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Convert some unittests to pytest. (#2779)
* Convert multi_node_test.py to pytest. * Convert array_test.py to pytest. * Convert failure_test.py to pytest. * Convert microbenchmarks to pytest. * Convert component_failures_test.py to pytest and some minor quotes changes. * Convert tensorflow_test.py to pytest. * Convert actor_test.py to pytest. * Fix. * Fix
This commit is contained in:
Robert Nishihara
committed by
Philipp Moritz
Philipp Moritz
parent
3813ae34b3
commit
eda6ebb87d
+107
-109
@@ -2,120 +2,118 @@ 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 pytest
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import os
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import unittest
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import ray
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import time
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import numpy as np
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class MicroBenchmarkTest(unittest.TestCase):
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def tearDown(self):
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ray.shutdown()
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def testTiming(self):
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@ray.remote
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def empty_function():
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pass
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@ray.remote
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def trivial_function():
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return 1
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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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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
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# (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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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
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# 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 = 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 "
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"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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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. "
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"d = {}, b = {}".format(d, b))
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else:
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print("WARNING: The caching test was too slow. "
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"d = {}, b = {}".format(d, b))
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@pytest.fixture
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def ray_start_regular():
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# Start the Ray processes.
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ray.init(num_cpus=3)
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yield None
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# The code after the yield will run as teardown code.
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ray.shutdown()
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if __name__ == "__main__":
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unittest.main(verbosity=2)
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def test_timing(ray_start_regular):
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@ray.remote
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def empty_function():
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pass
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@ray.remote
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def trivial_function():
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return 1
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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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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
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# (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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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
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# 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 = 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 "
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"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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def test_cache(ray_start_regular):
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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. "
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"d = {}, b = {}".format(d, b))
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else:
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print("WARNING: The caching test was too slow. "
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"d = {}, b = {}".format(d, b))
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