CL-Gym: Full-Featured PyTorch Library for Continual Learning

Related tags

Deep LearningCL-Gym
Overview

CL-Gym: Full-Featured PyTorch Library for Continual Learning

CL-Gym is a small yet very flexible library for continual learning research and development.
Currently, CL-Gym is under heavy development and ready to be used by experienced researchers and engineers. However, the stable version will be ready for public release in August. Meanwhile, we welcome your feedback and suggestions on making CL-Gym better for researchers and developers!

How to Install

pip install cl-gym

Getting Started

Documentation: https://cl-gym.readthedocs.io/en/main
Short Demo: Open In Colab

Reference

@InProceedings{Mirzadeh_2021_CVPR,
   author = {Mirzadeh, Seyed Iman and Ghasemzadeh, Hassan},
   title = {CL-Gym: Full-Featured PyTorch Library for Continual Learning},
   booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
   month = {June}, year = {2021}, pages = {3621-3627} }
You might also like...
ElegantRL is featured with lightweight, efficient and stable, for researchers and practitioners.
ElegantRL is featured with lightweight, efficient and stable, for researchers and practitioners.

Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥

Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.

Trading Gym Trading Gym is an open-source project for the development of reinforcement learning algorithms in the context of trading. It is currently

Plug-n-Play Reinforcement Learning in Python with OpenAI Gym and JAX
Plug-n-Play Reinforcement Learning in Python with OpenAI Gym and JAX

coax is built on top of JAX, but it doesn't have an explicit dependence on the jax python package. The reason is that your version of jaxlib will depend on your CUDA version.

gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks.
gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks.

gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks. It is built on top of the OpenAI Gym toolkit.

Deep Q Learning with OpenAI Gym and Pokemon Showdown

pokemon-deep-learning An openAI gym project for pokemon involving deep q learning. Made by myself, Sam Little, and Layton Webber. This code captures g

Multi-objective gym environments for reinforcement learning.
Multi-objective gym environments for reinforcement learning.

MO-Gym: Multi-Objective Reinforcement Learning Environments Gym environments for multi-objective reinforcement learning (MORL). The environments follo

CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation (ACMMM'21 Oral Paper)
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation (ACMMM'21 Oral Paper)

CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation (ACMMM'21 Oral Paper) (Accepted for oral presentation at ACM

ICSS - Interactive Continual Semantic Segmentation

Presentation This repository contains the code of our paper: Weakly-supervised c

[CVPR 2022] CoTTA Code for our CVPR 2022 paper Continual Test-Time Domain Adaptation

CoTTA Code for our CVPR 2022 paper Continual Test-Time Domain Adaptation Prerequisite Please create and activate the following conda envrionment. To r

Comments
  • Missing Dataset PAMAP2

    Missing Dataset PAMAP2

    Dear Authors,

    I cannot find the link to your PAMAP2 Dataset as the link used in your implementation to download the dataset was not available. I have used the original PAMAP2 dataset from UCI link but it is not the same format as yours. Could you help me on this please? Thank you in advance for your help.

    opened by bonpagnakann 0
  • how to create my custom benchmark dataset ?

    how to create my custom benchmark dataset ?

    hello , how to create my custom benchmark dataset ? i am trying to use my own dataset for object detection task. i have two types of dataset and want to enter them in a sort of continual learning.

    but i am still new in the field of continual learning , and want to know how to config the benchmark

    looking forward tp your answer

    opened by alaa-shubbak 1
Releases(v1.0-beta.3)
  • v1.0-beta.3(Jun 23, 2021)

    Notes

    This is the first published version of CL-Gym. The current version needs more rigorous testing, and only then we will publish release candidates.

    Source code(tar.gz)
    Source code(zip)
Owner
Iman Mirzadeh
Graduate Research Assistant
Iman Mirzadeh
Face detection using deep learning.

