CIFAR10 HPT Config

cifar10_hpt.yaml

studySpec:
  metrics:
  # Correspond to the metrics we use the hypertune library to report.
  - metricId: val_accuracy
    goal: MAXIMIZE
  parameters:
  # Correspond to the command line argument our Python code expects.
  - parameterId: dropout_rate
    doubleValueSpec:
      minValue: 0.01
      maxValue: 0.9
trialJobSpec:
  workerPoolSpecs:
  - machineSpec:
      # Machines and GPUs: https://cloud.google.com/vertex-ai/docs/training/configure-compute#specifying_gpus
      machineType: n1-standard-4
      acceleratorType: NVIDIA_TESLA_V100
      acceleratorCount: 2
    replicaCount: 1
    pythonPackageSpec:
      # Executors: https://cloud.google.com/vertex-ai/docs/training/pre-built-containers
      executorImageUri: us-docker.pkg.dev/vertex-ai/training/tf-gpu.2-3:latest
      packageUris: GCS_PATH_FOR_PYTHON_CODE
      pythonModule: trainer.task
      args: --epochs=50