class ray.tune.schedulers.FIFOScheduler[source]#

Bases: ray.tune.schedulers.trial_scheduler.TrialScheduler

Simple scheduler that just runs trials in submission order.

PublicAPI: This API is stable across Ray releases.

on_trial_add(trial_runner: ray.tune.execution.trial_runner.TrialRunner, trial: ray.tune.experiment.trial.Trial)[source]#

Called when a new trial is added to the trial runner.

on_trial_error(trial_runner: ray.tune.execution.trial_runner.TrialRunner, trial: ray.tune.experiment.trial.Trial)[source]#

Notification for the error of trial.

This will only be called when the trial is in the RUNNING state.

on_trial_result(trial_runner: ray.tune.execution.trial_runner.TrialRunner, trial: ray.tune.experiment.trial.Trial, result: Dict) str[source]#

Called on each intermediate result returned by a trial.

At this point, the trial scheduler can make a decision by returning one of CONTINUE, PAUSE, and STOP. This will only be called when the trial is in the RUNNING state.

on_trial_complete(trial_runner: ray.tune.execution.trial_runner.TrialRunner, trial: ray.tune.experiment.trial.Trial, result: Dict)[source]#

Notification for the completion of trial.

This will only be called when the trial is in the RUNNING state and either completes naturally or by manual termination.

on_trial_remove(trial_runner: ray.tune.execution.trial_runner.TrialRunner, trial: ray.tune.experiment.trial.Trial)[source]#

Called to remove trial.

This is called when the trial is in PAUSED or PENDING state. Otherwise, call on_trial_complete.

choose_trial_to_run(trial_runner: ray.tune.execution.trial_runner.TrialRunner) Optional[ray.tune.experiment.trial.Trial][source]#

Called to choose a new trial to run.

This should return one of the trials in trial_runner that is in the PENDING or PAUSED state. This function must be idempotent.

If no trial is ready, return None.

debug_string() str[source]#

Returns a human readable message for printing to the console.