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https://github.com/wassname/ray.git
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Kai Fricke
51 lines
1.3 KiB
YAML
51 lines
1.3 KiB
YAML
cluster_name: ray-xgboost-release-cpu-small
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max_workers: 5
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upscaling_speed: 32
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idle_timeout_minutes: 15
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docker:
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image: anyscale/ray-ml:latest
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container_name: ray_container
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pull_before_run: true
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provider:
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type: aws
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region: us-west-2
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availability_zone: us-west-2a
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cache_stopped_nodes: false
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available_node_types:
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cpu_4_ondemand:
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node_config:
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InstanceType: m5.xlarge
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resources: {"CPU": 4}
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min_workers: 0
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max_workers: 0
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gpu_1_ondemand:
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node_config:
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InstanceType: p2.xlarge
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resources: {"CPU": 4, "GPU": 1}
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min_workers: 4
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max_workers: 4
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auth:
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ssh_user: ubuntu
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head_node_type: cpu_4_ondemand
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worker_default_node_type: gpu_1_ondemand
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file_mounts: {
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"~/release-automation-xgboost_tests": "."
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}
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setup_commands:
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- pip install pytest xgboost_ray
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- sudo mkdir -p /data || true
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- sudo chown ray:1000 /data || true
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- rm -rf /data/classification.parquet || true
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- cp -R /tmp/ray_tmp_mount/release-automation-xgboost_tests ~/release-automation-xgboost_tests || echo "Copy failed"
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- 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
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