- name: inference
  team: core
  cluster:
    app_config: app_config.yaml
    compute_template: inference.yaml

  run:
    timeout: 600
    prepare: python wait_cluster.py 2 600
    script: python inference.py
  
- name: shuffle_data_loader
  team: core
  cluster:
    app_config: shuffle_app_config.yaml
    compute_template: shuffle_compute.yaml

  run:
    timeout: 1800
    script: python dataset_shuffle_data_loader.py

- name: parquet_metadata_resolution
  team: core
  cluster:
    app_config: pipelined_training_app.yaml
    compute_template: pipelined_training_compute.yaml

  run:
    timeout: 1200
    prepare: python wait_cluster.py 15 1200
    script: python parquet_metadata_resolution.py --num-files 915

- name: pipelined_training_50_gb
  team: core
  cluster:
    app_config: pipelined_training_app.yaml
    compute_template: pipelined_training_compute.yaml

  run:
    timeout: 4800
    prepare: python wait_cluster.py 15 1200
    script: python pipelined_training.py --epochs 1

- name: pipelined_ingestion_1500_gb
  team: core
  cluster:
    app_config: pipelined_ingestion_app.yaml
    compute_template: pipelined_ingestion_compute.yaml

  run:
    timeout: 9600
    prepare: python wait_cluster.py 21 2400
    script: python pipelined_training.py --epochs 2 --num-windows 2 --num-files 915 --debug

- name: datasets_ingest_train_infer
  team: core
  cluster:
    app_config: ray_sgd_training_app.yaml
    compute_template: ray_sgd_training_compute.yaml

  run:
    timeout: 14400
    prepare: python wait_cluster.py 66 2400
    script: python ray_sgd_training.py --address auto --use-s3 --num-workers 16 --use-gpu --large-dataset

  smoke_test:
    cluster:
      app_config: ray_sgd_training_app.yaml
      compute_template: ray_sgd_training_smoke_compute.yaml

    run:
      timeout: 3600
      prepare: python wait_cluster.py 8 2400
      script: python ray_sgd_training.py --address auto --use-s3 --num-workers 8 --use-gpu

- name: datasets_preprocess_ingest
  team: core
  cluster:
    app_config: ray_sgd_training_app.yaml
    compute_template: ray_sgd_training_compute_no_gpu.yaml

  run:
    timeout: 7200
    prepare: python wait_cluster.py 21 2400
    script: python ray_sgd_training.py --address auto --use-s3 --num-workers 16 --use-gpu --large-dataset --debug

- name: datasets_ingest_400G
  team: core
  cluster:
    app_config: ray_sgd_training_app.yaml
    compute_template: dataset_ingest_400G_compute.yaml

  run:
    timeout: 7200
    script: python ray_sgd_runner.py --address auto --use-gpu --num-epochs 1