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Sonic on Ray

This file describes how to use Sonic with Ray and RLLib. We include instructions on how to get the training running on EC2.

Running training on a single node

Start a p2.8xlarge with the Deep Learning AMI (Ubuntu). In us-west-2, this is ami-d2c759aa.

Activate the TensorFlow environment with

source activate tensorflow_p36

Now install Ray and the RLlib requirements using

pip install ray opencv-python

Next we need to install the gym retro environment. Run

git clone --recursive [email protected]:openai/retro.git gym-retro
cd gym-retro
pip install -e .

Now clone this repo and install it:

cd ~
git clone [email protected]:openai/sonic-on-ray.git
cd sonic-on-ray
pip install -e .

You can then run the training with

cd ~/sonic-on-ray
python train_ppo.py

Running training on a cluster

First install Ray on your laptop with

pip install ray

Now clone the sonic-on-ray repo with

git clone [email protected]:openai/sonic-on-ray.git

And start a cluster with

ray create_or_update sonic-autoscaler.yaml

After the cluster has been started, you will see a message like this:

Started Ray on this node. You can add additional nodes to the cluster by calling

    ray start --redis-address 172.31.58.176:6379

from the node you wish to add. You can connect a driver to the cluster from Python by running

    import ray
    ray.init(redis_address="172.31.58.176:6379")

[...]

To login to the cluster, run:

      ssh -i ~/.ssh/ray-autoscaler_us-east-1.pem [email protected]

You can now start the hyperparameter search by sshing into the cluster, running

source activate tensorflow_p36

and replacing the ray.init() call in ~/sonic-on-ray/train_ppo_grid_search.py by the one printed above and then running the script.