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

Related tags

Deep Learningrockpool
Overview

Rockpool

PyPI - Package Conda Documentation Status PyPI - Python Version Black - formatterDOI

Noodle

Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build networks, simulate, train and test them, deploy them either in simulation or on event-driven neuromorphic compute hardware. Rockpool provides layers with a number of simulation backends, including Brian2, NEST, Torch, JAX, Numba and raw numpy. Rockpool is designed to make machine learning based on SNNs easier. It is not designed for detailed simulation of biological networks.

Documentation and getting started

The best place to start with Rockpool is the documentation, which contains several tutorials and getting started guides.

The documentation is hosted online: https://rockpool.ai/

Installation instructions

Use pip to install Rockpool and required dependencies

$ pip install rockpool --user

The --user option installs the package only for the current user.

If you want to install all the extra dependencies required for Brian, PyTorch and Jax layers, use the command

$ pip install rockpool[all] --user

NEST-backed modules

The NEST simulator cannot be installed using pip. Please see the documentation for NEST at [https://nest-simulator.readthedocs.io/en/latest/] for instructions on how to get NEST running on your system.

License

Rockpool is released under a AGPL license. Commercial licenses are available on request.

Contributing

Fork the public repository at https://github.com/SynSense/rockpool, then clone your fork.

$ git clone https://github.com/your-fork-location/rockpool.git rockpool

Install the package in development mode using pip

$ cd rockpool
$ pip install -e . --user

or

$ pip install -e .[all] --user

The main branch is development. You should commit your modifications to a new feature branch.

$ git checkout -b feature/my-feature develop
...
$ git commit -m 'This is a verbose commit message.'

Then push your new branch to your repository

$ git push -u origin feature/my-feature

When you're finished with your modifications, make a merge request on github.com, from your branch in your fork to https://github.com/SynSense/rockpool.

Owner
SynSense
SynSense
Official code of ICCV2021 paper "Residual Attention: A Simple but Effective Method for Multi-Label Recognition"

CSRA This is the official code of ICCV 2021 paper: Residual Attention: A Simple But Effective Method for Multi-Label Recoginition Demo, Train and Vali

163 Dec 22, 2022
Open CV - Convert a picture to look like a cartoon sketch in python

Use the video https://www.youtube.com/watch?v=k7cVPGpnels for initial learning.

Sammith S Bharadwaj 3 Jan 29, 2022
Training neural models with structured signals.

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

955 Jan 02, 2023
HCQ: Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval

HCQ: Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval [toc] 1. Introduction This repository provides the code for our paper at

13 Dec 08, 2022
SAS: Self-Augmentation Strategy for Language Model Pre-training

SAS: Self-Augmentation Strategy for Language Model Pre-training This repository

Alibaba 5 Nov 02, 2022
PyTorch implementation for the paper Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime

Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n

Prarthana Bhattacharyya 5 Nov 08, 2022
A Partition Filter Network for Joint Entity and Relation Extraction EMNLP 2021

EMNLP 2021 - A Partition Filter Network for Joint Entity and Relation Extraction

zhy 127 Jan 04, 2023
Yolo ros - YOLO-ROS for HUAWEI ATLAS200

YOLO-ROS YOLO-ROS for NVIDIA YOLO-ROS for HUAWEI ATLAS200, please checkout for b

ChrisLiu 5 Oct 18, 2022
Re-implementation of the Noise Contrastive Estimation algorithm for pyTorch, following "Noise-contrastive estimation: A new estimation principle for unnormalized statistical models." (Gutmann and Hyvarinen, AISTATS 2010)

Noise Contrastive Estimation for pyTorch Overview This repository contains a re-implementation of the Noise Contrastive Estimation algorithm, implemen

Denis Emelin 42 Nov 24, 2022
The official implementation of Equalization Loss for Long-Tailed Object Recognition (CVPR 2020) based on Detectron2

Equalization Loss for Long-Tailed Object Recognition Jingru Tan, Changbao Wang, Buyu Li, Quanquan Li, Wanli Ouyang, Changqing Yin, Junjie Yan ⚠️ We re

Jingru Tan 197 Dec 25, 2022
Code for MarioNette: Self-Supervised Sprite Learning, in NeurIPS 2021

MarioNette | Webpage | Paper | Video MarioNette: Self-Supervised Sprite Learning Dmitriy Smirnov, Michaël Gharbi, Matthew Fisher, Vitor Guizilini, Ale

Dima Smirnov 28 Nov 18, 2022
[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore

[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6101 of Semester 1, AY2021-2022, starting from 08/2021. The instructors of

AccSrd 1 Sep 22, 2022
Put blind watermark into a text with python

text_blind_watermark Put blind watermark into a text. Can be used in Wechat dingding ... How to Use install pip install text_blind_watermark Alice Pu

郭飞 164 Dec 30, 2022
dualPC.R contains the R code for the main functions.

dualPC.R contains the R code for the main functions. dualPC_sim.R contains an example run with the different PC versions; it calls dualPC_algs.R whic

3 May 30, 2022
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

Yolo v4, v3 and v2 for Windows and Linux (neural networks for object detection) Paper YOLO v4: https://arxiv.org/abs/2004.10934 Paper Scaled YOLO v4:

Alexey 20.2k Jan 09, 2023
Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch

PyGAS: Auto-Scaling GNNs in PyG PyGAS is the practical realization of our G NN A uto S cale (GAS) framework, which scales arbitrary message-passing GN

Matthias Fey 139 Dec 25, 2022
Spectralformer: Rethinking hyperspectral image classification with transformers

The code in this toolbox implements the "Spectralformer: Rethinking hyperspectral image classification with transformers". More specifically, it is detailed as follow.

Danfeng Hong 104 Jan 04, 2023
A Pytorch implementation of "Manifold Matching via Deep Metric Learning for Generative Modeling" (ICCV 2021)

Manifold Matching via Deep Metric Learning for Generative Modeling A Pytorch implementation of "Manifold Matching via Deep Metric Learning for Generat

69 Dec 10, 2022
Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps[AAAI2021]

Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps Here is the code for ssbassline model. We also provide OCR results/features/mode

ZephyrZhuQi 51 Nov 18, 2022
Retina blood vessel segmentation with a convolutional neural network

Retina blood vessel segmentation with a convolution neural network (U-net) This repository contains the implementation of a convolutional neural netwo

Orobix 1.2k Jan 06, 2023