Python Openai-gym-environments Resources

What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? [Paper] [ICML'21 Project] PyTorch Implementation T

Introduction This script trains an agent with stochastic policy gradient ascent to solve the Lunar Lander challenge from OpenAI. In order to run this

batch-bandits Implementation of popular bandit algorithms in batch environments. Source code to our paper "The Impact of Batch Learning in Stochastic

FAR Planner uses a dynamically updated visibility graph for fast replanning. The planner models the environment with polygons and builds a global visi

Optimal Intrusion Response An OpenAI Gym interface to a MDP/Markov Game model for optimal intrusion response of a realistic infrastructure simulated u

TagBox Steer OpenAI's Jukebox with Music Taggers! The closest thing we have to VQGAN+CLIP for music! Unsupervised Source Separation By Steering Pretra

vien VIEN is a command-line tool for managing Python Virtual Environments. It provides one-line shortcuts for: creating and deleting environments runn

Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN) This is the implementation of the paper Multi-Age

VirtualFish VirtualFish is a Python virtual environment manager for the Fish shell. You can get started by reading the documentation. (It’s quite shor

openai-cli-prompt Simple CLI prompt for easy I/O with OpenAI's API Quickstart Create a .env file with: OPENAI_API_KEY=Your OpenAI API Key Configure

MemSeg: Memory-based semantic segmentation for off-road unstructured natural environments Introduction This repository is a PyTorch implementation of

Install and Run Python Applications in Isolated Environments

wger (ˈvɛɡɐ) Workout Manager is a free, open source web application that helps you manage your personal workouts, weight and diet plans and can also be used as a simple gym management utility.

Rotazioni: a linear programming workout split optimizer Dependencies Dependencies for the frontend and backend are respectively listed in client/packa

Automator-Terminator A Proof-of-Concept Layer 2 Denial of Service Attack that disrupts low level operations of Programmable Logic Controllers (PLCs) w

pyribs Website Source PyPI Conda CI/CD Docs Docs Status Twitter pyribs.org GitHub docs.pyribs.org A bare-bones Python library for quality diversity op

Reinforcement Learning with Q Learning Algorithm Q learning algorithm is trained on the gym's frozen lake environment. Libraries Used gym Numpy tqdm P

NLP command-line assistant powered by OpenAI

dm_control: DeepMind Infrastructure for Physics-Based Simulation. DeepMind's software stack for physics-based simulation and Reinforcement Learning en

Anomaly Detection in Multi-Agent Trajectories for Automated Driving This is the official project page including the paper, code, simulation, baseline

CARL (context adaptive RL) provides highly configurable contextual extensions to several well-known RL environments.

Multi-Car Racing Gym Environment This repository contains MultiCarRacing-v0 a multiplayer variant of Gym's original CarRacing-v0 environment. This env

A Jupyter notebook to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

Minimalistic Gridworld Environment (MiniGrid) There are other gridworld Gym environments out there, but this one is designed to be particularly simple

Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr

🤖 Vim Codex An AI plugin that does the work for you. This is a simple plugin for Vim that will allow you to use OpenAI Codex. To use this plugin you

BasicRL: easy and fundamental codes for deep reinforcement learning BasicRL is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up. It is

Vision-and-Language Navigation in Continuous Environments (VLN-CE) Project Website — VLN-CE Challenge — RxR-Habitat Challenge Official implementations

Deep Learning Materials by Deep Learning Wizard Start Learning Now Please head to www.deeplearningwizard.com to start learning! It is mobile/tablet fr

A ZSH plugin that enables you to use OpenAI's powerful Codex AI in the command line.

Overview PowerGym is a Gym-like environment for Volt-Var control in power distribution systems. The Volt-Var control targets minimizing voltage violat

GPT2-Pytorch with Text-Generator Better Language Models and Their Implications Our model, called GPT-2 (a successor to GPT), was trained simply to pre

CLIP-Guided-Diffusion Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab. Original colab notebooks by Ka

CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks

pip-audit pip-audit is a prototype tool for scanning Python environments for packages with known vulnerabilities. It uses the Python Packaging Advisor

Conda-Vendor Conda Vendor is a tool to create local conda channels and manifests for vendored deployments Installation To install with pip, run: pip i

Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt. This is done by

gym-mtsim: OpenAI Gym - MetaTrader 5 Simulator MtSim is a simulator for the MetaTrader 5 trading platform alongside an OpenAI Gym environment for rein

safe-control-gym Physics-based CartPole and Quadrotor Gym environments (using PyBullet) with symbolic a priori dynamics (using CasADi) for learning-ba

Cross-Quality Labeled Faces in the Wild (XQLFW) Here, we release the database, evaluation protocol and code for the following paper: Cross Quality LFW

Ranking Models in Unlabeled New Environments Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch 1.7.0 + torchivision 0.8.1

OpenAI-Codex-Code-Generation Fully coded Apps by Codex. How I use Codex in VSCode to generate multiple completions with autosorting by highest "mean p

NEWLY ADDED A3G A NEW GPU/CPU ARCHITECTURE OF A3C FOR SUBSTANTIALLY ACCELERATED TRAINING!! RL A3C Pytorch NEWLY ADDED A3G!! New implementation of A3C

