mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
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.
115 lines
4 KiB
Python
115 lines
4 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 os
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import unittest
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import ray
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import sys
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import time
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import numpy as np
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if sys.version_info >= (3, 0):
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from importlib import reload
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import ray.test.test_functions as test_functions
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class MicroBenchmarkTest(unittest.TestCase):
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def testTiming(self):
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reload(test_functions)
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ray.init(num_workers=3)
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# measure the time required to submit a remote task to the scheduler
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elapsed_times = []
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for _ in range(1000):
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start_time = time.time()
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test_functions.empty_function.remote()
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end_time = time.time()
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elapsed_times.append(end_time - start_time)
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elapsed_times = np.sort(elapsed_times)
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average_elapsed_time = sum(elapsed_times) / 1000
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print("Time required to submit an empty function call:")
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print(" Average: {}".format(average_elapsed_time))
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print(" 90th percentile: {}".format(elapsed_times[900]))
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print(" 99th percentile: {}".format(elapsed_times[990]))
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print(" worst: {}".format(elapsed_times[999]))
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# average_elapsed_time should be about 0.00038
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# measure the time required to submit a remote task to the scheduler (where the remote task returns one value)
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elapsed_times = []
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for _ in range(1000):
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start_time = time.time()
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test_functions.trivial_function.remote()
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end_time = time.time()
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elapsed_times.append(end_time - start_time)
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elapsed_times = np.sort(elapsed_times)
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average_elapsed_time = sum(elapsed_times) / 1000
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print("Time required to submit a trivial function call:")
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print(" Average: {}".format(average_elapsed_time))
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print(" 90th percentile: {}".format(elapsed_times[900]))
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print(" 99th percentile: {}".format(elapsed_times[990]))
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print(" worst: {}".format(elapsed_times[999]))
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# average_elapsed_time should be about 0.001
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# measure the time required to submit a remote task to the scheduler and get the result
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elapsed_times = []
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for _ in range(1000):
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start_time = time.time()
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x = test_functions.trivial_function.remote()
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ray.get(x)
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end_time = time.time()
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elapsed_times.append(end_time - start_time)
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elapsed_times = np.sort(elapsed_times)
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average_elapsed_time = sum(elapsed_times) / 1000
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print("Time required to submit a trivial function call and get the result:")
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print(" Average: {}".format(average_elapsed_time))
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print(" 90th percentile: {}".format(elapsed_times[900]))
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print(" 99th percentile: {}".format(elapsed_times[990]))
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print(" worst: {}".format(elapsed_times[999]))
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# average_elapsed_time should be about 0.0013
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# measure the time required to do do a put
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elapsed_times = []
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for _ in range(1000):
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start_time = time.time()
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ray.put(1)
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end_time = time.time()
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elapsed_times.append(end_time - start_time)
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elapsed_times = np.sort(elapsed_times)
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average_elapsed_time = sum(elapsed_times) / 1000
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print("Time required to put an int:")
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print(" Average: {}".format(average_elapsed_time))
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print(" 90th percentile: {}".format(elapsed_times[900]))
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print(" 99th percentile: {}".format(elapsed_times[990]))
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print(" worst: {}".format(elapsed_times[999]))
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# average_elapsed_time should be about 0.00087
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ray.worker.cleanup()
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def testCache(self):
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ray.init(num_workers=1)
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A = np.random.rand(1, 1000000)
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v = np.random.rand(1000000)
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A_id = ray.put(A)
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v_id = ray.put(v)
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a = time.time()
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for i in range(100):
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A.dot(v)
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b = time.time() - a
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c = time.time()
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for i in range(100):
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ray.get(A_id).dot(ray.get(v_id))
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d = time.time() - c
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if d > 1.5 * b:
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if os.getenv("TRAVIS") is None:
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raise Exception("The caching test was too slow. d = {}, b = {}".format(d, b))
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else:
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print("WARNING: The caching test was too slow. d = {}, b = {}".format(d, b))
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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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