mirror of
https://github.com/vale981/ray
synced 2025-03-09 04:46:38 -04:00
be4a37bf37
* Remove start_ray_local from ray.init and change default number of workers to 10. * Remove alexnet example. * Move array methods to experimental. * Remove TRPO example. * Remove old files. * Compile plasma when we build numbuf. * Address comments.
112 lines
3 KiB
Python
112 lines
3 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import unittest
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import ray
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import numpy as np
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import time
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class TaskTests(unittest.TestCase):
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def testSubmittingTasks(self):
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for num_local_schedulers in [1, 4]:
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for num_workers_per_scheduler in [4]:
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num_workers = num_local_schedulers * num_workers_per_scheduler
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ray.worker._init(start_ray_local=True, num_workers=num_workers,
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num_local_schedulers=num_local_schedulers)
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@ray.remote
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def f(x):
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return x
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for _ in range(1):
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ray.get([f.remote(1) for _ in range(1000)])
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for _ in range(10):
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ray.get([f.remote(1) for _ in range(100)])
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for _ in range(100):
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ray.get([f.remote(1) for _ in range(10)])
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for _ in range(1000):
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ray.get([f.remote(1) for _ in range(1)])
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self.assertTrue(ray.services.all_processes_alive())
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ray.worker.cleanup()
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def testDependencies(self):
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for num_local_schedulers in [1, 4]:
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for num_workers_per_scheduler in [4]:
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num_workers = num_local_schedulers * num_workers_per_scheduler
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ray.worker._init(start_ray_local=True, num_workers=num_workers,
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num_local_schedulers=num_local_schedulers)
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@ray.remote
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def f(x):
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return x
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x = 1
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for _ in range(1000):
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x = f.remote(x)
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ray.get(x)
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@ray.remote
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def g(*xs):
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return 1
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xs = [g.remote(1)]
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for _ in range(100):
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xs.append(g.remote(*xs))
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xs.append(g.remote(1))
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ray.get(xs)
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self.assertTrue(ray.services.all_processes_alive())
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ray.worker.cleanup()
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def testGettingAndPutting(self):
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ray.init(num_workers=1)
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for n in range(8):
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x = np.zeros(10 ** n)
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for _ in range(100):
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ray.put(x)
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x_id = ray.put(x)
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for _ in range(1000):
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ray.get(x_id)
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self.assertTrue(ray.services.all_processes_alive())
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ray.worker.cleanup()
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def testWait(self):
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for num_local_schedulers in [1, 4]:
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for num_workers_per_scheduler in [4]:
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num_workers = num_local_schedulers * num_workers_per_scheduler
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ray.worker._init(start_ray_local=True, num_workers=num_workers,
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num_local_schedulers=num_local_schedulers)
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@ray.remote
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def f(x):
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return x
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x_ids = [f.remote(i) for i in range(100)]
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for i in range(len(x_ids)):
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ray.wait([x_ids[i]])
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for i in range(len(x_ids) - 1):
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ray.wait(x_ids[i:])
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@ray.remote
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def g(x):
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time.sleep(x)
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for i in range(1, 5):
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x_ids = [g.remote(np.random.uniform(0, i)) for _ in range(2 * num_workers)]
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ray.wait(x_ids, num_returns=len(x_ids))
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self.assertTrue(ray.services.all_processes_alive())
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ray.worker.cleanup()
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if __name__ == "__main__":
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unittest.main(verbosity=2)
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