Enable direct calls by default (#6367)

* wip * add * timeout fix * const ref * comments * fix * fix * Move actor state into actor handle * comments 2 * enable by default * temp reorder * some fixes * add debug code * tmp * fix * wip * remove dbg * fix compile * fix * fix check * remove non direct tests * Increment ref count before resolving value * rename * fix another bug * tmp * tmp * Fix object pinning * build change * lint * ActorManager * tmp * ActorManager * fix test component failures * Remove old code * Remove unused * fix * fix * fix resources * fix advanced * eric's diff * blacklist * blacklist * cleanup * annotate * disable tests for now * remove * fix * fix * clean up verbosity * fix test * fix concurrency test * Update .travis.yml * Update .travis.yml * Update .travis.yml * split up analysis suite * split up trial runner suite * fix detached direct actors * fix * split up advanced tesT * lint * fix core worker test hang * fix bad check fail which breaks test_cluster.py in tune * fix some minor diffs in test_cluster * less workers * make less stressful * split up test * retry flaky tests * remove old test flags * fixes * lint * Update worker_pool.cc * fix race * fix * fix bugs in node failure handling * fix race condition * fix bugs in node failure handling * fix race condition * nits * fix test * disable heartbeatS * disable heartbeatS * fix * fix * use worker id * fix max fail * debug exit * fix merge, and apply [PATCH] fix concurrency test * [patch] fix core worker test hang * remove NotifyActorCreation, and return worker on completion of actor creation task * remove actor diied callback * Update core_worker.cc * lint * use task manager * fix merge * fix deadlock * wip * merge conflits * fix * better sysexit handling * better sysexit handling * better sysexit handling * check id * better debug * task failed msg * task failed msg * retry failed tasks with delay * retry failed tasks with delay * clip deps * fix * fix core worker tests * fix task manager test * fix all tests * cleanup * set to 0 for direct tests * dont check worker id for ownership rpc * dont check worker id for ownership rpc * debug messages * add comment * remove debug statements * nit * check worker id * fix test * owner * fix tests
2026-07-14 11:17:54 +08:00 · 2019-12-13 13:58:04 -08:00
parent 3754effafc
commit be5dd8eb5e
16 changed files with 174 additions and 362 deletions
@@ -151,19 +151,22 @@ def main():

    timeit("1:1 actor calls async", actor_async, 1000)

-    a = Actor.options(is_direct_call=True).remote()
+    a = Actor.options(max_concurrency=16).remote()

    def actor_concurrent():
        ray.get([a.small_value.remote() for _ in range(1000)])

-    timeit("1:1 direct actor calls async", actor_concurrent, 1000)
+    timeit("1:1 actor calls concurrent", actor_concurrent, 1000)

-    a = Actor.options(is_direct_call=True, max_concurrency=16).remote()
+    n = 5000
+    n_cpu = multiprocessing.cpu_count() // 2
+    actors = [Actor._remote() for _ in range(n_cpu)]
+    client = Client.remote(actors)

-    def actor_concurrent():
-        ray.get([a.small_value.remote() for _ in range(1000)])
+    def actor_async_direct():
+        ray.get(client.small_value_batch.remote(n))

-    timeit("1:1 direct actor calls concurrent", actor_concurrent, 1000)
+    timeit("1:n actor calls async", actor_async_direct, n * len(actors))

    n_cpu = multiprocessing.cpu_count() // 2
    a = [Actor.remote() for _ in range(n_cpu)]
@@ -177,44 +180,16 @@ def main():

    timeit("n:n actor calls async", actor_multi2, m * n)

-    n = 5000
-    n_cpu = multiprocessing.cpu_count() // 2
-    actors = [Actor._remote(is_direct_call=True) for _ in range(n_cpu)]
-    client = Client.remote(actors)
-
-    def actor_async_direct():
-        ray.get(client.small_value_batch.remote(n))
-
-    timeit("1:n direct actor calls async", actor_async_direct, n * len(actors))
-
-    clients = [Client.remote(a) for a in actors]
-
-    def actor_multi2_direct():
-        ray.get([c.small_value_batch.remote(n) for c in clients])
-
-    timeit("n:n direct actor calls async", actor_multi2_direct,
-           n * len(clients))
-
    n = 1000
-    actors = [Actor._remote(is_direct_call=True) for _ in range(n_cpu)]
+    actors = [Actor._remote() for _ in range(n_cpu)]
    clients = [Client.remote(a) for a in actors]

    def actor_multi2_direct_arg():
        ray.get([c.small_value_batch_arg.remote(n) for c in clients])

-    timeit("n:n direct actor calls with arg async", actor_multi2_direct_arg,
+    timeit("n:n actor calls with arg async", actor_multi2_direct_arg,
           n * len(clients))

-    n = 1000
-    actors = [Actor._remote(is_direct_call=True) for _ in range(n_cpu)]
-    clients = [Client.remote(a) for a in actors]
-
-    def actor_multi2_direct_arg():
-        ray.get([c.small_value_batch_arg.remote(n) for c in clients])
-
-    timeit("multi client direct actor calls with arg async",
-           actor_multi2_direct_arg, n * len(clients))
-

 if __name__ == "__main__":
    main()