def check_actor_restart():
actors = list(ray.state.actors().values())
assert len(actors) == 1
print(actors)
return (actors[0]["State"] == convert_actor_state(
gcs_utils.ActorTableData.ALIVE) and actors[0]["NumRestarts"] == 1)
def _all_actors_dead():
return all(
actor["State"] == convert_actor_state(gcs_utils.ActorTableData.DEAD)
for actor in list(ray.state.actors().values()))
def test_capture_child_actors(ray_start_cluster, connect_to_client):
cluster = ray_start_cluster
total_num_actors = 4
for _ in range(2):
cluster.add_node(num_cpus=total_num_actors)
ray.init(address=cluster.address)
with connect_to_client_or_not(connect_to_client):
pg = ray.util.placement_group([{
"CPU": 2
}, {
"CPU": 2
}],
strategy="STRICT_PACK")
ray.get(pg.ready())
# If get_current_placement_group is used when the current worker/driver
# doesn't belong to any of placement group, it should return None.
assert get_current_placement_group() is None
# Test actors first.
@ray.remote(num_cpus=1)
class NestedActor:
def ready(self):
return True
@ray.remote(num_cpus=1)
class Actor:
def __init__(self):
self.actors = []
def ready(self):
return True
def schedule_nested_actor(self):
# Make sure we can capture the current placement group.
assert get_current_placement_group() is not None
# Actors should be implicitly captured.
actor = NestedActor.remote()
ray.get(actor.ready.remote())
self.actors.append(actor)
def schedule_nested_actor_outside_pg(self):
# Don't use placement group.
actor = NestedActor.options(placement_group=None).remote()
ray.get(actor.ready.remote())
self.actors.append(actor)
a = Actor.options(placement_group=pg,
placement_group_capture_child_tasks=True).remote()
ray.get(a.ready.remote())
# 1 top level actor + 3 children.
for _ in range(total_num_actors - 1):
ray.get(a.schedule_nested_actor.remote())
# Make sure all the actors are scheduled on the same node.
# (why? The placement group has STRICT_PACK strategy).
node_id_set = set()
for actor_info in ray.state.actors().values():
if actor_info["State"] == convert_actor_state(
gcs_utils.ActorTableData.ALIVE):
node_id = actor_info["Address"]["NodeID"]
node_id_set.add(node_id)
# Since all node id should be identical, set should be equal to 1.
assert len(node_id_set) == 1
# Kill an actor and wait until it is killed.
kill_actor_and_wait_for_failure(a)
with pytest.raises(ray.exceptions.RayActorError):
ray.get(a.ready.remote())
# Now create an actor, but do not capture the current tasks
a = Actor.options(placement_group=pg).remote()
ray.get(a.ready.remote())
# 1 top level actor + 3 children.
for _ in range(total_num_actors - 1):
ray.get(a.schedule_nested_actor.remote())
# Make sure all the actors are not scheduled on the same node.
# It is because the child tasks are not scheduled on the same
# placement group.
node_id_set = set()
for actor_info in ray.state.actors().values():
if actor_info["State"] == convert_actor_state(
gcs_utils.ActorTableData.ALIVE):
node_id = actor_info["Address"]["NodeID"]
node_id_set.add(node_id)
assert len(node_id_set) == 2
# Kill an actor and wait until it is killed.
kill_actor_and_wait_for_failure(a)
with pytest.raises(ray.exceptions.RayActorError):
ray.get(a.ready.remote())
# Lastly, make sure when None is specified, actors are not scheduled
# on the same placement group.
a = Actor.options(placement_group=pg).remote()
ray.get(a.ready.remote())
# 1 top level actor + 3 children.
for _ in range(total_num_actors - 1):
ray.get(a.schedule_nested_actor_outside_pg.remote())
# Make sure all the actors are not scheduled on the same node.
# It is because the child tasks are not scheduled on the same
# placement group.
node_id_set = set()
for actor_info in ray.state.actors().values():
if actor_info["State"] == convert_actor_state(
gcs_utils.ActorTableData.ALIVE):
node_id = actor_info["Address"]["NodeID"]
node_id_set.add(node_id)
assert len(node_id_set) == 2