DeepMind Alchemy task environment: a meta-reinforcement learning benchmark

Overview

dm_alchemy: DeepMind Alchemy environment

Overview | Requirements | Installation | Usage | Documentation | Tutorial | Paper | Blog post

The DeepMind Alchemy environment is a meta-reinforcement learning benchmark that presents tasks sampled from a task distribution with deep underlying structure. It was created to test for the ability of agents to reason and plan via latent state inference, as well as useful exploration and experimentation. It is Unity-based.

Overview

This environment is provided through pre-packaged Docker containers.

This package consists of support code to run these Docker containers. You interact with the task environment via a dm_env Python interface.

Please see the documentation for more detailed information on the available tasks, actions and observations.

Requirements

dm_alchemy requires Docker, Python 3.6.1 or later and a x86-64 CPU with SSE4.2 support. We do not attempt to maintain a working version for Python 2.

Alchemy is intended to be run on Linux and is not officially supported on Mac and Windows. However, it can in principle be run on any platform (though installation may be more of a headache). In particular, on Windows, you will need to install and run Alchemy with WSL.

Note: We recommend using Python virtual environment to mitigate conflicts with your system's Python environment.

Download and install Docker:

Ensure that docker is working correctly by running docker run -d gcr.io/deepmind-environments/alchemy:v1.0.0.

Installation

You can install dm_alchemy by cloning a local copy of our GitHub repository:

$ git clone https://github.com/deepmind/dm_alchemy.git
$ pip install wheel
$ pip install --upgrade setuptools
$ pip install ./dm_alchemy

To also install the dependencies for the examples/, install with:

$ pip install ./dm_alchemy[examples]

Usage

Once dm_alchemy is installed, to instantiate a dm_env instance run the following:

import dm_alchemy

LEVEL_NAME = ('alchemy/perceptual_mapping_'
              'randomized_with_rotation_and_random_bottleneck')
settings = dm_alchemy.EnvironmentSettings(seed=123, level_name=LEVEL_NAME)
env = dm_alchemy.load_from_docker(settings)

For more details see the introductory colab.

Open in colab

Citing Alchemy

If you use Alchemy in your work, please cite the accompanying technical report:

@article{wang2021alchemy,
    title={Alchemy: A structured task distribution for meta-reinforcement learning},
    author={Jane Wang and Michael King and Nicolas Porcel and Zeb Kurth-Nelson
        and Tina Zhu and Charlie Deck and Peter Choy and Mary Cassin and
        Malcolm Reynolds and Francis Song and Gavin Buttimore and David Reichert
        and Neil Rabinowitz and Loic Matthey and Demis Hassabis and Alex Lerchner
        and Matthew Botvinick},
    year={2021},
    journal={arXiv preprint arXiv:2102.02926},
    url={https://arxiv.org/abs/2102.02926},
}

Notice

This is not an officially supported Google product.

Owner
DeepMind
DeepMind
EMNLP 2021 Findings' paper, SCICAP: Generating Captions for Scientific Figures

SCICAP: Scientific Figures Dataset This is the Github repo of the EMNLP 2021 Findings' paper, SCICAP: Generating Captions for Scientific Figures (Hsu

Edward 26 Nov 21, 2022
Pre-trained NFNets with 99% of the accuracy of the official paper

NFNet Pytorch Implementation This repo contains pretrained NFNet models F0-F6 with high ImageNet accuracy from the paper High-Performance Large-Scale

Benjamin Schmidt 133 Dec 09, 2022
A multi-scale unsupervised learning for deformable image registration

A multi-scale unsupervised learning for deformable image registration Shuwei Shao, Zhongcai Pei, Weihai Chen, Wentao Zhu, Xingming Wu and Baochang Zha

ShuweiShao 2 Apr 13, 2022
The official PyTorch implementation for NCSNv2 (NeurIPS 2020)

Improved Techniques for Training Score-Based Generative Models This repo contains the official implementation for the paper Improved Techniques for Tr

174 Dec 26, 2022
git《USD-Seg:Learning Universal Shape Dictionary for Realtime Instance Segmentation》(2020) GitHub: [fig2]

USD-Seg This project is an implement of paper USD-Seg:Learning Universal Shape Dictionary for Realtime Instance Segmentation, based on FCOS detector f

Ruolin Ye 80 Nov 28, 2022
This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods

pyLiDAR-SLAM This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods, which can easily be evaluated

Kitware, Inc. 208 Dec 16, 2022
Deep learning for Engineers - Physics Informed Deep Learning

SciANN: Neural Networks for Scientific Computations SciANN is a Keras wrapper for scientific computations and physics-informed deep learning. New to S

SciANN 195 Jan 03, 2023
Code for paper: "Spinning Language Models for Propaganda-As-A-Service"

Spinning Language Models for Propaganda-As-A-Service This is the source code for the Arxiv version of the paper. You can use this Google Colab to expl

Eugene Bagdasaryan 16 Jan 03, 2023
Optical Character Recognition + Instance Segmentation for russian and english languages

Распознавание рукописного текста в школьных тетрадях Соревнование, проводимое в рамках олимпиады НТО, разработанное Сбером. Платформа ODS. Результаты

Gerasimov Maxim 21 Dec 19, 2022
A collection of loss functions for medical image segmentation

A collection of loss functions for medical image segmentation

Jun 3.1k Jan 03, 2023
Facilitating Database Tuning with Hyper-ParameterOptimization: A Comprehensive Experimental Evaluation

A Comprehensive Experimental Evaluation for Database Configuration Tuning This is the source code to the paper "Facilitating Database Tuning with Hype

DAIR Lab 9 Oct 29, 2022
A simple code to convert image format and channel as well as resizing and renaming multiple images.

Rename-Resize-and-convert-multiple-images A simple code to convert image format and channel as well as resizing and renaming multiple images. This cod

Happy N. Monday 3 Feb 15, 2022
[SIGMETRICS 2022] One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search

One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search paper | website One Proxy Device Is Enough for Hardware-Aware Neural Architec

10 Dec 16, 2022
A modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (prediction model)

ParallelFold Author: Bozitao Zhong This is a modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (p

Bozitao Zhong 77 Dec 22, 2022
MANO hand model porting for the GraspIt simulator

Learning Joint Reconstruction of Hands and Manipulated Objects - ManoGrasp Porting the MANO hand model to GraspIt! simulator Yana Hasson, Gül Varol, D

Lucas Wohlhart 10 Feb 08, 2022
Multi-label classification of retinal disorders

Multi-label classification of retinal disorders This is a deep learning course project. The goal is to develop a solution, using computer vision techn

Sundeep Bhimireddy 1 Jan 29, 2022
dualFace: Two-Stage Drawing Guidance for Freehand Portrait Sketching (CVMJ)

dualFace dualFace: Two-Stage Drawing Guidance for Freehand Portrait Sketching (CVMJ) We provide python implementations for our CVM 2021 paper "dualFac

Haoran XIE 46 Nov 10, 2022
Author's PyTorch implementation of Randomized Ensembled Double Q-Learning (REDQ) algorithm.

REDQ source code Author's PyTorch implementation of Randomized Ensembled Double Q-Learning (REDQ) algorithm. Paper link: https://arxiv.org/abs/2101.05

109 Dec 16, 2022
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators

Pandas TA - A Technical Analysis Library in Python 3 Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package

Kevin Johnson 3.2k Jan 09, 2023
Code for "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" @ICRA2021

CloudAAE This is an tensorflow implementation of "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" Files log:

Gee 35 Nov 14, 2022