def testMultiStepRun(self):
ray.init(num_cpus=4, num_gpus=2)
kwargs = {
"stopping_criterion": {
"training_iteration": 5
},
"resources": Resources(cpu=1, gpu=1),
}
trials = [Trial("__fake", **kwargs), Trial("__fake", **kwargs)]
snapshot = TrialStatusSnapshot()
runner = TrialRunner(callbacks=[TrialStatusSnapshotTaker(snapshot)])
for t in trials:
runner.add_trial(t)
while not runner.is_finished():
runner.step()
self.assertTrue(snapshot.all_trials_are_terminated())
def testExtraCustomResources(self):
ray.init(num_cpus=4, num_gpus=2, resources={"a": 2})
# Since each trial will occupy the full custom resources,
# there are at most 1 trial running at any given moment.
snapshot = TrialStatusSnapshot()
runner = TrialRunner(callbacks=[TrialStatusSnapshotTaker(snapshot)])
kwargs = {
"stopping_criterion": {"training_iteration": 1},
"placement_group_factory": PlacementGroupFactory([{"CPU": 1}, {"a": 2}]),
}
trials = [Trial("__fake", **kwargs), Trial("__fake", **kwargs)]
for t in trials:
runner.add_trial(t)
while not runner.is_finished():
runner.step()
self.assertLess(snapshot.max_running_trials(), 2)
self.assertTrue(snapshot.all_trials_are_terminated())
def testExtraResources(self):
ray.init(num_cpus=4, num_gpus=2)
snapshot = TrialStatusSnapshot()
runner = TrialRunner(callbacks=[TrialStatusSnapshotTaker(snapshot)])
kwargs = {
"stopping_criterion": {"training_iteration": 1},
"placement_group_factory": PlacementGroupFactory(
[{"CPU": 1}, {"CPU": 3, "GPU": 1}]
),
}
trials = [Trial("__fake", **kwargs), Trial("__fake", **kwargs)]
for t in trials:
runner.add_trial(t)
while not runner.is_finished():
runner.step()
self.assertLess(snapshot.max_running_trials(), 2)
self.assertTrue(snapshot.all_trials_are_terminated())
