Docker execution model

HyperOptimizer runs your workload as containers. The image owns the code path; the platform owns scheduling, parameter selection, and metric collection.

Container contract

Your image must be able to run one trial from its default command. HyperOptimizer appends HPO arguments to that command.

python main.py --hpo-lookback-window=50 --hpo-risk-multiplier=1.4

The process should exit after the trial finishes. A successful run exits with code 0 and prints metric lines.

Parallel execution

Multiple trials can run at the same time. Treat each container as isolated. If trials write files, use unique output paths or write only within the container filesystem.

Parallelism speeds up experiments, but the optimizer can only learn from completed trials. Emit metrics as soon as the trial result is known.

Inputs and outputs

Inputs

Docker image
`--hpo-*` CLI parameters
Optional environment and data access

Outputs

Exit code
Stdout metric lines
Logs for debugging failed trials

Build the image with the Docker image guide.