fangwei123456/spikingjelly

SpikingJelly is a PyTorch-native framework for modeling, training, and deploying spiking neural networks. A typical user builds a network from neuron, layer, and surrogate-gradient components, supplies event-based data, and trains or converts the model; analysis and visualization support inspection. The repository also provides accelerated kernels, memory and distributed execution, precision controls, pretrained model architectures, and hardware/framework exchange. Relationships below follow the README and the shown source references; unsampled subsystem internals are represented at their exact directory paths, without assuming unshown call chains.