mirror of
https://github.com/ARM-software/workload-automation.git
synced 2024-10-07 03:11:53 +01:00
295 lines
12 KiB
Python
295 lines
12 KiB
Python
# Copyright 2015 ARM Limited
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# pylint: disable=attribute-defined-outside-init
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import os
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import re
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import csv
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import math
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import shutil
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import json
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import urllib
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import stat
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from zipfile import is_zipfile, ZipFile
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from collections import defaultdict
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try:
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import pandas as pd
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except ImportError:
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pd = None
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from wlauto import Workload, Parameter
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from wlauto.exceptions import WorkloadError, ConfigError
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from wlauto.utils.misc import check_output, get_null, get_meansd
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from wlauto.utils.types import numeric, identifier
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RESULT_REGEX = re.compile(r'RESULT ([^:]+): ([^=]+)\s*=\s*' # preamble and test/metric name
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r'(\[([^\]]+)\]|(\S+))' # value
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r'\s*(\S+)') # units
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TRACE_REGEX = re.compile(r'Trace saved as ([^\n]+)')
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# Trace event that signifies rendition of a Frame
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FRAME_EVENT = 'SwapBuffersLatency'
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TELEMETRY_ARCHIVE_URL = 'http://storage.googleapis.com/chromium-telemetry/snapshots/telemetry.zip'
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class Telemetry(Workload):
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name = 'telemetry'
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description = """
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Executes Google's Telemetery benchmarking framework (must be installed).
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Url: https://www.chromium.org/developers/telemetry
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From the web site:
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Telemetry is Chrome's performance testing framework. It allows you to
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perform arbitrary actions on a set of web pages and report metrics about
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it. The framework abstracts:
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- Launching a browser with arbitrary flags on any platform.
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- Opening a tab and navigating to the page under test.
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- Fetching data via the Inspector timeline and traces.
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- Using Web Page Replay to cache real-world websites so they don't
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change when used in benchmarks.
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Design Principles
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- Write one performance test that runs on all platforms - Windows, Mac,
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Linux, Chrome OS, and Android for both Chrome and ContentShell.
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- Runs on browser binaries, without a full Chromium checkout, and without
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having to build the browser yourself.
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- Use WebPageReplay to get repeatable test results.
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- Clean architecture for writing benchmarks that keeps measurements and
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use cases separate.
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- Run on non-Chrome browsers for comparative studies.
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This instrument runs telemetry via its ``run_benchmark`` script (which
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must be in PATH or specified using ``run_benchmark_path`` parameter) and
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parses metrics from the resulting output.
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**device setup**
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The device setup will depend on whether you're running a test image (in
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which case little or no setup should be necessary)
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"""
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parameters = [
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Parameter('run_benchmark_path', default=None,
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description="""
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This is the path to run_benchmark script which runs a
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Telemetry benchmark. If not specified, the assumption will be
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that it is in path (i.e. with be invoked as ``run_benchmark``).
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"""),
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Parameter('test', default='page_cycler.top_10_mobile',
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description="""
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Specifies the telemetry test to run.
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"""),
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Parameter('run_benchmark_params', default='',
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description="""
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Additional paramters to be passed to ``run_benchmark``.
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"""),
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Parameter('run_timeout', kind=int, default=900,
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description="""
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Timeout for execution of the test.
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"""),
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Parameter('extract_fps', kind=bool, default=False,
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description="""
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if ``True``, FPS for the run will be computed from the trace (must be enabled).
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"""),
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]
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def validate(self):
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ret = os.system('{} > {} 2>&1'.format(self.run_benchmark_path, get_null()))
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if ret > 255:
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pass # telemetry found and appears to be installed properly.
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elif ret == 127:
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raise WorkloadError('run_benchmark not found (did you specify correct run_benchmark_path?)')
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else:
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raise WorkloadError('Unexected error from run_benchmark: {}'.format(ret))
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if self.extract_fps and 'trace' not in self.run_benchmark_params:
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raise ConfigError('"trace" profiler must be enabled in order to extract FPS for Telemetry')
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self._resolve_run_benchmark_path()
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def setup(self, context):
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self.raw_output = None
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self.command = self.build_command()
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def run(self, context):
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self.logger.debug(self.command)
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self.raw_output, _ = check_output(self.command, shell=True, timeout=self.run_timeout, ignore='all')
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def update_result(self, context): # pylint: disable=too-many-locals
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if not self.raw_output:
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self.logger.warning('Did not get run_benchmark output.')
