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114 lines
3.4 KiB
114 lines
3.4 KiB
# Copyright 2017 The Chromium OS 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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"""Helper functions to parse result collected from device""" |
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from __future__ import print_function |
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from fix_skia_results import _TransformBenchmarks |
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import json |
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def normalize(bench, dict_list): |
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bench_base = { |
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'Panorama': 1, |
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'Dex2oat': 1, |
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'Hwui': 10000, |
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'Skia': 1, |
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'Synthmark': 1, |
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'Binder': 0.001 |
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} |
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result_dict = dict_list[0] |
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for key in result_dict: |
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result_dict[key] = result_dict[key] / bench_base[bench] |
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return [result_dict] |
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# Functions to parse benchmark result for data collection. |
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def parse_Panorama(bench, fin): |
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result_dict = {} |
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for line in fin: |
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words = line.split() |
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if 'elapsed' in words: |
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#TODO: Need to restructure the embedded word counts. |
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result_dict['total_time_s'] = float(words[3]) |
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result_dict['retval'] = 0 |
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return normalize(bench, [result_dict]) |
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raise ValueError('You passed the right type of thing, ' |
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'but it didn\'t have the expected contents.') |
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def parse_Synthmark(bench, fin): |
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result_dict = {} |
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accum = 0 |
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cnt = 0 |
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for line in fin: |
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words = line.split() |
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if 'normalized' in words: |
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#TODO: Need to restructure the embedded word counts. |
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accum += float(words[-1]) |
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cnt += 1 |
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if accum != 0: |
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result_dict['total_voices'] = accum / cnt |
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result_dict['retval'] = 0 |
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return normalize(bench, [result_dict]) |
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raise ValueError('You passed the right type of thing, ' |
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'but it didn\'t have the expected contents.') |
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def parse_Binder(bench, fin): |
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result_dict = {} |
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accum = 0 |
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cnt = 0 |
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for line in fin: |
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words = line.split() |
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for word in words: |
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if 'average' in word: |
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#TODO: Need to restructure the embedded word counts. |
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accum += float(word[8:-2]) |
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cnt += 1 |
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if accum != 0: |
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result_dict['avg_time_ms'] = accum / cnt |
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result_dict['retval'] = 0 |
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return normalize(bench, [result_dict]) |
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raise ValueError('You passed the right type of thing, ' |
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'but it didn\'t have the expected contents.') |
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def parse_Dex2oat(bench, fin): |
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result_dict = {} |
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cnt = 0 |
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for line in fin: |
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words = line.split() |
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if 'elapsed' in words: |
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cnt += 1 |
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#TODO: Need to restructure the embedded word counts. |
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if cnt == 1: |
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# First 'elapsed' time is for microbench 'Chrome' |
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result_dict['chrome_s'] = float(words[3]) |
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elif cnt == 2: |
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# Second 'elapsed' time is for microbench 'Camera' |
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result_dict['camera_s'] = float(words[3]) |
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result_dict['retval'] = 0 |
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# Two results found, return |
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return normalize(bench, [result_dict]) |
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raise ValueError('You passed the right type of thing, ' |
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'but it didn\'t have the expected contents.') |
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def parse_Hwui(bench, fin): |
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result_dict = {} |
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for line in fin: |
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words = line.split() |
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if 'elapsed' in words: |
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#TODO: Need to restructure the embedded word counts. |
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result_dict['total_time_s'] = float(words[3]) |
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result_dict['retval'] = 0 |
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return normalize(bench, [result_dict]) |
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raise ValueError('You passed the right type of thing, ' |
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'but it didn\'t have the expected contents.') |
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def parse_Skia(bench, fin): |
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obj = json.load(fin) |
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return normalize(bench, _TransformBenchmarks(obj))
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