mirror of
https://github.com/ARM-software/workload-automation.git
synced 2024-10-06 19:01:15 +01:00
e7fae25821
Added -p option to the list command. This alows filtering results by supported platforms, e.g. wa list workloads -p linux Also adding missing supported_platforms attribute to various extensions. If an extension does not have this attribute, the assumption is that it is supported by all available platforms.
314 lines
15 KiB
Python
314 lines
15 KiB
Python
# Copyright 2013-2015 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=W0613,E1101
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from __future__ import division
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import os
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import sys
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import time
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import csv
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import shutil
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import threading
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import errno
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import tempfile
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from distutils.version import LooseVersion
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from wlauto import Instrument, Parameter, IterationResult
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from wlauto.instrumentation import instrument_is_installed
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from wlauto.exceptions import (InstrumentError, WorkerThreadError, ConfigError,
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DeviceNotRespondingError, TimeoutError)
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from wlauto.utils.types import boolean, numeric
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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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VSYNC_INTERVAL = 16666667
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EPSYLON = 0.0001
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class FpsInstrument(Instrument):
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name = 'fps'
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description = """
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Measures Frames Per Second (FPS) and associated metrics for a workload's main View.
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.. note:: This instrument depends on pandas Python library (which is not part of standard
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WA dependencies), so you will need to install that first, before you can use it.
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The view is specified by the workload as ``view`` attribute. This defaults
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to ``'SurfaceView'`` for game workloads, and ``None`` for non-game
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workloads (as for them FPS mesurement usually doesn't make sense).
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Individual workloads may override this.
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This instrument adds four metrics to the results:
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:FPS: Frames Per Second. This is the frame rate of the workload.
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:frames: The total number of frames rendered during the execution of
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the workload.
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:janks: The number of "janks" that occured during execution of the
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workload. Janks are sudden shifts in frame rate. They result
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in a "stuttery" UI. See http://jankfree.org/jank-busters-io
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:not_at_vsync: The number of frames that did not render in a single
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vsync cycle.
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"""
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supported_platforms = ['android']
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parameters = [
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Parameter('drop_threshold', kind=numeric, default=5,
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description='Data points below this FPS will be dropped as they '
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'do not constitute "real" gameplay. The assumption '
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'being that while actually running, the FPS in the '
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'game will not drop below X frames per second, '
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'except on loading screens, menus, etc, which '
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'should not contribute to FPS calculation. '),
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Parameter('keep_raw', kind=boolean, default=False,
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description='If set to ``True``, this will keep the raw dumpsys output '
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'in the results directory (this is maily used for debugging) '
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'Note: frames.csv with collected frames data will always be '
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'generated regardless of this setting.'),
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Parameter('generate_csv', kind=boolean, default=True,
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description='If set to ``True``, this will produce temporal fps data '
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'in the results directory, in a file named fps.csv '
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'Note: fps data will appear as discrete step-like values '
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'in order to produce a more meainingfull representation,'
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'a rolling mean can be applied.'),
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Parameter('crash_check', kind=boolean, default=True,
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description="""
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Specifies wither the instrument should check for crashed content by examining
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frame data. If this is set, ``execution_time`` instrument must also be installed.
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The check is performed by using the measured FPS and exection time to estimate the expected
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frames cound and comparing that against the measured frames count. The the ratio of
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measured/expected is too low, then it is assumed that the content has crashed part way
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during the run. What is "too low" is determined by ``crash_threshold``.
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.. note:: This is not 100\% fool-proof. If the crash occurs sufficiently close to
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workload's termination, it may not be detected. If this is expected, the
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threshold may be adjusted up to compensate.
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"""),
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Parameter('crash_threshold', kind=float, default=0.7,
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description="""
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Specifies the threshold used to decided whether a measured/expected frames ration indicates
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a content crash. E.g. a value of ``0.75`` means the number of actual frames counted is a
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quarter lower than expected, it will treated as a content crash.
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"""),
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]
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clear_command = 'dumpsys SurfaceFlinger --latency-clear '
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def __init__(self, device, **kwargs):
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super(FpsInstrument, self).__init__(device, **kwargs)
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self.collector = None
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self.outfile = None
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self.fps_outfile = None
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self.is_enabled = True
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def validate(self):
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if not pd or LooseVersion(pd.__version__) < LooseVersion('0.13.1'):
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message = ('fps instrument requires pandas Python package (version 0.13.1 or higher) to be installed.\n'
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'You can install it with pip, e.g. "sudo pip install pandas"')
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raise InstrumentError(message)
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if self.crash_check and not instrument_is_installed('execution_time'):
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raise ConfigError('execution_time instrument must be installed in order to check for content crash.')
