SNN_Calibration

Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021

Feature Comparison of SNN calibration:

Requirements

Pytorch 1.8

For ImageNet experiments, please be sure that you can initialize distributed environments

For CIFAR experiments, one GPU would suffice.

Pre-training ANN on CIFAR10&100

Train an ANN model with main_train.py

python CIFAR/main_train.py --dataset CIFAR10 --arch VGG16 --dpath PATH/TO/DATA --usebn

Pre-trained results:

SNN Calibration on CIFAR10&100

Calibrate an SNN with main_calibration.py.

python CIFAR/main_calibration.py --dataset CIFAR10 --arch VGG16 --T 16 --usebn --calib advanced --dpath PATH/TO/DATA

--T is the time step, --calib is the calibration method, please use none, light, advanced for experiments.

The calibration will run for 5 times, and return the mean accuracy as well as the standard deviation.

Example results:

Pre-training ANN on ImageNet

To be updaed