mlos_bench.storage.sql.trial
Storage.Trial interface implementation for saving and restoring
the benchmark trial data using SQLAlchemy backend.
Classes
Store the results of a single run of the experiment in SQL database. |
Module Contents
- class mlos_bench.storage.sql.trial.Trial(*, engine: sqlalchemy.engine.Engine, schema: mlos_bench.storage.sql.schema.DbSchema, tunables: mlos_bench.tunables.tunable_groups.TunableGroups, experiment_id: str, trial_id: int, config_id: int, opt_targets: Dict[str, Literal['min', 'max']], config: Dict[str, Any] | None = None)[source]
Bases:
mlos_bench.storage.base_storage.Storage.TrialStore the results of a single run of the experiment in SQL database.
- Parameters:
- update(status: mlos_bench.environments.status.Status, timestamp: datetime.datetime, metrics: Dict[str, Any] | None = None) Dict[str, Any] | None[source]
Update the storage with the results of the experiment.
- Parameters:
status (Status) – Status of the experiment run.
timestamp (datetime.datetime) – Timestamp of the status and metrics.
metrics (Optional[Dict[str, Any]]) – One or several metrics of the experiment run. Must contain the (float) optimization target if the status is SUCCEEDED.
- Returns:
metrics – Same as metrics, but always in the dict format.
- Return type:
Optional[Dict[str, Any]]
- update_telemetry(status: mlos_bench.environments.status.Status, timestamp: datetime.datetime, metrics: List[Tuple[datetime.datetime, str, Any]]) None[source]
Save the experiment’s telemetry data and intermediate status.
- Parameters:
status (Status) – Current status of the trial.
timestamp (datetime.datetime) – Timestamp of the status (but not the metrics).
metrics (List[Tuple[datetime.datetime, str, Any]]) – Telemetry data.
- Return type:
None