wehub-resource-sync
120 lines
3.9 KiB
Python
120 lines
3.9 KiB
Python
import sys
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import time
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import numpy as np
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import pytest
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import ray
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import ray._private.ray_constants as ray_constants
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from ray._private.test_utils import get_other_nodes
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@pytest.mark.parametrize(
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"ray_start_cluster",
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[{"num_cpus": 4, "num_nodes": 3, "do_init": True}],
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indirect=True,
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)
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def test_actor_creation_node_failure(ray_start_cluster):
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# TODO(swang): Refactor test_raylet_failed, etc to reuse the below code.
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cluster = ray_start_cluster
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@ray.remote
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class Child:
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def __init__(self, death_probability):
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self.death_probability = death_probability
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def get_probability(self):
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return self.death_probability
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def ping(self):
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# Exit process with some probability.
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exit_chance = np.random.rand()
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if exit_chance < self.death_probability:
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sys.exit(-1)
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num_children = 25
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# Children actors will die about half the time.
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death_probability = 0.5
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children = [Child.remote(death_probability) for _ in range(num_children)]
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while len(cluster.list_all_nodes()) > 1:
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for j in range(2):
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# Submit some tasks on the actors. About half of the actors will
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# fail.
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children_out = [child.ping.remote() for child in children]
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# Wait a while for all the tasks to complete. This should trigger
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# reconstruction for any actor creation tasks that were forwarded
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# to nodes that then failed.
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ready, _ = ray.wait(
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children_out, num_returns=len(children_out), timeout=5 * 60.0
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)
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assert len(ready) == len(children_out)
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# Replace any actors that died.
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for i, out in enumerate(children_out):
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try:
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ray.get(out)
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except ray.exceptions.RayActorError:
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children[i] = Child.remote(death_probability)
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children_out = [child.get_probability.remote() for child in children]
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# Wait for new created actors to finish creation before
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# removing a node. This is needed because right now we don't
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# support reconstructing actors that died in the process of
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# being created.
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ready, _ = ray.wait(
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children_out, num_returns=len(children_out), timeout=5 * 60.0
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)
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assert len(ready) == len(children_out)
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# Remove a node. Any actor creation tasks that were forwarded to this
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# node must be restarted.
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cluster.remove_node(get_other_nodes(cluster, True)[-1])
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def test_driver_lives_sequential(ray_start_regular):
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ray._private.worker._global_node.kill_raylet()
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ray._private.worker._global_node.kill_log_monitor()
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ray._private.worker._global_node.kill_monitor()
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# If the driver can reach the tearDown method, then it is still alive.
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def test_driver_lives_parallel(ray_start_regular):
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all_processes = ray._private.worker._global_node.all_processes
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process_infos = (
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all_processes[ray_constants.PROCESS_TYPE_RAYLET]
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+ all_processes[ray_constants.PROCESS_TYPE_LOG_MONITOR]
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+ all_processes[ray_constants.PROCESS_TYPE_MONITOR]
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)
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# Kill all the components in parallel.
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for process_info in process_infos:
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process_info.process.terminate()
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time.sleep(0.1)
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for process_info in process_infos:
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process_info.process.kill()
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for process_info in process_infos:
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process_info.process.wait()
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# If the driver can reach the tearDown method, then it is still alive.
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def test_dying_worker(ray_start_2_cpus):
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@ray.remote(num_cpus=0, max_calls=1)
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def foo():
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pass
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for _ in range(20):
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ray.get([foo.remote() for _ in range(5)])
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# Make sure that nothing has died.
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assert ray._private.services.remaining_processes_alive()
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if __name__ == "__main__":
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sys.exit(pytest.main(["-sv", __file__]))
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