mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
69 lines
1.8 KiB
Python
69 lines
1.8 KiB
Python
import json
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import os
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import ray
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import ray._private.test_utils as test_utils
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import time
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import tqdm
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if "SMOKE_TEST" in os.environ:
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MAX_ACTORS_IN_CLUSTER = 100
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else:
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MAX_ACTORS_IN_CLUSTER = 10000
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def test_max_actors():
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# TODO (Alex): Dynamically set this based on number of cores
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cpus_per_actor = 0.25
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@ray.remote(num_cpus=cpus_per_actor)
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class Actor:
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def foo(self):
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pass
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actors = [
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Actor.remote()
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for _ in tqdm.trange(MAX_ACTORS_IN_CLUSTER, desc="Launching actors")
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]
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not_ready = [actor.foo.remote() for actor in actors]
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for _ in tqdm.trange(len(actors)):
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ready, not_ready = ray.wait(not_ready)
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assert ray.get(*ready) is None
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def no_resource_leaks():
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return ray.available_resources() == ray.cluster_resources()
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ray.init(address="auto")
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test_utils.wait_for_condition(no_resource_leaks)
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monitor_actor = test_utils.monitor_memory_usage()
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start_time = time.time()
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test_max_actors()
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end_time = time.time()
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ray.get(monitor_actor.stop_run.remote())
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used_gb, usage = ray.get(monitor_actor.get_peak_memory_info.remote())
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print(f"Peak memory usage: {round(used_gb, 2)}GB")
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print(f"Peak memory usage per processes:\n {usage}")
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del monitor_actor
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test_utils.wait_for_condition(no_resource_leaks)
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rate = MAX_ACTORS_IN_CLUSTER / (end_time - start_time)
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print(
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f"Success! Started {MAX_ACTORS_IN_CLUSTER} actors in "
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f"{end_time - start_time}s. ({rate} actors/s)"
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)
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if "TEST_OUTPUT_JSON" in os.environ:
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out_file = open(os.environ["TEST_OUTPUT_JSON"], "w")
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results = {
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"actors_per_second": rate,
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"num_actors": MAX_ACTORS_IN_CLUSTER,
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"time": end_time - start_time,
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"success": "1",
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"_peak_memory": round(used_gb, 2),
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"_peak_process_memory": usage,
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}
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json.dump(results, out_file)
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