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def setup(self, context):
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workload = context.workload
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if hasattr(workload, 'view'):
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self.fps_outfile = os.path.join(context.output_directory, 'fps.csv')
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self.outfile = os.path.join(context.output_directory, 'frames.csv')
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self.collector = LatencyCollector(self.outfile, self.device, workload.view or '', self.keep_raw, self.logger)
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self.device.execute(self.clear_command)
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else:
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self.logger.debug('Workload does not contain a view; disabling...')
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self.is_enabled = False
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def start(self, context):
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if self.is_enabled:
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self.logger.debug('Starting SurfaceFlinger collection...')
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self.collector.start()
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def stop(self, context):
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if self.is_enabled and self.collector.is_alive():
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self.logger.debug('Stopping SurfaceFlinger collection...')
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self.collector.stop()
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def update_result(self, context):
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if self.is_enabled:
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data = pd.read_csv(self.outfile)
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if not data.empty: # pylint: disable=maybe-no-member
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per_frame_fps = self._update_stats(context, data)
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if self.generate_csv:
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per_frame_fps.to_csv(self.fps_outfile, index=False, header=True)
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context.add_artifact('fps', path='fps.csv', kind='data')
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else:
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context.result.add_metric('FPS', float('nan'))
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context.result.add_metric('frame_count', 0)
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context.result.add_metric('janks', 0)
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context.result.add_metric('not_at_vsync', 0)
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def slow_update_result(self, context):
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result = context.result
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if result.has_metric('execution_time'):
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self.logger.debug('Checking for crashed content.')
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exec_time = result['execution_time'].value
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fps = result['FPS'].value
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frames = result['frame_count'].value
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if all([exec_time, fps, frames]):
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expected_frames = fps * exec_time
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ratio = frames / expected_frames
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self.logger.debug('actual/expected frames: {:.2}'.format(ratio))
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if ratio < self.crash_threshold:
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self.logger.error('Content for {} appears to have crashed.'.format(context.spec.label))
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result.status = IterationResult.FAILED
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result.add_event('Content crash detected (actual/expected frames: {:.2}).'.format(ratio))
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def _update_stats(self, context, data):
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vsync_interval = self.collector.refresh_period
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actual_present_time_deltas = (data.actual_present_time - data.actual_present_time.shift()).drop(0) # pylint: disable=E1103
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vsyncs_to_compose = (actual_present_time_deltas / vsync_interval).apply(lambda x: int(round(x, 0)))
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# drop values lower than drop_threshold FPS as real in-game frame
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# rate is unlikely to drop below that (except on loading screens
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# etc, which should not be factored in frame rate calculation).
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per_frame_fps = (1.0 / (vsyncs_to_compose * (vsync_interval / 1e9)))
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keep_filter = per_frame_fps > self.drop_threshold
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filtered_vsyncs_to_compose = vsyncs_to_compose[keep_filter]
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if not filtered_vsyncs_to_compose.empty:
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total_vsyncs = filtered_vsyncs_to_compose.sum()
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if total_vsyncs:
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frame_count = filtered_vsyncs_to_compose.size
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fps = 1e9 * frame_count / (vsync_interval * total_vsyncs)
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context.result.add_metric('FPS', fps)
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context.result.add_metric('frame_count', frame_count)
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else:
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context.result.add_metric('FPS', float('nan'))
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context.result.add_metric('frame_count', 0)
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vtc_deltas = filtered_vsyncs_to_compose - filtered_vsyncs_to_compose.shift()
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vtc_deltas.index = range(0, vtc_deltas.size)
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vtc_deltas = vtc_deltas.drop(0).abs()
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janks = vtc_deltas.apply(lambda x: (x > EPSYLON) and 1 or 0).sum()
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not_at_vsync = vsyncs_to_compose.apply(lambda x: (abs(x - 1.0) > EPSYLON) and 1 or 0).sum()
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context.result.add_metric('janks', janks)
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context.result.add_metric('not_at_vsync', not_at_vsync)
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else: # no filtered_vsyncs_to_compose
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context.result.add_metric('FPS', float('nan'))
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context.result.add_metric('frame_count', 0)
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context.result.add_metric('janks', 0)
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context.result.add_metric('not_at_vsync', 0)
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per_frame_fps.name = 'fps'
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return per_frame_fps
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class LatencyCollector(threading.Thread):
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# Note: the size of the frames buffer for a particular surface is defined
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# by NUM_FRAME_RECORDS inside android/services/surfaceflinger/FrameTracker.h.
