https://github.com/aws-deepracer-community/deepracer-for-cloud

Creates an AWS DeepRacing training environment which can be deployed in the cloud, or locally on Ubuntu Linux, Windows or Mac.
https://github.com/aws-deepracer-community/deepracer-for-cloud

Last synced: about 2 months ago
JSON representation

Creates an AWS DeepRacing training environment which can be deployed in the cloud, or locally on Ubuntu Linux, Windows or Mac.

• Host: GitHub
• URL: https://github.com/aws-deepracer-community/deepracer-for-cloud
• Owner: aws-deepracer-community
• License: mit-0
• Created: 2019-07-14T17:59:32.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2024-07-20T12:07:27.000Z (2 months ago)
• Last Synced: 2024-07-20T13:26:14.660Z (2 months ago)
• Language: Shell
• Homepage:
• Size: 521 KB
• Stars: 325
• Watchers: 23
• Forks: 176
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# DeepRacer-For-Cloud

Provides a quick and easy way to get up and running with a DeepRacer training environment using a cloud virtual machine or a local compter, such [AWS EC2 Accelerated Computing instances](https://aws.amazon.com/ec2/instance-types/?nc1=h_ls#Accelerated_Computing) or the Azure [N-Series Virtual Machines](https://docs.microsoft.com/en-us/azure/virtual-machines/windows/sizes-gpu).

DRfC runs on Ubuntu 20.04 or 22.04. GPU acceleration requires a NVIDIA GPU, preferrably with more than 8GB of VRAM.

## Introduction

DeepRacer-For-Cloud (DRfC) started as an extension of the work done by Alex (https://github.com/alexschultz/deepracer-for-dummies), which is again a wrapper around the amazing work done by Chris (https://github.com/crr0004/deepracer). With the introduction of the second generation Deepracer Console the repository has been split up. This repository contains the scripts needed to *run* the training, but depends on Docker Hub to provide pre-built docker images. All the under-the-hood building capabilities are in the [Deepracer Simapp](https://github.com/aws-deepracer-community/deepracer-simapp) repository.

## Main Features

DRfC supports a wide set of features to ensure that you can focus on creating the best model:

* User-friendly

	* Based on the continously updated community [Robomaker](https://github.com/aws-deepracer-community/deepracer-simapp) container, supporting a wide range of CPU and GPU setups.

	* Wide set of scripts (`dr-*`) enables effortless training.

	* Detection of your AWS DeepRacer Console models; allows upload of a locally trained model to any of them.

* Modes

	* Time Trial

	* Object Avoidance

	* Head-to-Bot

* Training

	* Multiple Robomaker instances per Sagemaker (N:1) to improve training progress.

	* Multiple training sessions in parallel - each being (N:1) if hardware supports it - to test out things in parallel.

	* Connect multiple nodes together (Swarm-mode only) to combine the powers of multiple computers/instances.

* Evaluation

	* Evaluate independently from training.

	* Save evaluation run to MP4 file in S3.

* Logging

	* Training metrics and trace files are stored to S3.

	* Optional integration with AWS CloudWatch.

	* Optional exposure of Robomaker internal log-files.

* Technology

	* Supports both Docker Swarm (used for connecting multiple nodes together) and Docker Compose

## Documentation

Full documentation can be found on the [Deepracer-for-Cloud GitHub Pages](https://aws-deepracer-community.github.io/deepracer-for-cloud).

## Support

* For general support it is suggested to join the [AWS DeepRacing Community](https://deepracing.io/). The Community Slack has a channel #dr-training-local where the community provides active support.

* Create a GitHub issue if you find an actual code issue, or where updates to documentation would be required.