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CIFAR10 HPT Config
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| 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 |
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