PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch.

Sami BARCHID

Last update: Jan 6, 2022

Related tags

Deep Learning snn-localization

Overview

snn-localization repo

PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch.

Install Dependencies

Originally runs on Python 3.6.13. Example of requirement.txt given. Includes:

conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
pip install albumentations==0.4.1 snntorch tensorboard

Usage

Run python train_localization_SG.py -h to see all options available.

Here's an example:

python train_localization_SG.py "data/oxford_iiit_pet" --experiment="Name_Of_Experiment" --height=176 --width=240 --timesteps=40 --epochs=100 --batch-size=4 --print-freq=100 --neural-coding=rate --lr=1e-3 --save-sample=42

A folder will be created at location experiments/Name_Of_Experiments with all data related to the experiment. It can include:

Tensorboard logs in experiments/Name_Of_Experiments/logs (val & train IoU metric and losses ).
Prediction samples from the test set at each epoch in experiments/Name_Of_Experiments/samples
Videos of SAM activations in experiments/Name_Of_Experiment/SAMs

In addition, a testing + additional metrics can be obtained (SAMs) by running the following command:

python test_localization_SG.py "data/oxford_iiit_pet" --experiment="Name_Of_Experiment" --height=176 --width=240 --timesteps=40 --epochs=100 --batch-size=4 --print-freq=100 --neural-coding=rate --lr=1e-3 --save-sample=42

You might also like...

A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.

Awesome Pretrained StyleGAN2 A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution. Note the readme is a

1.1k Dec 24, 2022

MEND: Model Editing Networks using Gradient Decomposition

MEND: Model Editing Networks using Gradient Decomposition Setup Environment This codebase uses Python 3.7.9. Other versions may work as well. Create a

141 Dec 2, 2022

Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

63 Sep 21, 2022

Complex-Valued Neural Networks (CVNN)Complex-Valued Neural Networks (CVNN)

Complex-Valued Neural Networks (CVNN) Done by @NEGU93 - J. Agustin Barrachina Using this library, the only difference with a Tensorflow code is that y

1 Nov 12, 2021

An implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.

Neural Attention Distillation This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep

84 Jan 4, 2023

Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"

Noisy Natural Gradient as Variational Inference PyTorch implementation of Noisy Natural Gradient as Variational Inference. Requirements Python 3 Pytor

119 Dec 2, 2022

PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset

Reference-Based-Sketch-Image-Colorization-ImageNet This is a PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization usin

11 Jul 28, 2022

Code release to accompany paper "Geometry-Aware Gradient Algorithms for Neural Architecture Search."

Geometry-Aware Gradient Algorithms for Neural Architecture Search This repository contains the code required to run the experiments for the DARTS sear

18 May 27, 2022

Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps

Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s

40 Dec 17, 2022

PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch.

Related tags

Overview

snn-localization repo

Install Dependencies

Usage

You might also like...

A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.

MEND: Model Editing Networks using Gradient Decomposition

Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Complex-Valued Neural Networks (CVNN)Complex-Valued Neural Networks (CVNN)

An implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.

Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"

PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset

Code release to accompany paper "Geometry-Aware Gradient Algorithms for Neural Architecture Search."

Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps

Owner

Sami BARCHID

Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021

Deep learning for spiking neural networks

A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.

Deep and online learning with spiking neural networks in Python

Spiking Neural Network for Computer Vision using SpikingJelly framework and Pytorch-Lightning

A PyTorch implementation of Learning to learn by gradient descent by gradient descent

"NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search".

ReLoss - Official implementation for paper "Relational Surrogate Loss Learning" ICLR 2022

With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function

Annotate datasets with a semi-trained or fully trained YOLOv5 model