mirror of
https://github.com/wassname/ray.git
synced 2026-07-03 19:48:35 +08:00
Philipp Moritz
113 lines
3.6 KiB
Python
113 lines
3.6 KiB
Python
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
from ray.tune.trial import Trial
|
|
from ray.tune.variant_generator import generate_trials
|
|
|
|
|
|
class TrialScheduler(object):
|
|
CONTINUE = "CONTINUE"
|
|
PAUSE = "PAUSE"
|
|
STOP = "STOP"
|
|
|
|
def on_trial_add(self, trial_runner, trial):
|
|
"""Called when a new trial is added to the trial runner."""
|
|
|
|
raise NotImplementedError
|
|
|
|
def on_trial_error(self, trial_runner, trial):
|
|
"""Notification for the error of trial.
|
|
|
|
This will only be called when the trial is in the RUNNING state."""
|
|
|
|
raise NotImplementedError
|
|
|
|
def on_trial_result(self, trial_runner, trial, result):
|
|
"""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."""
|
|
|
|
raise NotImplementedError
|
|
|
|
def on_trial_complete(self, trial_runner, trial, result):
|
|
"""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."""
|
|
|
|
raise NotImplementedError
|
|
|
|
def on_trial_remove(self, trial_runner, trial):
|
|
"""Called to remove trial.
|
|
|
|
This is called when the trial is in PAUSED or PENDING state. Otherwise,
|
|
call `on_trial_complete`."""
|
|
|
|
raise NotImplementedError
|
|
|
|
def add_experiment(self, experiment, trial_runner):
|
|
"""Adds an experiment to the scheduler.
|
|
|
|
The scheduler is responsible for adding the trials of the experiment
|
|
to the runner, which can be done immediately (if there are a finite
|
|
set of trials), or over time (if there is an infinite stream of trials
|
|
or if the scheduler is iterative in nature).
|
|
"""
|
|
generator = generate_trials(experiment.spec, experiment.name)
|
|
while True:
|
|
try:
|
|
trial_runner.add_trial(next(generator))
|
|
except StopIteration:
|
|
break
|
|
|
|
def choose_trial_to_run(self, trial_runner):
|
|
"""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."""
|
|
|
|
raise NotImplementedError
|
|
|
|
def debug_string(self):
|
|
"""Returns a human readable message for printing to the console."""
|
|
|
|
raise NotImplementedError
|
|
|
|
|
|
class FIFOScheduler(TrialScheduler):
|
|
"""Simple scheduler that just runs trials in submission order."""
|
|
|
|
def on_trial_add(self, trial_runner, trial):
|
|
pass
|
|
|
|
def on_trial_error(self, trial_runner, trial):
|
|
pass
|
|
|
|
def on_trial_result(self, trial_runner, trial, result):
|
|
return TrialScheduler.CONTINUE
|
|
|
|
def on_trial_complete(self, trial_runner, trial, result):
|
|
pass
|
|
|
|
def on_trial_remove(self, trial_runner, trial):
|
|
pass
|
|
|
|
def choose_trial_to_run(self, trial_runner):
|
|
for trial in trial_runner.get_trials():
|
|
if (trial.status == Trial.PENDING
|
|
and trial_runner.has_resources(trial.resources)):
|
|
return trial
|
|
for trial in trial_runner.get_trials():
|
|
if (trial.status == Trial.PAUSED
|
|
and trial_runner.has_resources(trial.resources)):
|
|
return trial
|
|
return None
|
|
|
|
def debug_string(self):
|
|
return "Using FIFO scheduling algorithm."
|