Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks (TSSL-BP)

This repository is the official implementation of Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks.

Requirements

Dependencies and Libraries

• python 3.7
• pytorch
• torchvision

Installation

To install requirements:

pip install -r requirements.txt

Datasets

NMNIST: dataset, preprocessing

Training

Before running

Modify the data path and network settings in the config files.

Select the index of GPU in the main.py (0 by default)

Run the code

$ python main.py -config Networks/config_file.yaml
$ python main.py -config Networks/config_file.yaml -checkpoint checkpoint/ckpt.pth // load the checkpoint

Results

Our proposed method achieves the following performance on :

MNIST

Network Size	Time Steps	Epochs	Mean	Stddev	Best
15C5-P2-40C5-P2-300	5	100	99.50%	0.02%	99.53%

N-MNIST

Network Size	Time Steps	Epochs	Mean	Stddev	Best
12C5-P2-64C5-P2	100	100	99.35%	0.03%	99.40%
12C5-P2-64C5-P2	30	100	99.23%	0.05%	99.28%

Fashion MNIST

Network Size	Time Steps	Epochs	Mean	Stddev	Best
400 − 400	5	100	89.75%	0.03%	89.92%
32C5-P2-64C5-P2-1024	5	100	92.69%	0.09%	92.83%

CIFAR 10

Network Size	Time Steps	Epochs	Mean	Stddev	Best
96C3-256C3-P2-384C3-P2-384C3-256C3-1024-1024	5	150	88.98%	0.27%	89.37%
128C3-256C3-P2-512C3-P2-1024C3-512C3-1024-512	5	150	N/A	N/A	91.41%