qualia_plugin_snn.learningframework.SpikingJellyMultiStepTimeStepsInData module

Provide the SpikingJelly multi-step with timesteps in input data learningframework module.

class qualia_plugin_snn.learningframework.SpikingJellyMultiStepTimeStepsInData.SpikingJellyMultiStepTimeStepsInData

Bases: SpikingJellyTimeStepsInData

SpikingJelly multi-step with timesteps in data LearningFramework implementation extending SpikingJelly single-step.

class TrainerModule

Bases: TrainerModule

SpikingJelly multi-step with timesteps in data TrainerModule extending SpikingJelly single-step TrainerModule.

forward(x: Tensor) → Tensor

Forward pass for a Spiking Neural Network model with timesteps in input data in multi-step mode.

First calls SpikingJelly’s reset on the model to reset neurons potentials. Call qualia_plugin_snn.learningmodel.pytorch.SNN.SNN.forward() for each timestep of the input data. Finally, average the output of the model over the timesteps.

Parameters:

x (Tensor) – Input data with timestep dimension in [N, T, C, S] or [N, T, C, H, W] order

Returns:

Output predictions

Raises:

ValueError – when the input data does not have the correct number of dimenions or the timestep dimension does not match qualia_plugin_snn.learningmodel.pytorch.SNN.SNN.timesteps

Return type:

Tensor