mirror of
https://github.com/vale981/ray
synced 2025-03-07 02:51:39 -05:00

* add copy * upgrade to tf 1.14 * update * reduce count to workaround https://github.com/ray-project/ray/issues/5125 * Update impala.py * placeholder * comments * update
65 lines
2.3 KiB
YAML
65 lines
2.3 KiB
YAML
cluster_name: default
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min_workers: 0
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max_workers: 0
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target_utilization_fraction: 0.8
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idle_timeout_minutes: 5
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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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auth:
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ssh_user: ubuntu
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head_node:
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InstanceType: m5.xlarge
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ImageId: ami-0888a3b5189309429 # DLAMI 7/1/19
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BlockDeviceMappings:
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- DeviceName: /dev/sda1
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Ebs:
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VolumeSize: 150
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worker_nodes:
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InstanceType: m5.large
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ImageId: ami-0888a3b5189309429 # DLAMI 7/1/19
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BlockDeviceMappings:
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- DeviceName: /dev/sda1
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Ebs:
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VolumeSize: 150
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# Run workers on spot by default. Comment this out to use on-demand.
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InstanceMarketOptions:
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MarketType: spot
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# List of shell commands to run to set up nodes.
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setup_commands:
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# Install latest TensorFlow
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- source activate tensorflow_p36 && conda remove -y --force wrapt || true
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- source activate tensorflow_p36 && pip install -U tensorflow==1.14
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# Install nightly Ray wheels.
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# Example: https://s3-us-west-2.amazonaws.com/ray-wheels/<<<RAY_BRANCH>>>/<<<RAY_COMMIT>>>/ray-<<<RAY_VERSION>>>-cp36-cp36m-manylinux1_x86_64.whl
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- source activate tensorflow_p36 && pip install -U RAY_WHEEL_TO_TEST_HERE
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- source activate tensorflow_p36 && pip install ray[rllib] ray[debug] gym[atari]
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- source activate tensorflow_p36 && pip install ray[debug]
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- echo set-window-option -g mouse on > ~/.tmux.conf
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- echo 'termcapinfo xterm* ti@:te@' > ~/.screenrc
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# Uncomment the following if you wish to build Ray instead.
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# - sudo apt-get update
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# - sudo apt-get install -y build-essential curl unzip
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# - git clone https://github.com/ray-project/ray || true
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# - ray/ci/travis/install-bazel.sh
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# - cd ray/python; git checkout master; git pull; source activate tensorflow_p36 && pip install -e . --verbose
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# Custom commands that will be run on the head node after common setup.
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head_setup_commands: []
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# Custom commands that will be run on worker nodes after common setup.
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worker_setup_commands: []
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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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# 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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