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Deprecate non-direct-call API (#7336)

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This commit is contained in:
Edward Oakes
2020-02-27 10:37:23 -08:00
committed by GitHub
parent 55ccfb6089
commit d9027acaf2
16 changed files with 77 additions and 426 deletions
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python/ray/tests/test_advanced.py
+1 -89
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@@ -12,7 +12,6 @@ import numpy as np
import pytest
import ray
import ray.ray_constants as ray_constants
import ray.cluster_utils
import ray.test_utils
@@ -247,7 +246,7 @@ def test_wait_cluster(ray_start_cluster):
assert len(unready) == 0
@pytest.mark.skipif(ray_constants.direct_call_enabled(), reason="TODO(ekl)")
@pytest.mark.skip(reason="TODO(ekl)")
def test_object_transfer_dump(ray_start_cluster):
cluster = ray_start_cluster
@@ -507,93 +506,6 @@ def test_multithreading(ray_start_2_cpus):
ray.get(actor.join.remote()) == "ok"
@pytest.mark.skipif(
ray_constants.direct_call_enabled(), reason="uses task and object table")
def test_free_objects_multi_node(ray_start_cluster):
# This test will do following:
# 1. Create 3 raylets that each hold an actor.
# 2. Each actor creates an object which is the deletion target.
# 3. Wait 0.1 second for the objects to be deleted.
# 4. Check that the deletion targets have been deleted.
# Caution: if remote functions are used instead of actor methods,
# one raylet may create more than one worker to execute the
# tasks, so the flushing operations may be executed in different
# workers and the plasma client holding the deletion target
# may not be flushed.
cluster = ray_start_cluster
config = json.dumps({"object_manager_repeated_push_delay_ms": 1000})
for i in range(3):
cluster.add_node(
num_cpus=1,
resources={"Custom{}".format(i): 1},
_internal_config=config)
ray.init(address=cluster.address)
class RawActor:
def get(self):
return ray.worker.global_worker.node.unique_id
ActorOnNode0 = ray.remote(resources={"Custom0": 1})(RawActor)
ActorOnNode1 = ray.remote(resources={"Custom1": 1})(RawActor)
ActorOnNode2 = ray.remote(resources={"Custom2": 1})(RawActor)
def create(actors):
a = actors[0].get.remote()
b = actors[1].get.remote()
c = actors[2].get.remote()
(l1, l2) = ray.wait([a, b, c], num_returns=3)
assert len(l1) == 3
assert len(l2) == 0
return (a, b, c)
def run_one_test(actors, local_only, delete_creating_tasks):
(a, b, c) = create(actors)
# The three objects should be generated on different object stores.
assert ray.get(a) != ray.get(b)
assert ray.get(a) != ray.get(c)
assert ray.get(c) != ray.get(b)
ray.internal.free(
[a, b, c],
local_only=local_only,
delete_creating_tasks=delete_creating_tasks)
# Wait for the objects to be deleted.
time.sleep(0.1)
return (a, b, c)
actors = [
ActorOnNode0.remote(),
ActorOnNode1.remote(),
ActorOnNode2.remote()
]
# Case 1: run this local_only=False. All 3 objects will be deleted.
(a, b, c) = run_one_test(actors, False, False)
(l1, l2) = ray.wait([a, b, c], timeout=0.01, num_returns=1)
# All the objects are deleted.
assert len(l1) == 0
assert len(l2) == 3
# Case 2: run this local_only=True. Only 1 object will be deleted.
(a, b, c) = run_one_test(actors, True, False)
(l1, l2) = ray.wait([a, b, c], timeout=0.01, num_returns=3)
# One object is deleted and 2 objects are not.
assert len(l1) == 2
assert len(l2) == 1
# The deleted object will have the same store with the driver.
local_return = ray.worker.global_worker.node.unique_id
for object_id in l1:
assert ray.get(object_id) != local_return
# Case3: These cases test the deleting creating tasks for the object.
(a, b, c) = run_one_test(actors, False, False)
task_table = ray.tasks()
for obj in [a, b, c]:
assert ray._raylet.compute_task_id(obj).hex() in task_table
(a, b, c) = run_one_test(actors, False, True)
task_table = ray.tasks()
for obj in [a, b, c]:
assert ray._raylet.compute_task_id(obj).hex() not in task_table
def test_local_mode(shutdown_only):
@ray.remote
def local_mode_f():