mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
59 lines
1.9 KiB
YAML
59 lines
1.9 KiB
YAML
cluster_name: ray-rllib-regression-tests
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min_workers: 0
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max_workers: 0
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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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run_options: ["--ulimit nofile=1045876"]
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# Cloud-provider specific configuration.
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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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# How Ray will authenticate with newly launched nodes.
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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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ImageId: ami-0a2363a9cff180a64 # Custom ami
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# Set primary volume to 25 GiB
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BlockDeviceMappings:
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- DeviceName: /dev/sda1
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Ebs:
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VolumeSize: 100
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worker_nodes:
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InstanceType: p3.16xlarge
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ImageId: ami-0a2363a9cff180a64 # Custom ami
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# Set primary volume to 25 GiB
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BlockDeviceMappings:
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- DeviceName: /dev/sda1
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Ebs:
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VolumeSize: 100
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# List of shell commands to run to set up nodes.
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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 terminado
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- pip install torch==1.6 torchvision
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- pip install boto3==1.4.8 cython==0.29.0
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- "pip install https://s3-us-west-2.amazonaws.com/ray-wheels/releases/1.1.0/f591f6c1c8fa14af6df2adfdcf3255c59dff12b1/ray-1.1.0.dev0-cp37-cp37m-manylinux2014_x86_64.whl"
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- git clone https://github.com/ray-project/ray.git ray-cp
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- pip install -r ./ray-cp/release/rllib_tests/regression_tests/requirements.txt
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# Command to start ray on the head node. You don't need to change this.
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head_start_ray_commands:
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- ray stop
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- OMP_NUM_THREADS=1 ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
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# Command to start ray on worker nodes. You don't need to change this.
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worker_start_ray_commands:
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- ray stop
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- OMP_NUM_THREADS=1 ray start --address=$RAY_HEAD_IP:6379 --object-manager-port=8076
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