import json import os import ray import ray._private.test_utils as test_utils from ray.util.placement_group import placement_group, remove_placement_group import time import tqdm if "SMOKE_TEST" in os.environ: MAX_PLACEMENT_GROUPS = 20 else: MAX_PLACEMENT_GROUPS = 1000 def test_many_placement_groups(): # @ray.remote(num_cpus=1, resources={"node": 0.02}) @ray.remote class C1: def ping(self): return "pong" # @ray.remote(num_cpus=1) @ray.remote class C2: def ping(self): return "pong" # @ray.remote(resources={"node": 0.02}) @ray.remote class C3: def ping(self): return "pong" bundle1 = {"node": 0.02, "CPU": 1} bundle2 = {"CPU": 1} bundle3 = {"node": 0.02} pgs = [] for _ in tqdm.trange(MAX_PLACEMENT_GROUPS, desc="Creating pgs"): pg = placement_group(bundles=[bundle1, bundle2, bundle3]) pgs.append(pg) for pg in tqdm.tqdm(pgs, desc="Waiting for pgs to be ready"): ray.get(pg.ready()) actors = [] for pg in tqdm.tqdm(pgs, desc="Scheduling tasks"): actors.append(C1.options(placement_group=pg).remote()) actors.append(C2.options(placement_group=pg).remote()) actors.append(C3.options(placement_group=pg).remote()) not_ready = [actor.ping.remote() for actor in actors] for _ in tqdm.trange(len(actors)): ready, not_ready = ray.wait(not_ready) assert ray.get(*ready) == "pong" for pg in tqdm.tqdm(pgs, desc="Cleaning up pgs"): remove_placement_group(pg) def no_resource_leaks(): return test_utils.no_resource_leaks_excluding_node_resources() ray.init(address="auto") test_utils.wait_for_condition(no_resource_leaks) monitor_actor = test_utils.monitor_memory_usage() start_time = time.time() test_many_placement_groups() end_time = time.time() ray.get(monitor_actor.stop_run.remote()) used_gb, usage = ray.get(monitor_actor.get_peak_memory_info.remote()) print(f"Peak memory usage: {round(used_gb, 2)}GB") print(f"Peak memory usage per processes:\n {usage}") del monitor_actor test_utils.wait_for_condition(no_resource_leaks) rate = MAX_PLACEMENT_GROUPS / (end_time - start_time) print( f"Success! Started {MAX_PLACEMENT_GROUPS} pgs in " f"{end_time - start_time}s. ({rate} pgs/s)" ) if "TEST_OUTPUT_JSON" in os.environ: out_file = open(os.environ["TEST_OUTPUT_JSON"], "w") results = { "pgs_per_second": rate, "num_pgs": MAX_PLACEMENT_GROUPS, "time": end_time - start_time, "success": "1", "_peak_memory": round(used_gb, 2), "_peak_process_memory": usage, } json.dump(results, out_file)