Python Reinforcement-training Resources

A list of papers regarding generalization in (deep) reinforcement learning

Although Evolutionary Algorithms have shown to result in interesting behavior, they focus on learning across generations whereas behavior could also be learned during ones lifetime.

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.

Cockpit is a visual and statistical debugger specifically designed for deep learning!

Accelerating Reinforcement Learning with Learned Skill Priors [Project Website] [Paper] Karl Pertsch1, Youngwoon Lee1, Joseph Lim1 1CLVR Lab, Universi

RIIT Our open-source code for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implement and standard

PlenOctrees Official Repo: NeRF-SH training and conversion This repository contains code to train NeRF-SH and to extract the PlenOctree, constituting

Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te

ST3D Code release for the paper ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection, CVPR 2021 Authors: Jihan Yang*, Shaoshu

Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1

Training-code-of-STM This repository fully reproduces Space-Time Memory Networks Performance on Davis17 val set&Weights backbone training stage traini

mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms. It provides easily interchangeable modeling and planning components, and a set of utility functions that allow writing model-based RL algorithms with only a few lines of code.

The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.

Labelled data remains a scarce resource in many practical NLP scenarios. This is especially the case when working with resource-poor languages (or text domains), or when using task-specific labels without pre-existing datasets. The only available option is often to collect and annotate texts by hand, which is expensive and time-consuming.

Generating Persona Consistent Dialogues by Exploiting Natural Language Inference Source code for RCDG model in AAAI20 Generating Persona Consistent Di

BNN - BN = ? Training Binary Neural Networks without Batch Normalization Codes for this paper BNN - BN = ? Training Binary Neural Networks without Bat

BMW-Anonymization-Api Data privacy and individuals’ anonymity are and always have been a major concern for data-driven companies. Therefore, we design

Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning

PLBART Code pre-release of our work, Unified Pre-training for Program Understanding and Generation accepted at NAACL 2021. Note. A detailed documentat

Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This

Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (

FFD Source Code Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face M

Proto-RL: Reinforcement Learning with Prototypical Representations This is a PyTorch implementation of Proto-RL from Reinforcement Learning with Proto

Geometry-aware Instance-reweighted Adversarial Training This repository provides codes for Geometry-aware Instance-reweighted Adversarial Training (ht

Deep-Reinforcement-Learning-in-Stock-Trading Using deep actor-critic model to learn best strategies in pair trading Abstract Partially observed Markov

Deep Trading Agent Deep Reinforcement Learning based Trading Agent for Bitcoin using DeepSense Network for Q function approximation. For complete deta

Reinforcement Learning for Finance We apply reinforcement learning for stock trading. Fetch Data Example import utils # fetch symbols from yahoo fina

Reinforcement Learning for Automated Trading This thesis has been realized for the obtention of the Master's in Mathematical Engineering at the Polite

This is the original implementation of our paper, A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem (arXiv:1706.1

Trading Using Q-Learning In this project, I will present an adaptive learning model to trade a single stock under the reinforcement learning framework

Reinforcement-trading This project uses Reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can

A tour through tensorflow with financial data I present several models ranging in complexity from simple regression to LSTM and policy networks. The s

qtrader Reinforcement Learning for Portfolio Management Why Reinforcement Learning? Learns the optimal action, rather than models the market. Adaptive

TradzQAI Trading environnement for RL agents, backtesting and training. Live session with coinbasepro-python is finaly arrived ! Available sessions: L

...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on

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

TradingGym TradingGym is a toolkit for training and backtesting the reinforcement learning algorithms. This was inspired by OpenAI Gym and imitated th

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

Pre-training CharacterBERT (and BERT) This is a repository for pre-training BERT and CharacterBERT. DISCLAIMER: The code was largely adapted from an o

MARL Tricks Our codes for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implemented and standardiz

This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.

