Setup

To enable Comet Logging for this example, we will have to install Ray from Source.

1. Create a Virtual Environment

We will use conda to create our virtual environment, but feel free to use your preferred method for creating Python virtual environments.

conda create -n comet-ray-tune python=3.8
conda activate comet-ray-tune

2. Run the Setup Helper Script

The helper script, setup.sh will install Ray in the virtual environment

chmod +x setup.sh && ./setup.sh

Set your Comet Credentials

In order to run the example, you will need to set the following Comet credentials using environment variables.

export COMET_API_KEY=<Your Comet API Key>
export COMET_WORKSPACE=<Your Comet Workspace>
export COMET_PROJECT_NAME=<Your Comet Project Name>

Run the Example

The following command will run a hyperparameter sweep using tune on the MNIST dataset, and log metrics, hyperparameters, and checkpoints to Comet.

Each Ray trial_id will be logged as an individual experiment in Comet.

Example using the CometLoggerCallback

python tune_comet_callback.py

Example using the Ray Functional API

python tune_comet_functional.py

Example using the Ray Trainable Class API

python tune_comet_trainable.py

Example Tune Run in Comet

Here is an example project with a completed tune sweep

Ray Tune Example Project