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https://github.com/vale981/ray
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107aef89a8
* add * update cluster env * fix build Co-authored-by: Matthew Deng <matthew.j.deng@gmail.com>
78 lines
1.9 KiB
YAML
78 lines
1.9 KiB
YAML
- name: inference
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owner:
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mail: "core@anyscale.com"
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slack: "@Alex Wu"
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cluster:
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app_config: app_config.yaml
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compute_template: inference.yaml
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run:
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timeout: 600
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prepare: python wait_cluster.py 2 600
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script: python inference.py
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- name: shuffle_data_loader
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owner:
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mail: "core@anyscale.com"
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slack: "@Chen Shen"
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cluster:
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app_config: shuffle_app_config.yaml
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compute_template: shuffle_compute.yaml
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run:
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timeout: 1800
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script: python dataset_shuffle_data_loader.py
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- name: pipelined_training_50_gb
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owner:
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mail: "core@anyscale.com"
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slack: "@Chen Shen"
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cluster:
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app_config: pipelined_training_app.yaml
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compute_template: pipelined_training_compute.yaml
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run:
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timeout: 4800
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prepare: python wait_cluster.py 15 1200
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script: python pipelined_training.py --epochs 1
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- name: pipelined_ingestion_1500_gb_15_windows
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owner:
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mail: "core@anyscale.com"
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slack: "@Chen Shen"
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cluster:
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app_config: pipelined_ingestion_app.yaml
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compute_template: pipelined_ingestion_compute.yaml
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run:
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timeout: 4800
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prepare: python wait_cluster.py 21 2400
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script: python pipelined_training.py --epochs 2 --num-windows 15 --num-files 915 --debug
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- name: datasets_ingest_train_infer
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owner:
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mail: "core@anyscale.com"
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slack: "@Chen Shen"
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cluster:
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app_config: ray_sgd_training_app.yaml
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compute_template: ray_sgd_training_compute.yaml
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run:
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timeout: 14400
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prepare: python wait_cluster.py 66 2400
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script: python ray_sgd_training.py --address auto --use-s3 --num-workers 16 --use-gpu --large-dataset
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smoke_test:
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cluster:
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app_config: ray_sgd_training_app.yaml
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compute_template: ray_sgd_training_smoke_compute.yaml
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run:
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timeout: 3600
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prepare: python wait_cluster.py 8 2400
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script: python ray_sgd_training.py --address auto --use-s3 --num-workers 8 --use-gpu
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