to TensorHandle holding result data associated with this layer after ‘hxtorch.run’ is executed.

abstract property func

Getter for function assigned to the module

Returns: Returns the function assigned to the module.

output_type: alias of hxtorch.spiking.handle.TensorHandle

training: bool