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
DvD-TD3: Diversity via Determinants for TD3 version

DvD-TD3: Diversity via Determinants for TD3 version The implementation of paper Effective Diversity in Population Based Reinforcement Learning. Instal

3 Feb 11, 2022
TensorFlow-LiveLessons - "Deep Learning with TensorFlow" LiveLessons

TensorFlow-LiveLessons Note that the second edition of this video series is now available here. The second edition contains all of the content from th

Deep Learning Study Group 830 Jan 03, 2023
A simple library that implements CLIP guided loss in PyTorch.

pytorch_clip_guided_loss: Pytorch implementation of the CLIP guided loss for Text-To-Image, Image-To-Image, or Image-To-Text generation. A simple libr

Sergei Belousov 74 Dec 26, 2022
Python Fanduel API (2021) - Lineup Automation

Southpaw is a python package that provides access to the Fanduel API. Optimize your DFS experience by programmatically updating your lineups, analyzin

Brandin Canfield 13 Jan 04, 2023
Unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"

Pytorch Implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG) This is the unofficial PyTorch Implementation of "DOLG: Single-St

DK 96 Jan 06, 2023
Machine learning library for fast and efficient Gaussian mixture models

This repository contains code which implements the Stochastic Gaussian Mixture Model (S-GMM) for event-based datasets Dependencies CMake Premake4 Blaz

Omar Oubari 1 Dec 19, 2022
HGCAE Pytorch implementation. CVPR2021 accepted.

Hyperbolic Graph Convolutional Auto-Encoders Accepted to CVPR2021 🎉 Official PyTorch code of Unsupervised Hyperbolic Representation Learning via Mess

Junho Cho 37 Nov 13, 2022
[CVPR2021] UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles

UAV-Human Official repository for CVPR2021: UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicle Paper arXiv Res

129 Jan 04, 2023
Few-NERD: Not Only a Few-shot NER Dataset

Few-NERD: Not Only a Few-shot NER Dataset This is the source code of the ACL-IJCNLP 2021 paper: Few-NERD: A Few-shot Named Entity Recognition Dataset.

THUNLP 319 Dec 30, 2022
Official code repository for the EMNLP 2021 paper

Integrating Visuospatial, Linguistic and Commonsense Structure into Story Visualization PyTorch code for the EMNLP 2021 paper "Integrating Visuospatia

Adyasha Maharana 23 Dec 19, 2022
PECOS - Prediction for Enormous and Correlated Spaces

PECOS - Predictions for Enormous and Correlated Output Spaces PECOS is a versatile and modular machine learning (ML) framework for fast learning and i

Amazon 387 Jan 04, 2023
A lightweight library to compare different PyTorch implementations of the same network architecture.

TorchBug is a lightweight library designed to compare two PyTorch implementations of the same network architecture. It allows you to count, and compar

Arjun Krishnakumar 5 Jan 02, 2023
An imperfect information game is a type of game with asymmetric information

DecisionHoldem An imperfect information game is a type of game with asymmetric information. Compared with perfect information game, imperfect informat

Decision AI 25 Dec 23, 2022
An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.

简体中文 | English News [2021-10-12] PaddleNLP 2.1版本已发布!新增开箱即用的NLP任务能力、Prompt Tuning应用示例与生成任务的高性能推理! 🎉 更多详细升级信息请查看Release Note。 [2021-08-22]《千言:面向事实一致性的生

6.9k Jan 01, 2023
Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch .

PyTorch-High-Res-Stereo-Depth-Estimation Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch. Stereo dep

Ibai Gorordo 26 Nov 24, 2022
Official repository for the paper F, B, Alpha Matting

FBA Matting Official repository for the paper F, B, Alpha Matting. This paper and project is under heavy revision for peer reviewed publication, and s

Marco Forte 404 Jan 05, 2023
A Python Library for Graph Outlier Detection (Anomaly Detection)

PyGOD is a Python library for graph outlier detection (anomaly detection). This exciting yet challenging field has many key applications, e.g., detect

PyGOD Team 757 Jan 04, 2023
Code for layerwise detection of linguistic anomaly paper (ACL 2021)

Layerwise Anomaly This repository contains the source code and data for our ACL 2021 paper: "How is BERT surprised? Layerwise detection of linguistic

6 Dec 07, 2022
PyTorch implementation of HDN(Homography Decomposition Networks) for planar object tracking

Homography Decomposition Networks for Planar Object Tracking This project is the offical PyTorch implementation of HDN(Homography Decomposition Networ

CaptainHook 48 Dec 15, 2022
Zero-Cost Proxies for Lightweight NAS

Zero-Cost-NAS Companion code for the ICLR2021 paper: Zero-Cost Proxies for Lightweight NAS tl;dr A single minibatch of data is used to score neural ne

SamsungLabs 108 Dec 20, 2022