Welcome to VDL’s documentation!¶
This documentation documents how to reproduce the result in the VDL project. The most update-to-date version can be found in the VDL github repository
This project implements the distributed learning system as shown in the above figure. How to run and benchmark each component and how to run the complete system are documented in the following sections.
- Multiple learners component
- Run 5 learners and 10 actors in a cluster
- The virtual robot arm
Files in this project¶
# Main docs/ # Documentation files in reStructuredText format universe-starter-agent/ # Virtual distributed learning system, the code is # modified from https://github.com/openai/universe-starter-agent, which # provides the baseline learning algorithm. # Components learner-actor/ # Experiment code for learner-actor communication tensorflow_MNIST/ # Experiment code for P2P-multi-learner # Utility gym-demo/ # Virtual environnment demos to make sure the dev # boxs are correctly configured. benchmark/ # Benchmark code to evaluate the network speed and # speed of different virtual environments neonrace/ # Code to run trained neonrace auto-driving model spread/ # Compiled spread and its python wrapper # Virtual arm arm-pose/ # Pose estimation code trained on the virtual arm # and test on the real arm. owi-arm/ # Code to control real and the virtual arm