CLIP Guided Diffusion From RiversHaveWings. Generate vibrant and detailed images using only text. See captions and more generations in the Gallery See

gym-recsys: Customizable RecSys Simulator for OpenAI Gym Installation | How to use | Examples | Citation This package describes an OpenAI Gym interfac

A "gym" style toolkit for building lightweight Neural Architecture Search systems

PyTorch implementation of OpenAI's Finetuned Transformer Language Model This is a PyTorch implementation of the TensorFlow code provided with OpenAI's

Deep Reinforcement Learning Algorithms with PyTorch This repository contains PyTorch implementations of deep reinforcement learning algorithms and env

GPT2-Pytorch with Text-Generator Better Language Models and Their Implications Our model, called GPT-2 (a successor to GPT), was trained simply to pre

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

pytorch-a3c-mujoco Disclaimer: my implementation right now is unstable (you ca refer to the learning curve below), I'm not sure if it's my problems. A

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments [Project website] [Paper] This project is a PyTorch

CL-Gym: Full-Featured PyTorch Library for Continual Learning CL-Gym is a small yet very flexible library for continual learning research and developme

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.

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

notebook-environments Manage python virtual environments on the working notebook server. Installation It is recommended to use this package together w

MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

Optimal Model Design for Reinforcement Learning This repository contains JAX code for the paper Control-Oriented Model-Based Reinforcement Learning wi

Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments Paper: arXiv (ICRA 2021) Video : https://youtu.be/CC

mastrade MasTrade is a trading bot in baselines3,pytorch,gym idea we have for example 1 btc and we buy a crypto with it with market option to trade in

train-CLIP 📎 A PyTorch Lightning solution to training CLIP from scratch. Goal ⚽ Our aim is to create an easy to use Lightning implementation of OpenA

It was in January of 2021 that OpenAI announced two new models: DALL-E and CLIP, both multi-modality models connecting texts and images in some way. In this article we are going to implement CLIP model from scratch in PyTorch. OpenAI has open-sourced some of the code relating to CLIP model but I found it intimidating and it was far from something short and simple. I also came across a good tutorial inspired by CLIP model on Keras code examples and I translated some parts of it into PyTorch to build this tutorial totally with our beloved PyTorch!

The ABR Control library is a python package for the control and path planning of robotic arms in real or simulated environments. ABR Control provides API's for the Mujoco, CoppeliaSim (formerly known as VREP), and Pygame simulation environments, and arm configuration files for one, two, and three-joint models, as well as the UR5 and Kinova Jaco 2 arms. Users can also easily extend the package to run with custom arm configurations. ABR Control auto-generates efficient C code for generating the control signals, or uses Mujoco's internal functions to carry out the calculations.

Reinforcement Learning (PyTorch) 🤖 + 🍰 = ❤️ This repo will contain PyTorch implementation of various fundamental RL algorithms. It's aimed at making

Ryan Murdock has done it again, combining OpenAI's CLIP and the generator from a BigGAN! This repository wraps up his work so it is easily accessible to anyone who owns a GPU.

django-admin-env-notice Visually distinguish environments in Django Admin. Based on great advice from post: 5 ways to make Django Admin safer by hakib

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.

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

...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

OpenAI's CLIP — REST API This is a container wrapping OpenAI's CLIP model in a RESTful interface. Running the container locally First, build the conta

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

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)

[ICLR 2021] RAPID: A Simple Approach for Exploration in Reinforcement Learning This is the Tensorflow implementation of ICLR 2021 paper Rank the Episo

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

Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy. Now with tensorflow 1.0 support. Evaluation usa

gpt-2-simple A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifical

spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr

Ravens is a collection of simulated tasks in PyBullet for learning vision-based robotic manipulation, with emphasis on pick and place. It features a Gym-like API with 10 tabletop rearrangement tasks, each with (i) a scripted oracle that provides expert demonstrations (for imitation learning), and (ii) reward functions that provide partial credit (for reinforcement learning).

This project allows you to train AI agents on custom-built multiplayer environments, through self-play reinforcement learning.

gpt-2-simple A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifical

spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr

pipx — Install and Run Python Applications in Isolated Environments Documentation: https://pipxproject.github.io/pipx/ Source Code: https://github.com

DALL-E in Pytorch Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch. It will also contain CLIP for ranking the ge

Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative

artificial intelligence cosmic love and attention fire in the sky a pyramid made of ice a lonely house in the woods marriage in the mountains lantern

Learning to Simulate Dynamic Environments with GameGAN PyTorch code for GameGAN Learning to Simulate Dynamic Environments with GameGAN Seung Wook Kim,

Meta-World Meta-World is an open-source simulated benchmark for meta-reinforcement learning and multi-task learning consisting of 50 distinct robotic

Coach Coach is a python reinforcement learning framework containing implementation of many state-of-the-art algorithms. It exposes a set of easy-to-us

Status: Maintenance (expect bug fixes and minor updates) Gym Retro Gym Retro lets you turn classic video games into Gym environments for reinforcement

Status: Maintenance (expect bug fixes and minor updates) OpenAI Gym OpenAI Gym is a toolkit for developing and comparing reinforcement learning algori

ItsDangerous ... so better sign this Various helpers to pass data to untrusted environments and to get it back safe and sound. Data is cryptographical

Status: Maintenance (expect bug fixes and minor updates) OpenAI Gym OpenAI Gym is a toolkit for developing and comparing reinforcement learning algori