Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021

Overview

SNN_Calibration

Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021

Feature Comparison of SNN calibration:

Features SNN Direct Training ANN-SNN Conversion SNN Calibration
Accuract (T<100​) High Low High
Scalability to ImageNet Tiny Large Large
Training Speed Slow Fast Fast
# Required Data Full-set
(1.2M For ImageNet)
~1000 ~1000
Inference Speed Fast Slow Fast

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:

Dataset Model Random Seed Accuracy
CIFAR10 VGG16 1000 95.76
CIFAR10 ResNet-20 1000 95.68
CIFAR100 VGG16 1000 77.98
CIFAR100 ResNet-20 1000 76.52

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:

Architecture Datset T Random Seed Calibration Mean Acc Std.
VGG16 CIFAR10 16 1000 None 64.52 4.12
VGG16 CIFAR10 16 1000 Light 93.30 0.08
VGG16 CIFAR10 16 1000 Advanced 93.65 0.25
ResNet-20 CIFAR10 16 1000 None 67.88 3.63
ResNet-20 CIFAR10 16 1000 Light 93.89 0.20
ResNet-20 CIFAR10 16 1000 Advanced 94.33 0.12
VGG16 CIFAR100 16 1000 None 2.69 0.76
VGG16 CIFAR100 16 1000 Light 65.26 0.99
VGG16 CIFAR100 16 1000 Advanced 70.91 0.65
ResNet-20 CIFAR100 16 1000 None 39.27 2.85
ResNet-20 CIFAR100 16 1000 Light 73.89 0.15
ResNet-20 CIFAR100 16 1000 Advanced 74.48 0.16

Pre-training ANN on ImageNet

To be updaed

Owner
Yuhang Li
Research Intern at @SenseTime Group Limited
Yuhang Li
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

An-Introduction-to-Statistical-Learning This repository contains the exercises and its solution contained in the book An Introduction to Statistical L

2.1k Jan 02, 2023
Simple Pixelbot for Diablo 2 Resurrected written in python and opencv.

Simple Pixelbot for Diablo 2 Resurrected written in python and opencv. Obviously only use it in offline mode as it is against the TOS of Blizzard to use it in online mode!

468 Jan 03, 2023
R-Drop: Regularized Dropout for Neural Networks

R-Drop: Regularized Dropout for Neural Networks R-drop is a simple yet very effective regularization method built upon dropout, by minimizing the bidi

756 Dec 27, 2022
Torch-mutable-modules - Use in-place and assignment operations on PyTorch module parameters with support for autograd

Torch Mutable Modules Use in-place and assignment operations on PyTorch module p

Kento Nishi 7 Jun 06, 2022
Official Repsoitory for "Activate or Not: Learning Customized Activation." [CVPR 2021]

CVPR 2021 | Activate or Not: Learning Customized Activation. This repository contains the official Pytorch implementation of the paper Activate or Not

184 Dec 27, 2022
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.

Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized

Filippo Bianchi 249 Dec 21, 2022
Banglore House Prediction Using Flask Server (Python)

Banglore House Prediction Using Flask Server (Python) 🌐 Links 🌐 📂 Repo In this repository, I've implemented a Machine Learning-based Bangalore Hous

Dhyan Shah 1 Jan 24, 2022
The official homepage of the (outdated) COCO-Stuff 10K dataset.

COCO-Stuff 10K dataset v1.1 (outdated) Holger Caesar, Jasper Uijlings, Vittorio Ferrari Overview Welcome to official homepage of the COCO-Stuff [1] da

Holger Caesar 263 Dec 11, 2022
A New Open-Source Off-road Environment for Benchmark Generalization of Autonomous Driving

A New Open-Source Off-road Environment for Benchmark Generalization of Autonomous Driving Isaac Han, Dong-Hyeok Park, and Kyung-Joong Kim IEEE Access

13 Dec 27, 2022
Predicts an answer in yes or no.

Oui-ou-non-prediction Predicts an answer in 'yes' or 'no'. It is based on the game 'effeuiller la marguerite' in which the person plucks flower petals

Ananya Gupta 1 Jan 15, 2022
Emblaze - Interactive Embedding Comparison

Emblaze - Interactive Embedding Comparison Emblaze is a Jupyter notebook widget for visually comparing embeddings using animated scatter plots. It bun

CMU Data Interaction Group 77 Nov 24, 2022
Feature board for ERPNext

ERPNext Feature Board Feature board for ERPNext Development Prerequisites k3d kubectl helm bench Install K3d Cluster # export K3D_FIX_CGROUPV2=1 # use

Revant Nandgaonkar 16 Nov 09, 2022
Original Pytorch Implementation of FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation

FLAME Original Pytorch Implementation of FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation, accepted at the 17th IEEE Internation Co

Neelabh Sinha 19 Dec 17, 2022
[CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment

RADN [CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment [Paper on arXiv] Overview Update [2021/5/7] add codes for W

IIGROUP 53 Dec 28, 2022
code for the ICLR'22 paper: On Robust Prefix-Tuning for Text Classification

On Robust Prefix-Tuning for Text Classification Prefix-tuning has drawed much attention as it is a parameter-efficient and modular alternative to adap

Zonghan Yang 12 Nov 30, 2022
Official implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis https://arxiv.org/abs/2011.13775

CIPS -- Official Pytorch Implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis Requirements pip install -r requi

Multimodal Lab @ Samsung AI Center Moscow 201 Dec 21, 2022
Pytorch implementation of MixNMatch

MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation [Paper] Yuheng Li, Krishna Kumar Singh, Utkarsh Ojha, Yong Jae Le

910 Dec 30, 2022
TDN: Temporal Difference Networks for Efficient Action Recognition

TDN: Temporal Difference Networks for Efficient Action Recognition Overview We release the PyTorch code of the TDN(Temporal Difference Networks).

Multimedia Computing Group, Nanjing University 326 Dec 13, 2022
Exemplo de implementação do padrão circuit breaker em python

fast-circuit-breaker Circuit breakers existem para permitir que uma parte do seu sistema falhe sem destruir todo seu ecossistema de serviços. Michael

James G Silva 17 Nov 10, 2022
PyTorch implementation of the ExORL: Exploratory Data for Offline Reinforcement Learning

ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg

Denis Yarats 52 Jan 01, 2023