mirror of
https://github.com/vale981/ray
synced 2025-03-08 19:41:38 -05:00
46 lines
1.1 KiB
YAML
46 lines
1.1 KiB
YAML
cluster_name: ray-rllib-stress-tests
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min_workers: 9
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max_workers: 9
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target_utilization_fraction: 0.8
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idle_timeout_minutes: 15
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docker:
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image: anyscale/ray-ml:latest-gpu
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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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auth:
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ssh_user: ubuntu
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head_node:
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InstanceType: p3.16xlarge
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worker_nodes:
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InstanceType: m5.16xlarge
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file_mounts: {
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# "/path1/on/remote/machine": "/path1/on/local/machine",
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# "/path2/on/remote/machine": "/path2/on/local/machine",
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}
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setup_commands:
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- apt-get install -y libglib2.0-0 libcudnn7=7.6.5.32-1+cuda10.1
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- pip install -U https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-1.2.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl
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worker_setup_commands: []
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head_start_ray_commands:
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- ray stop
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- ulimit -n 65536; OMP_NUM_THREADS=1 ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
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worker_start_ray_commands:
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- ray stop
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- ulimit -n 65536; OMP_NUM_THREADS=1 ray start --address=$RAY_HEAD_IP:6379 --object-manager-port=8076
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