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# At the time of writing, this was hard-coded to 128. So at 60 fps
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# (and there is no reason to go above that, as it matches vsync rate
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# on pretty much all phones), there is just over 2 seconds' worth of
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# frames in there. Hence the sleep time of 2 seconds between dumps.
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#command_template = 'while (true); do dumpsys SurfaceFlinger --latency {}; sleep 2; done'
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command_template = 'dumpsys SurfaceFlinger --latency {}'
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def __init__(self, outfile, device, activity, keep_raw, logger):
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super(LatencyCollector, self).__init__()
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self.outfile = outfile
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self.device = device
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self.command = self.command_template.format(activity)
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self.keep_raw = keep_raw
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self.logger = logger
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self.stop_signal = threading.Event()
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self.frames = []
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self.last_ready_time = 0
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self.refresh_period = VSYNC_INTERVAL
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self.drop_threshold = self.refresh_period * 1000
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self.exc = None
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self.unresponsive_count = 0
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def run(self):
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try:
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self.logger.debug('SurfaceFlinger collection started.')
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self.stop_signal.clear()
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fd, temp_file = tempfile.mkstemp()
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self.logger.debug('temp file: {}'.format(temp_file))
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wfh = os.fdopen(fd, 'wb')
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try:
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while not self.stop_signal.is_set():
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wfh.write(self.device.execute(self.command))
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time.sleep(2)
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finally:
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wfh.close()
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# TODO: this can happen after the run during results processing
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with open(temp_file) as fh:
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text = fh.read().replace('\r\n', '\n').replace('\r', '\n')
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for line in text.split('\n'):
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line = line.strip()
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if line:
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self._process_trace_line(line)
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if self.keep_raw:
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raw_file = os.path.join(os.path.dirname(self.outfile), 'surfaceflinger.raw')
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shutil.copy(temp_file, raw_file)
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os.unlink(temp_file)
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except (DeviceNotRespondingError, TimeoutError): # pylint: disable=W0703
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raise
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except Exception, e: # pylint: disable=W0703
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self.logger.warning('Exception on collector thread: {}({})'.format(e.__class__.__name__, e))
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self.exc = WorkerThreadError(self.name, sys.exc_info())
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self.logger.debug('SurfaceFlinger collection stopped.')
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with open(self.outfile, 'w') as wfh:
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writer = csv.writer(wfh)
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writer.writerow(['desired_present_time', 'actual_present_time', 'frame_ready_time'])
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writer.writerows(self.frames)
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self.logger.debug('Frames data written.')
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def stop(self):
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self.stop_signal.set()
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self.join()
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if self.unresponsive_count:
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message = 'SurfaceFlinger was unrepsonsive {} times.'.format(self.unresponsive_count)
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if self.unresponsive_count > 10:
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self.logger.warning(message)
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else:
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self.logger.debug(message)
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if self.exc:
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raise self.exc # pylint: disable=E0702
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self.logger.debug('FSP collection complete.')
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def _process_trace_line(self, line):
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parts = line.split()
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if len(parts) == 3:
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desired_present_time, actual_present_time, frame_ready_time = map(int, parts)
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if frame_ready_time <= self.last_ready_time:
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return # duplicate frame
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if (frame_ready_time - desired_present_time) > self.drop_threshold:
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self.logger.debug('Dropping bogus frame {}.'.format(line))
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return # bogus data
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self.last_ready_time = frame_ready_time
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self.frames.append((desired_present_time, actual_present_time, frame_ready_time))
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elif len(parts) == 1:
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self.refresh_period = int(parts[0])
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self.drop_threshold = self.refresh_period * 10
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elif 'SurfaceFlinger appears to be unresponsive, dumping anyways' in line:
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self.unresponsive_count += 1
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else:
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self.logger.warning('Unexpected SurfaceFlinger dump output: {}'.format(line))
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