cluster_name: ray-xgboost-release-cpu-small

max_workers: 5

upscaling_speed: 32

idle_timeout_minutes: 15

docker:
    image: anyscale/ray-ml:latest
    container_name: ray_container
    pull_before_run: true

provider:
    type: aws
    region: us-west-2
    availability_zone: us-west-2a
    cache_stopped_nodes: false

available_node_types:
    cpu_4_ondemand:
        node_config:
            InstanceType: m5.xlarge
        resources: {"CPU": 4}
        min_workers: 0
        max_workers: 0
    gpu_1_ondemand:
        node_config:
            InstanceType: p2.xlarge
        resources: {"CPU": 4, "GPU": 1}
        min_workers: 4
        max_workers: 4

auth:
    ssh_user: ubuntu

head_node_type: cpu_4_ondemand
worker_default_node_type: gpu_1_ondemand

file_mounts: {
    "~/release-automation-xgboost_tests": "."
}

setup_commands:
    - pip install pytest xgboost_ray
    - sudo mkdir -p /data || true
    - sudo chown ray:1000 /data || true
    - rm -rf /data/classification.parquet || true
    - cp -R /tmp/ray_tmp_mount/release-automation-xgboost_tests ~/release-automation-xgboost_tests || echo "Copy failed"
    - python ~/release-automation-xgboost_tests/create_test_data.py /data/classification.parquet --seed 1234 --num-rows 1000000 --num-cols 40 --num-partitions 100 --num-classes 2