torchbench_gpu_sdl.yaml

---
version: "2.0"

services:
  gpu-test:
    image: docker.io/thumperai/torchbench
    expose:
      - port: 3000
        as: 80
        to:
          - global: true
    # cmd:
    #    - 'python /workspace/benchmark/install.py models hf_bert hf_Bert_large resnet50 tacotron2 && pytest /workspace/benchmark/test_bench.py -k "(hf_bert or hf_bert_Large or resnet50 or tacotron2)" --ignore_machine_config'
        # - "cd benchmark && python install.py models hf_bert hf_Bert_large resnet50 tacotron2 && pytest /workspace/benchmark/test_bench.py -k '(hf_bert or hf_bert_Large or resnet50 or tacotron2 and (not cuda))' --ignore_machine_config"
        # runtime is about 1 minute for setup and about 8 minutes for benchmarks on laptop 
profiles:
  compute:
    gpu-test:
      resources:
        cpu:
          units: 1
        memory:
          size: 20Gi
        gpu:
          units: 1
        storage:
          - size: 100Gi
  placement:
    westcoast:
      pricing:
        gpu-test:
          denom: uakt
          amount: 100000
deployment:
  gpu-test:
    westcoast:
      profile: gpu-test
      count: 1