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return
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raw_outfile = os.path.join(context.output_directory, 'telemetry_raw.out')
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with open(raw_outfile, 'w') as wfh:
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wfh.write(self.raw_output)
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context.add_artifact('telemetry-raw', raw_outfile, kind='raw')
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results, artifacts = parse_telemetry_results(raw_outfile)
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csv_outfile = os.path.join(context.output_directory, 'telemetry.csv')
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with open(csv_outfile, 'wb') as wfh:
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writer = csv.writer(wfh)
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writer.writerow(['kind', 'url', 'iteration', 'value', 'units'])
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for result in results:
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writer.writerows(result.rows)
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for i, value in enumerate(result.values, 1):
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context.add_metric(result.kind, value, units=result.units,
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classifiers={'url': result.url, 'time': i})
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context.add_artifact('telemetry', csv_outfile, kind='data')
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for idx, artifact in enumerate(artifacts):
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if is_zipfile(artifact):
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zf = ZipFile(artifact)
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for item in zf.infolist():
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zf.extract(item, context.output_directory)
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zf.close()
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context.add_artifact('telemetry_trace_{}'.format(idx), path=item.filename, kind='data')
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else: # not a zip archive
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wa_path = os.path.join(context.output_directory,
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os.path.basename(artifact))
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shutil.copy(artifact, wa_path)
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context.add_artifact('telemetry_artifact_{}'.format(idx), path=wa_path, kind='data')
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if self.extract_fps:
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self.logger.debug('Extracting FPS...')
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_extract_fps(context)
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def build_command(self):
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device_opts = ''
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if self.device.platform == 'chromeos':
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if '--remote' not in self.run_benchmark_params:
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device_opts += '--remote={} '.format(self.device.host)
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if '--browser' not in self.run_benchmark_params:
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device_opts += '--browser=cros-chrome '
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elif self.device.platform == 'android':
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if '--device' not in self.run_benchmark_params and self.device.adb_name:
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device_opts += '--device={} '.format(self.device.adb_name)
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if '--browser' not in self.run_benchmark_params:
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device_opts += '--browser=android-webview-shell '
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else:
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raise WorkloadError('Currently, telemetry workload supports only ChromeOS or Android devices.')
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return '{} {} {} {}'.format(self.run_benchmark_path,
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self.test,
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device_opts,
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self.run_benchmark_params)
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def _resolve_run_benchmark_path(self):
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# pylint: disable=access-member-before-definition
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if self.run_benchmark_path:
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if not os.path.exists(self.run_benchmark_path):
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raise ConfigError('run_benchmark path "{}" does not exist'.format(self.run_benchmark_path))
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else:
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self.run_benchmark_path = os.path.join(self.dependencies_directory, 'telemetry', 'run_benchmark')
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self.logger.debug('run_benchmark_path not specified using {}'.format(self.run_benchmark_path))
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if not os.path.exists(self.run_benchmark_path):
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self.logger.debug('Telemetry not found locally; downloading...')
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local_archive = os.path.join(self.dependencies_directory, 'telemetry.zip')
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urllib.urlretrieve(TELEMETRY_ARCHIVE_URL, local_archive)
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zf = ZipFile(local_archive)
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zf.extractall(self.dependencies_directory)
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if not os.path.exists(self.run_benchmark_path):
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raise WorkloadError('Could not download and extract Telemetry')
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old_mode = os.stat(self.run_benchmark_path).st_mode
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os.chmod(self.run_benchmark_path, old_mode | stat.S_IXUSR)
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def _extract_fps(context):
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trace_files = [a.path for a in context.iteration_artifacts
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if a.name.startswith('telemetry_trace_')]
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for tf in trace_files:
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name = os.path.splitext(os.path.basename(tf))[0]
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fps_file = os.path.join(context.output_directory, name + '-fps.csv')
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with open(tf) as fh:
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data = json.load(fh)
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events = pd.Series([e['ts'] for e in data['traceEvents'] if
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FRAME_EVENT == e['name']])
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fps = (1000000 / (events - events.shift(1)))
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fps.index = events
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df = fps.dropna().reset_index()
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df.columns = ['timestamp', 'fps']
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with open(fps_file, 'w') as wfh:
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df.to_csv(wfh, index=False)
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context.add_artifact('{}_fps'.format(name), fps_file, kind='data')
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context.result.add_metric('{} FPS'.format(name), df.fps.mean(),
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units='fps')
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context.result.add_metric('{} FPS (std)'.format(name), df.fps.std(),
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units='fps', lower_is_better=True)
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class TelemetryResult(object):
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@property
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def average(self):
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return get_meansd(self.values)[0]
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@property
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def std(self):
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return get_meansd(self.values)[1]
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@property
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def rows(self):
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for i, v in enumerate(self.values):
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yield [self.kind, self.url, i, v, self.units]
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def __init__(self, kind=None, url=None, values=None, units=None):
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self.kind = kind
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self.url = url
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self.values = values or []
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self.units = units
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def __str__(self):
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return 'TR({kind},{url},{values},{units})'.format(**self.__dict__)
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__repr__ = __str__
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def parse_telemetry_results(filepath):
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results = []
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artifacts = []
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with open(filepath) as fh:
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for line in fh:
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match = RESULT_REGEX.search(line)
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if match:
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result = TelemetryResult()
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result.kind = match.group(1)
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result.url = match.group(2)
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if match.group(4):
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result.values = map(numeric, match.group(4).split(','))
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else:
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result.values = [numeric(match.group(5))]
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result.units = match.group(6)
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results.append(result)
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match = TRACE_REGEX.search(line)
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if match:
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artifacts.append(match.group(1))
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return results, artifacts
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if __name__ == '__main__':
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import sys
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from pprint import pprint
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path = sys.argv[1]
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pprint(parse_telemetry_results(path))
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