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185 lines
6.0 KiB
185 lines
6.0 KiB
#!/usr/bin/python2
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#
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# Copyright 2015 The ANGLE Project Authors. All rights reserved.
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# Use of this source code is governed by a BSD-style license that can be
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# found in the LICENSE file.
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#
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# perf_test_runner.py:
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# Helper script for running and analyzing perftest results. Runs the
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# tests in an infinite batch, printing out the mean and coefficient of
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# variation of the population continuously.
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#
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import argparse
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import glob
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import logging
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import os
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import re
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import subprocess
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import sys
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base_path = os.path.abspath(os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
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# Look for a [Rr]elease build.
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TEST_SUITE_SEARCH_PATH = glob.glob('out/*elease*')
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DEFAULT_METRIC = 'wall_time'
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DEFAULT_EXPERIMENTS = 10
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DEFAULT_TEST_SUITE = 'angle_perftests'
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if sys.platform == 'win32':
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DEFAULT_TEST_NAME = 'DrawCallPerfBenchmark.Run/d3d11_null'
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else:
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DEFAULT_TEST_NAME = 'DrawCallPerfBenchmark.Run/gl'
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EXIT_SUCCESS = 0
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EXIT_FAILURE = 1
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scores = []
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# Danke to http://stackoverflow.com/a/27758326
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def mean(data):
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"""Return the sample arithmetic mean of data."""
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n = len(data)
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if n < 1:
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raise ValueError('mean requires at least one data point')
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return float(sum(data)) / float(n) # in Python 2 use sum(data)/float(n)
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def sum_of_square_deviations(data, c):
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"""Return sum of square deviations of sequence data."""
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ss = sum((float(x) - c)**2 for x in data)
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return ss
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def coefficient_of_variation(data):
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"""Calculates the population coefficient of variation."""
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n = len(data)
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if n < 2:
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raise ValueError('variance requires at least two data points')
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c = mean(data)
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ss = sum_of_square_deviations(data, c)
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pvar = ss / n # the population variance
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stddev = (pvar**0.5) # population standard deviation
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return stddev / c
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def truncated_list(data, n):
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"""Compute a truncated list, n is truncation size"""
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if len(data) < n * 2:
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raise ValueError('list not large enough to truncate')
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return sorted(data)[n:-n]
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def truncated_mean(data, n):
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"""Compute a truncated mean, n is truncation size"""
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return mean(truncated_list(data, n))
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def truncated_cov(data, n):
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"""Compute a truncated coefficient of variation, n is truncation size"""
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return coefficient_of_variation(truncated_list(data, n))
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def main(raw_args):
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'--suite',
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help='Test suite binary. Default is "%s".' % DEFAULT_TEST_SUITE,
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default=DEFAULT_TEST_SUITE)
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parser.add_argument(
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'-m',
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'--metric',
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help='Test metric. Default is "%s".' % DEFAULT_METRIC,
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default=DEFAULT_METRIC)
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parser.add_argument(
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'--experiments',
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help='Number of experiments to run. Default is %d.' % DEFAULT_EXPERIMENTS,
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default=DEFAULT_EXPERIMENTS,
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type=int)
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parser.add_argument('-v', '--verbose', help='Extra verbose logging.', action='store_true')
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parser.add_argument('test_name', help='Test to run', default=DEFAULT_TEST_NAME)
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args, extra_args = parser.parse_known_args(raw_args)
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if args.verbose:
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logging.basicConfig(level='DEBUG')
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if sys.platform == 'win32':
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args.suite += '.exe'
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# Find most recent binary
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newest_binary = None
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newest_mtime = None
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for path in TEST_SUITE_SEARCH_PATH:
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binary_path = os.path.join(base_path, path, args.suite)
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if os.path.exists(binary_path):
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binary_mtime = os.path.getmtime(binary_path)
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if (newest_binary is None) or (binary_mtime > newest_mtime):
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newest_binary = binary_path
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newest_mtime = binary_mtime
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perftests_path = newest_binary
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if perftests_path == None or not os.path.exists(perftests_path):
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print('Cannot find Release %s!' % args.test_suite)
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return EXIT_FAILURE
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print('Using test executable: %s' % perftests_path)
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print('Test name: %s' % args.test_name)
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def get_results(metric, extra_args=[]):
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run = [perftests_path, '--gtest_filter=%s' % args.test_name] + extra_args
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logging.info('running %s' % str(run))
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process = subprocess.Popen(run, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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output, err = process.communicate()
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m = re.search(r'Running (\d+) tests', output)
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if m and int(m.group(1)) > 1:
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print(output)
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raise Exception('Found more than one test result in output')
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# Results are reported in the format:
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# name_backend.metric: story= value units.
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pattern = r'\.' + metric + r':.*= ([0-9.]+)'
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logging.debug('searching for %s in output' % pattern)
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m = re.findall(pattern, output)
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if not m:
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print(output)
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raise Exception('Did not find the metric "%s" in the test output' % metric)
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return [float(value) for value in m]
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# Calibrate the number of steps
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steps = get_results("steps_to_run", ["--calibration"] + extra_args)[0]
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print("running with %d steps." % steps)
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# Loop 'args.experiments' times, running the tests.
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for experiment in range(args.experiments):
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experiment_scores = get_results(args.metric,
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["--steps-per-trial", str(steps)] + extra_args)
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for score in experiment_scores:
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sys.stdout.write("%s: %.2f" % (args.metric, score))
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scores.append(score)
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if (len(scores) > 1):
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sys.stdout.write(", mean: %.2f" % mean(scores))
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sys.stdout.write(", variation: %.2f%%" %
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(coefficient_of_variation(scores) * 100.0))
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if (len(scores) > 7):
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truncation_n = len(scores) >> 3
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sys.stdout.write(", truncated mean: %.2f" % truncated_mean(scores, truncation_n))
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sys.stdout.write(", variation: %.2f%%" %
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(truncated_cov(scores, truncation_n) * 100.0))
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print("")
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return EXIT_SUCCESS
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if __name__ == "__main__":
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sys.exit(main(sys.argv[1:]))
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