LocalMetadataRunner

class axtreme.runner.LocalMetadataRunner(evaluation_function: EvaluationFunction)

Bases: Runner

Except for the addition of evauation_function this is coppied exactly from ax.runners.SyntheticRunner.

__init__(evaluation_function: EvaluationFunction) → None

Methods

__init__(evaluation_function)
clone()	Create a copy of this Runner.
deserialize_init_args(args[, ...])	Given a dictionary, deserialize the properties needed to initialize the object.
poll_available_capacity()	Checks how much available capacity there is to schedule trial evaluations.
poll_exception(trial)	Returns the exception from a trial.
poll_trial_status(trials)	Checks the status of any non-terminal trials and returns their indices as a mapping from TrialStatus to a list of indices.
run(trial)	Deploys a trial based on custom runner subclass implementation.
run_multiple(trials)	Runs a single evaluation for each of the given trials.
serialize_init_args(obj)	Serialize the properties needed to initialize the object.
stop(trial[, reason])	Stop a trial based on custom runner subclass implementation.

Attributes

db_id
run_metadata_report_keys	A list of keys of the metadata dict returned by run() that are relevant outside the runner-internal impolementation.
staging_required	Whether the trial goes to staged or running state once deployed.

poll_trial_status(trials: Iterable[BaseTrial]) → dict[TrialStatus, set[int]]

Checks the status of any non-terminal trials and returns their indices as a mapping from TrialStatus to a list of indices. Required for runners used with Ax Scheduler.

NOTE: Does not need to handle waiting between polling calls while trials are running; this function should just perform a single poll.

Parameters:

trials – Trials to poll.

Returns:

A dictionary mapping TrialStatus to a list of trial indices that have the respective status at the time of the polling. This does not need to include trials that at the time of polling already have a terminal (ABANDONED, FAILED, COMPLETED) status (but it may).

run(trial: BaseTrial) → dict[str, Any]

Deploys a trial based on custom runner subclass implementation.

Parameters:

trial – The trial to deploy.

Returns:

Dict of run metadata from the deployment process.

property run_metadata_report_keys: list[str]

A list of keys of the metadata dict returned by run() that are relevant outside the runner-internal impolementation. These can e.g. be reported in Scheduler.report_results().