<commit_before># XL ML Test

Cloud **Accel**erated **M**achine **L**earning **Test**s

To run one test once, run the following:

```bash
jsonnet templates/oneshot.jsonnet --tla-str test=$TEST_NAME | kubectl create -f -
```

To generate and deploy Kubernetes YAMLs from the templates, run the following:

```bash
jsonnet -S templates/multifile.jsonnet -m k8s/gen
kubectl apply -f k8s/gen
```<commit_msg>Update main README with instructions on how to use this repo.<commit_after># XL ML Test

Cloud **Accel**erated **M**achine **L**earning **Test**s

A set of tools and examples to run machine learning tests on ML hardware
accelerators (TPUs or GPUs) using Google Cloud Platform.

This is not an officially supported Google product.

## Getting Started

1. Reach out to <EMAIL> to see about potentially getting a free trial on Google Cloud Platform.
2. Follow instructions in the `deployments` directory to set up a Kubernetes Cluster.
3. Follow instructions in the `images` directory to set up the Docker image that your tests will run.
4. Set up your tests. Here you have 1 of 2 choices:
    * See `examples` directory if you will have a relatively small number of tests and don't need inheritance in your tests.
    * See `templates` directory for a more powerful templating engine to generate test config files programmatically.
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