Face Detection Docker Solution Using Faster R-CNN Dockerface is a deep learning face detector. It deploys a trained Faster R-CNN network on Caffe thro

Nataniel Ruiz 181 Dec 19, 2022
This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models are Pix2Pix, Pix2PixHD, CycleGAN and PointWise.

RGB2NIR_Experimental This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models

5 Jan 04, 2023
To prepare an image processing model to classify the type of disaster based on the image dataset

Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas

Bunny Saini 1 Jan 24, 2022
An implementation of the WHATWG URL Standard in JavaScript

whatwg-url whatwg-url is a full implementation of the WHATWG URL Standard. It can be used standalone, but it also exposes a lot of the internal algori

314 Dec 28, 2022
For auto aligning, cropping, and scaling HR and LR images for training image based neural networks

ImgAlign For auto aligning, cropping, and scaling HR and LR images for training image based neural networks Usage Make sure OpenCV is installed, 'pip

15 Dec 04, 2022
Multiple style transfer via variational autoencoder

ST-VAE Multiple style transfer via variational autoencoder By Zhi-Song Liu, Vicky Kalogeiton and Marie-Paule Cani This repo only provides simple testi

13 Oct 29, 2022
A simple python program that can be used to implement user authentication tokens into your program...

token-generator A simple python module that can be used by developers to implement user authentication tokens into your program... code examples creat

octo 6 Apr 18, 2022
face property detection pytorch

This is the face property train code of project face-detection-project

i am x 2 Oct 18, 2021
Project dự đoán giá cổ phiếu bằng thuật toán LSTM gồm: code train và code demo

Web predicts stock prices using Long - Short Term Memory algorithm Give me some start please!!! User interface image: Choose: DayBegin, DayEnd, Stock

Vo Thuong Truong Nhon 8 Nov 11, 2022
This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of Coordinate Independent Convolutional Networks.

Orientation independent Möbius CNNs This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of

Maurice Weiler 59 Dec 09, 2022
DI-smartcross - Decision Intelligence Platform for Traffic Crossing Signal Control

DI-smartcross DI-smartcross - Decision Intelligence Platform for Traffic Crossin

OpenDILab 213 Jan 02, 2023
Computational Methods Course at UdeA. Forked and size reduced from:

Computational Methods for Physics & Astronomy Book version at: https://restrepo.github.io/ComputationalMethods by: Sebastian Bustamante 2014/2015 Dieg

Diego Restrepo 11 Sep 10, 2022
Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Ali Aliev 15.3k Jan 05, 2023
RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation

RIFE RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation Ported from https://github.com/hzwer/arXiv2020-RIFE Dependencies NumPy

49 Jan 07, 2023
This repository contains a set of codes to run (i.e., train, perform inference with, evaluate) a diarization method called EEND-vector-clustering.

EEND-vector clustering The EEND-vector clustering (End-to-End-Neural-Diarization-vector clustering) is a speaker diarization framework that integrates

45 Dec 26, 2022
Implementation of SwinTransformerV2 in TensorFlow.

SwinTransformerV2-TensorFlow A TensorFlow implementation of SwinTransformerV2 by Microsoft Research Asia, based on their official implementation of Sw

Phan Nguyen 2 May 30, 2022
Code accompanying "Adaptive Methods for Aggregated Domain Generalization"

Adaptive Methods for Aggregated Domain Generalization (AdaClust) Official Pytorch Implementation of Adaptive Methods for Aggregated Domain Generalizat

Xavier Thomas 15 Sep 20, 2022
Pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021).

Pytorch code for SS-Net This is a pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021). Environment Code is tested

Sun Ran 1 May 18, 2022
Plenoxels: Radiance Fields without Neural Networks, Code release WIP

Plenoxels: Radiance Fields without Neural Networks Alex Yu*, Sara Fridovich-Keil*, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa UC Be

Alex Yu 2.3k Dec 30, 2022
Kindle is an easy model build package for PyTorch.

Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? wh

Jongkuk Lim 77 Nov 11, 2022