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518427627b
* Working prototype * Pass buffer length, fix tests * Don't buffer per default * Dispatch and process save in one go, added tests * Fix tests * Pass adaptive seconds to train_buffered, stop result processing after STOP decision * Fix tests, add release test * Update tests * Added detailed logs for slow operations * Update python/ray/tune/trial_runner.py Co-authored-by: Richard Liaw <rliaw@berkeley.edu> * Apply suggestions from code review * Revert tests and go back to old tuning loop * nit Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
34 lines
651 B
YAML
34 lines
651 B
YAML
cluster_name: ray-tune-scalability-tests
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min_workers: 15
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max_workers: 15
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initial_workers: 15
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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:nightly
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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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# 64 CPUs
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InstanceType: m5.16xlarge
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worker_nodes:
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# 64 CPUs
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InstanceType: m5.16xlarge
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setup_commands:
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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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