ray/ci/regression_test/rllib_regresssion_tests/ray-project/cluster.yaml
2020-02-24 21:18:53 -08:00

43 lines
1.6 KiB
YAML

cluster_name: ray-rllib-regression-tests
min_workers: 0
max_workers: 0
# Cloud-provider specific configuration.
provider:
type: aws
region: us-west-2
availability_zone: us-west-2a
cache_stopped_nodes: False
# How Ray will authenticate with newly launched nodes.
auth:
ssh_user: ubuntu
head_node:
InstanceType: p3.16xlarge
ImageId: ami-07728e9e2742b0662 # Deep Learning AMI (Ubuntu 16.04)
# Set primary volume to 25 GiB
BlockDeviceMappings:
- DeviceName: /dev/sda1
Ebs:
VolumeSize: 100
# List of shell commands to run to set up nodes.
setup_commands:
- wget --quiet https://s3-us-west-2.amazonaws.com/ray-wheels/releases/{{ray_version}}/{{commit}}/ray-{{ray_version}}-cp36-cp36m-manylinux1_x86_64.whl
- source activate tensorflow_p36 && pip install -U ray-{{ray_version}}-cp36-cp36m-manylinux1_x86_64.whl
- source activate tensorflow_p36 && pip install ray[rllib] ray[debug]
- source activate tensorflow_p36 && pip install boto3==1.4.8 cython==0.29.0
# Command to start ray on the head node. You don't need to change this.
head_start_ray_commands:
- source activate tensorflow_p36 && ray stop
- ulimit -n 65536; source activate tensorflow_p36 && OMP_NUM_THREADS=1 ray start --head --redis-port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml
# Command to start ray on worker nodes. You don't need to change this.
worker_start_ray_commands:
- source activate tensorflow_p36 && ray stop
- ulimit -n 65536; source activate tensorflow_p36 && OMP_NUM_THREADS=1 ray start --address=$RAY_HEAD_IP:6379 --object-manager-port=8076