The code in this repository acts as a sample project for running distributed reinforcement learning jobs on Azure using Ray's RLLIB. To run the project from your machine, the following steps should be satisfied.
- Azure ML Workspace
- Compute instance for triggering Job
- Compute cluster for running the training job.
- Login to your Azure account and create an Azure ML workspace.
- Create a compute instance (LINUX)
- git clone this repo into the workspace.
- Run the below command to create a compute cluster
python infra/cluster.py
- To run the single agent DQN training, run the below command
python dqn.py
- To run the training Job, run the below command
python run_experiment.py
Optional
- You can run the RL job in local machine by running the below command. In local mode the script uses the developer workstation to spin-off workers (1 by default).
python run_tune_local.py