[ML Reproducibility Challenge:] Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks (TSSL-BP)
This repository is for the reproduction of Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks.
Instructions from https://github.com/stonezwr/TSSL-BP/
- python 3.7
- pytorch
- torchvision
To install requirements:
pip install -r requirements.txt
Modify the data path and network settings in the config files.
Select the index of GPU in the main.py (0 by default)
$ python main.py -config Networks/config_file.yaml
$ python main.py -config Networks/config_file.yaml -checkpoint checkpoint/ckpt.pth // load the checkpoint
Performance comparison between original paper and this reproduction:
Paper | Network Size | Time Steps | Epochs | Mean | Stddev | Best |
---|---|---|---|---|---|---|
Original paper | 15C5-P2-40C5-P2-300 | 5 | 100 | 99.50% | 0.02% | 99.53% |
Reproduction | 15C5-P2-40C5-P2-300 | 5 | 100 | 99.40% | 0.04% | 99.47% |
Paper | Network Size | Time Steps | Epochs | Mean | Stddev | Best |
---|---|---|---|---|---|---|
Original paper | 96C3-256C3-P2-384C3-P2-384C3-256C3-1024-1024 | 5 | 150 | 88.98% | 0.27% | 89.22% |
Reproduction | 96C3-256C3-P2-384C3-P2-384C3-256C3-1024-1024 | 5 | 150 | 88.96% | 0.10% | 89.07% |
Paper | Network Size | Time Steps | Epochs | Mean | Stddev | Best |
---|---|---|---|---|---|---|
Original paper | 128C3-256C3-P2-512C3-P2-1024C3-512C3-1024-512 | 5 | 150 | N/A | N/A | 91.41% |
Reproduction | 128C3-256C3-P2-512C3-P2-1024C3-512C3-1024-512 | 5 | 150 | N/A | N/A | 89.61% |