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1.0 1.0 0.0 300.61 MB

Extract from AWS DeepRacer Robomaker Bundle

License: MIT License

Python 93.38% C++ 4.82% Shell 1.36% CMake 0.37% Rich Text Format 0.04% C 0.04%

deepracer-simapp's Introduction

AWS DeepRacer Simapp Image

This repository contains the extracts from the AWS DeepRacer Simapp; including

  • the environment and tracks
  • the robotics agent code ('markov')
  • Dockerfiles

In DeepRacer-for-Cloud this single image is being used for three purposes:

  • "Robomaker" container (1 or more) providing robotics simulation using ROS and Gazebo
  • "Sagemaker" container providing the model training job
  • "RL Coach" container which bootstraps the Sagemaker container, using the Sagemaker SDK and Sagemaker Local.

Source

The code in bundle/ is primarily provided by AWS, and is closely matching the code that is running in the AWS DeepRacer console. Work is based on the information provided in Guidance for training an AWS DeepRacer model using Amazon Sagemaker.

The source is taken from the deepracer-sim-public Container, and is replicated here in the upstream branch.

Single image

Up until Version 5.3 these docker containers were run backed by three different containers. As the actual prerequisites (Ubuntu and Python packages) converged over time, the images were content-wise very similar, but the same code was downloaded more than once increasing network and storage needs.

Previous versions had the Markov code bundle/markov injected into Sagemaker containers via the RL coach container (where it was built in); now the codebase is built into the single image, and RL coach does not inject code anymore.

Core Technologies / Technology Stack

Installed core technologies are:

  • Ubuntu 20.04
  • Python 3.8
  • Tensorflow 2.13
  • CUDA 11.8 (GPU only)
  • REDIS 6.2.7
  • ROS Noetic
  • Gazebo 11

Available pre-built versions

In most cases it will be sufficient to use one of our pre-built images:

  • CPU image support training using the CPU for inference. (Tag VERSION-cpu)
  • GPU image support training using CUDA GPU for inference. (Tag VERSION-gpu)

Both containers support OpenGL acceleration.

Built images are available via docker pull awsdeepracercommunity/deepracer-simapp:<tag> - see also Docker Hub.

Building the image

A build script is available as build.sh. By default both images will be built (cpu and gpu for version 5.3). Use the -a switch to limit number of images.

Development build

To get a folder compatible with DRfCs DR_ROBOMAKER_MOUNT_SIMAPP_DIR use the build-dev-bundle.sh script. Through using a build container it will create a ./install directory that can be mounted in Robomaker.

deepracer-simapp's People

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