# A unique identifier for the head node and workers of this cluster.
cluster_name: tpupodtest

max_workers: 2

available_node_types:
    ray_head_default:
        min_workers: 0
        max_workers: 0
        resources: {"CPU": 0}
        # Provider-specific config for this node type, e.g. instance type. By default
        # Ray will auto-configure unspecified fields such as subnets and ssh-keys.
        # For more documentation on available fields, see:
        # https://cloud.google.com/compute/docs/reference/rest/v1/instances/insert
        node_config:
            machineType: n1-standard-4
            disks:
              - boot: true
                autoDelete: true
                type: PERSISTENT
                initializeParams:
                  diskSizeGb: 50
                  # See https://cloud.google.com/compute/docs/images for more images
                  sourceImage: projects/ubuntu-os-cloud/global/images/family/ubuntu-2004-lts
    ray_tpu:
        min_workers: 1
        max_workers: 1
        resources: {"TPU": 1}  # use TPU custom resource in your code
        node_config:
            # Note: A v4-16 will have 2 hosts.
            # While the cluster launcher can create multiple TPU pods, note that
            # "proper" autoscaling currently does not work as expected as all hosts
            # in a TPU pod need to execute the same program.
            acceleratorType: v4-16
            runtimeVersion: tpu-vm-v4-base

provider:
    type: gcp
    region: us-central2
    availability_zone: us-central2-b
    project_id: null # Replace this with your GCP project ID.

initialization_commands:
  - sudo apt-get update
  - sudo apt-get install -y python3-pip python-is-python3

setup_commands:
  - pip install 'ray[default]'

head_setup_commands:
  - pip install google-api-python-client

# Specify the node type of the head node (as configured above).
head_node_type: ray_head_default