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
Setup freqtrade/freqUI on Heroku

UNMAINTAINED - REPO MOVED TO https://github.com/p-zombie/freqtrade Creating the app git clone https://github.com/joaorafaelm/freqtrade.git && cd freqt

João 51 Aug 29, 2022
Retrieval.pytorch - The code we used in [2020 DIGIX]

Retrieval.pytorch - The code we used in [2020 DIGIX]

Guo-Hua Wang 2 Feb 07, 2022
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens

TensorLayer Community 7.1k Dec 27, 2022
Camera calibration & 3D pose estimation tools for AcinoSet

AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild Daniel Joska, Liam Clark, Naoya Muramatsu, Ricardo Jericevich, Fre

African Robotics Unit 42 Nov 16, 2022
Answer a series of contextually-dependent questions like they may occur in natural human-to-human conversations.

SCAI-QReCC-21 [leaderboards] [registration] [forum] [contact] [SCAI] Answer a series of contextually-dependent questions like they may occur in natura

19 Sep 28, 2022
Unofficial implementation of MLP-Mixer: An all-MLP Architecture for Vision

MLP-Mixer: An all-MLP Architecture for Vision This repo contains PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision. Usage : impo

Rishikesh (ऋषिकेश) 175 Dec 23, 2022
Language model Prompt And Query Archive

LPAQA: Language model Prompt And Query Archive This repository contains data and code for the paper How Can We Know What Language Models Know? Install

127 Dec 20, 2022
This is a Python Module For Encryption, Hashing And Other stuff

EnroCrypt This is a Python Module For Encryption, Hashing And Other Basic Stuff You Need, With Secure Encryption And Strong Salted Hashing You Can Do

5 Sep 15, 2022
Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders"

DECA Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders". All the code is writte

23 Dec 01, 2022
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding (AAAI 2020) - PyTorch Implementation

Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding PyTorch implementation for the Scalable Attentive Sentence-Pair Modeling vi

Microsoft 25 Dec 02, 2022
High-fidelity 3D Model Compression based on Key Spheres

High-fidelity 3D Model Compression based on Key Spheres This repository contains the implementation of the paper: Yuanzhan Li, Yuqi Liu, Yujie Lu, Siy

5 Oct 11, 2022
This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust.

Demo BERT ONNX pipeline written in rust This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust. R

Xavier Tao 14 Dec 17, 2022
Hierarchical Time Series Forecasting with a familiar API

scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work

Carlo Mazzaferro 204 Dec 17, 2022
Deploy a ML inference service on a budget in less than 10 lines of code.

BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end.

1.3k Dec 25, 2022
[ArXiv 2021] Data-Efficient Instance Generation from Instance Discrimination

InsGen - Data-Efficient Instance Generation from Instance Discrimination Data-Efficient Instance Generation from Instance Discrimination Ceyuan Yang,

GenForce: May Generative Force Be with You 93 Dec 25, 2022
Source code for the paper: Variance-Aware Machine Translation Test Sets (NeurIPS 2021 Datasets and Benchmarks Track)

Variance-Aware-MT-Test-Sets Variance-Aware Machine Translation Test Sets License See LICENSE. We follow the data licensing plan as the same as the WMT

NLP2CT Lab, University of Macau 5 Dec 21, 2021
Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad to your characters in Modo.

Applicator Kit for Modo Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad with a TrueDepth camera to

Andrew Buttigieg 3 Aug 24, 2021
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

Tony JiHyun Kim 119 Dec 02, 2022
Official implementation of Self-supervised Graph Attention Networks (SuperGAT), ICLR 2021.

SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor

Dongkwan Kim 127 Dec 28, 2022
Official implementation of the MM'21 paper Constrained Graphic Layout Generation via Latent Optimization

[MM'21] Constrained Graphic Layout Generation via Latent Optimization This repository provides the official code for the paper "Constrained Graphic La

Kotaro Kikuchi 73 Dec 27, 2022