ray.tune.schedulers.TrialScheduler

class ray.tune.schedulers.TrialScheduler

Bases: object

Interface for implementing a Trial Scheduler class.

Note to Tune developers: If a new scheduler is added, please update air/_internal/usage.py.

DeveloperAPI: This API may change across minor Ray releases.

Methods

choose_trial_to_run(tune_controller)	Called to choose a new trial to run.
debug_string()	Returns a human readable message for printing to the console.
on_trial_add(tune_controller, trial)	Called when a new trial is added to the trial runner.
on_trial_complete(tune_controller, trial, result)	Notification for the completion of trial.
on_trial_error(tune_controller, trial)	Notification for the error of trial.
on_trial_remove(tune_controller, trial)	Called to remove trial.
on_trial_result(tune_controller, trial, result)	Called on each intermediate result returned by a trial.
restore(checkpoint_path)	Restore trial scheduler from checkpoint.
save(checkpoint_path)	Save trial scheduler to a checkpoint
set_search_properties(metric, mode, **spec)	Pass search properties to scheduler.

Attributes

CONTINUE	Status for continuing trial execution
NOOP
PAUSE	Status for pausing trial execution
STOP	Status for stopping trial execution
metric
supports_buffered_results