mirror of
https://github.com/ARM-software/workload-automation.git
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8edce40301
Fixed: if index isnt zero based, drop(0) will fail
175 lines
7.5 KiB
Python
Executable File
175 lines
7.5 KiB
Python
Executable File
# Copyright 2016 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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import collections
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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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SurfaceFlingerFrame = collections.namedtuple('SurfaceFlingerFrame', 'desired_present_time actual_present_time frame_ready_time')
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GfxInfoFrame = collections.namedtuple('GfxInfoFrame', 'Flags IntendedVsync Vsync OldestInputEvent NewestInputEvent HandleInputStart AnimationStart PerformTraversalsStart DrawStart SyncQueued SyncStart IssueDrawCommandsStart SwapBuffers FrameCompleted')
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# https://android.googlesource.com/platform/frameworks/base/+/marshmallow-release/libs/hwui/JankTracker.cpp
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# Frames that are exempt from jank metrics.
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# First-draw frames, for example, are expected to be slow,
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# this is hidden from the user with window animations and other tricks
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# Similarly, we don't track direct-drawing via Surface:lockHardwareCanvas() for now
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# Android M: WindowLayoutChanged | SurfaceCanvas
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GFXINFO_EXEMPT = 1 | 4
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class FpsProcessor(object):
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"""
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Provides common object for processing surfaceFlinger output for frame
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statistics.
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This processor returns the four frame statistics below:
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:FPS: Frames Per Second. This is the frame rate of the workload.
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:frame_count: 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 occurred 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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def __init__(self, data, action=None, extra_data=None):
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"""
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data - a pandas.DataFrame object with frame data (e.g. frames.csv)
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action - output metrics names with additional action specifier
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extra_data - extra data given to use for calculations of metrics
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"""
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self.data = data
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self.action = action
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self.extra_data = extra_data
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def process(self, refresh_period, drop_threshold): # pylint: disable=too-many-locals
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"""
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Generate frame per second (fps) and associated metrics for workload.
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refresh_period - the vsync interval
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drop_threshold - data points below this fps will be dropped
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"""
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fps = float('nan')
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frame_count, janks, not_at_vsync = 0, 0, 0
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vsync_interval = refresh_period
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per_frame_fps = pd.Series()
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# SurfaceFlinger Algorithm
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if self.data.columns.tolist() == list(SurfaceFlingerFrame._fields):
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# fiter out bogus frames.
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bogus_frames_filter = self.data.actual_present_time != 0x7fffffffffffffff
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actual_present_times = self.data.actual_present_time[bogus_frames_filter]
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actual_present_time_deltas = actual_present_times.diff().dropna()
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vsyncs_to_compose = actual_present_time_deltas.div(vsync_interval)
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vsyncs_to_compose.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.multiply(vsync_interval / 1e9)))
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keep_filter = per_frame_fps > drop_threshold
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filtered_vsyncs_to_compose = vsyncs_to_compose[keep_filter]
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per_frame_fps.name = 'fps'
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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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frame_count = filtered_vsyncs_to_compose.size
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if total_vsyncs:
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fps = 1e9 * frame_count / (vsync_interval * total_vsyncs)
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janks = self._calc_janks(filtered_vsyncs_to_compose)
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not_at_vsync = self._calc_not_at_vsync(vsyncs_to_compose)
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# GfxInfo Algorithm
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elif self.data.columns.tolist() == list(GfxInfoFrame._fields):
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frame_time = self.data.FrameCompleted - self.data.IntendedVsync
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per_frame_fps = (1e9 / frame_time)
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keep_filter = per_frame_fps > drop_threshold
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per_frame_fps = per_frame_fps[keep_filter]
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per_frame_fps.name = 'fps'
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frame_count = self.data.index.size
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if frame_count:
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janks = frame_time[frame_time >= vsync_interval].count()
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not_at_vsync = self.data.IntendedVsync - self.data.Vsync
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not_at_vsync = not_at_vsync[not_at_vsync != 0].count()
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duration = self.data.Vsync.iloc[-1] - self.data.Vsync.iloc[0]
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fps = (1e9 * frame_count) / float(duration)
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# If gfxinfocsv is provided, get stats from that instead
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if self.extra_data:
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series = pd.read_csv(self.extra_data, header=None, index_col=0, squeeze=True)
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if not series.empty: # pylint: disable=maybe-no-member
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frame_count = series['Total frames rendered']
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janks = series['Janky frames']
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not_at_vsync = series['Number Missed Vsync']
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metrics = (fps, frame_count, janks, not_at_vsync)
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return per_frame_fps, metrics
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def percentiles(self):
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# SurfaceFlinger Algorithm
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if self.data.columns.tolist() == list(SurfaceFlingerFrame._fields):
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frame_time = self.data.frame_ready_time.diff()
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# GfxInfo Algorithm
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elif self.data.columns.tolist() == list(GfxInfoFrame._fields):
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frame_time = self.data.FrameCompleted - self.data.IntendedVsync
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data = frame_time.dropna().quantile([0.90, 0.95, 0.99])
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# Convert to ms, round to nearest, cast to int
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data = data.div(1e6).round()
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try:
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data = data.astype('int')
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except ValueError:
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pass
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# If gfxinfocsv is provided, get stats from that instead
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if self.extra_data:
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series = pd.read_csv(self.extra_data, header=None, index_col=0, squeeze=True)
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if not series.empty: # pylint: disable=maybe-no-member
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data = series[series.index.str.contains('th percentile')] # pylint: disable=maybe-no-member
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return list(data.get_values())
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@staticmethod
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def _calc_janks(filtered_vsyncs_to_compose):
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"""
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Internal method for calculating jank frames.
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"""
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pause_latency = 20
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vtc_deltas = filtered_vsyncs_to_compose.diff().dropna()
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vtc_deltas = vtc_deltas.abs()
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janks = vtc_deltas.apply(lambda x: (pause_latency > x > 1.5) and 1 or 0).sum()
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return janks
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@staticmethod
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def _calc_not_at_vsync(vsyncs_to_compose):
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"""
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Internal method for calculating the number of frames that did not
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render in a single vsync cycle.
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"""
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epsilon = 0.0001
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func = lambda x: (abs(x - 1.0) > epsilon) and 1 or 0
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not_at_vsync = vsyncs_to_compose.apply(func).sum()
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return not_at_vsync
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