SimplePose Code and pre-trained models for our paper, “Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation”, a

spatial-action-maps Update: Please see our new spatial-intention-maps repository, which extends this work to multi-agent settings. It contains many ne

Adversarial Training Against Location-Optimized Adversarial Patches arXiv | Paper | Code | Video | Slides Code for the paper: Sukrut Rao, David Stutz,

CPT: Efficient Deep Neural Network Training via Cyclic Precision Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin Accep

Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st

higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi

Introduction This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code her

Somoclu Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs, it is able to rely on MPI for distributing

Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage

BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith

Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

TensorTrade: Trade Efficiently with Reinforcement Learning TensorTrade is still in Beta, meaning it should be used very cautiously if used in producti

Contrast to Divide: self-supervised pre-training for learning with noisy labels This is an official implementation of "Contrast to Divide: self-superv

PG-MORL This repository contains the implementation for the paper Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Contro

Overview This is a re-implementation of the model-based RL algorithm MBPO in pytorch as described in the following paper: When to Trust Your Model: Mo

PWLQ Updates 2020/07/16 - We are working on getting permission from our institution to release our source code. We will release it once we are granted

spatial-intention-maps This code release accompanies the following paper: Spatial Intention Maps for Multi-Agent Mobile Manipulation Jimmy Wu, Xingyua

New version release：https://github.com/oh-my-ocr/text_renderer Text Renderer Generate text images for training deep learning OCR model (e.g. CRNN). Su

TextRecognitionDataGenerator A synthetic data generator for text recognition What is it for? Generating text image samples to train an OCR software. N

English | 简体中文 Introduction PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and a

Adaptive Transformers in RL Official implementation of Adaptive Transformers in RL In this work we replicate several results from Stabilizing Transfor

Dataset Cartography Code for the paper Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics at EMNLP 2020. This repository cont

Training GANs with Stronger Augmentations via Contrastive Discriminator (ICLR 2021) This repository contains the code for reproducing the paper: Train

This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code here will be included in upstream Pytorch eventually. The intention of Apex is to make up-to-date utilities available to users as quickly as possible.

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

PLBART Code pre-release of our work, Unified Pre-training for Program Understanding and Generation accepted at NAACL 2021. Note. A detailed documentat

PGPElib A mini library for Policy Gradients with Parameter-based Exploration [1] and friends. This library serves as a clean re-implementation of the

Crafter Open world survival environment for reinforcement learning. Highlights Crafter is a procedurally generated 2D world, where the agent finds foo

UP-DETR: Unsupervised Pre-training for Object Detection with Transformers This is the official PyTorch implementation and models for UP-DETR paper: @a

Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho

Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain

English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

SafeOpt - Safe Bayesian Optimization This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1], [2]. It also p

ChainerRL ChainerRL is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Ch

Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml

Dopamine Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grok

TRFL TRFL (pronounced "truffle") is a library built on top of TensorFlow that exposes several useful building blocks for implementing Reinforcement Le

Tensorforce: a TensorFlow library for applied reinforcement learning Introduction Tensorforce is an open-source deep reinforcement learning framework,

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning. TF-Agents makes implementing, de

Applied Reinforcement Learning @ Facebook Overview ReAgent is an open source end-to-end platform for applied reinforcement learning (RL) developed and

Stable Baselines Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a

Status: Maintenance (expect bug fixes and minor updates) Baselines OpenAI Baselines is a set of high-quality implementations of reinforcement learning

Reproduce, Automate, Scale your data science. Welcome to Polyaxon, a platform for building, training, and monitoring large scale deep learning applica

Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built

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

TNT TNT is a library providing powerful dataloading, logging and visualization utilities for Python. It is closely integrated with PyTorch and is desi

COCO LM Pretraining (wip) Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch. They were a

网络协议2天集训 抓包工具安装 Wireshark wireshark下载地址 Tcpdump CentOS yum install tcpdump -y Ubuntu apt-get install tcpdump -y k8s抓包测试环境 查看虚拟网卡veth pair 查看

Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly Code for this paper Ultra-Data-Efficient GAN Tra

MazeRL is an application oriented Deep Reinforcement Learning (RL) framework, addressing real-world decision problems. Our vision is to cover the complete development life cycle of RL applications ranging from simulation engineering up to agent development, training and deployment.

DRLib：A concise deep reinforcement learning library, integrating HER and PER for almost off policy RL algos A concise deep reinforcement learning libr