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Unified Diff: tools/perf/metrics/gpu_timeline_unittest.py

Issue 854833003: Added GPU performance metrics. (Closed) Base URL: https://chromium.googlesource.com/chromium/src.git@master
Patch Set: Replaced gpu_times pagetest with standard timeline_based_measurement Created 5 years, 11 months ago
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« tools/perf/benchmarks/gpu_times.py ('K') | « tools/perf/metrics/gpu_timeline.py ('k') | tools/telemetry/telemetry/web_perf/timeline_based_measurement.py » ('j') | tools/telemetry/telemetry/web_perf/timeline_based_measurement.py » ('J')
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Index: tools/perf/metrics/gpu_timeline_unittest.py
diff --git a/tools/perf/metrics/gpu_timeline_unittest.py b/tools/perf/metrics/gpu_timeline_unittest.py
new file mode 100644
index 0000000000000000000000000000000000000000..1fc78bb7225b9433eb0fa84baf59b35393eaeda2
--- /dev/null
+++ b/tools/perf/metrics/gpu_timeline_unittest.py
@@ -0,0 +1,311 @@
+# Copyright 2015 The Chromium Authors. All rights reserved.
+# Use of this source code is governed by a BSD-style license that can be
+# found in the LICENSE file.
+
+import unittest
+
+from metrics import test_page_test_results
+from metrics import gpu_timeline
+from telemetry.timeline import async_slice as async_slice_module
+from telemetry.timeline import slice as slice_module
+from telemetry.timeline import model as model_module
+from telemetry.web_perf import timeline_interaction_record as tir_module
+
+SERVICE_FRAME_END_CATEGORY, SERVICE_FRAME_END_NAME = \
+ gpu_timeline.SERVICE_FRAME_END_MARKER
+
+DEVICE_FRAME_END_CATEGORY, DEVICE_FRAME_END_NAME = \
+ gpu_timeline.DEVICE_FRAME_END_MARKER
+
+INTERACTION_RECORDS = [tir_module.TimelineInteractionRecord("test-record",
+ 0,
+ float('inf'))]
+
+
+def _CreateGPUSlices(parent_thread, name, start_time, duration, offset=0):
+ args = { 'gl_category': gpu_timeline.TOPLEVEL_GL_CATEGORY }
+ return (slice_module.Slice(parent_thread,
+ gpu_timeline.TOPLEVEL_SERVICE_CATEGORY,
+ name, start_time,
+ args=args,
+ duration=duration,
+ thread_duration=duration),
+ async_slice_module.AsyncSlice(gpu_timeline.TOPLEVEL_DEVICE_CATEGORY,
+ name, start_time + offset,
+ args=args,
+ duration=duration))
+
+def _CreateFrameEndSlices(parent_thread, start_time, duration, offset=0):
+ args = { 'gl_category': gpu_timeline.TOPLEVEL_GL_CATEGORY }
+ return (slice_module.Slice(parent_thread,
+ SERVICE_FRAME_END_CATEGORY,
+ SERVICE_FRAME_END_NAME,
+ start_time,
+ args=args,
+ duration=duration,
+ thread_duration=duration),
+ async_slice_module.AsyncSlice(DEVICE_FRAME_END_CATEGORY,
+ DEVICE_FRAME_END_NAME,
+ start_time + offset,
+ args=args,
+ duration=duration))
+
+
+def _AddSliceToThread(parent_thread, slice_item):
+ if isinstance(slice_item, slice_module.Slice):
+ parent_thread.PushSlice(slice_item)
+ elif isinstance(slice_item, async_slice_module.AsyncSlice):
+ parent_thread.AddAsyncSlice(slice_item)
+ else:
+ assert False, "Invalid Slice Item Type: %s" % type(slice_item)
+
+
+class GPUTimelineTest(unittest.TestCase):
+ def GetResults(self, metric, model, renderer_thread, interaction_records):
+ results = test_page_test_results.TestPageTestResults(self)
+ metric.AddResults(model, renderer_thread, interaction_records, results)
+ return results
+
+ def testExpectedResults(self):
+ """Test a simply trace will output all expected results."""
+ model = model_module.TimelineModel()
+ test_thread = model.GetOrCreateProcess(1).GetOrCreateThread(2)
+ for slice_item in _CreateGPUSlices(test_thread, 'test_item', 100, 10):
+ _AddSliceToThread(test_thread, slice_item)
+ model.FinalizeImport()
+
+ metric = gpu_timeline.GPUTimelineMetric()
+ results = self.GetResults(metric, model=model, renderer_thread=test_thread,
+ interaction_records=INTERACTION_RECORDS)
+
+ for source_type in (None, 'cpu', 'gpu'):
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'max'), 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'mean'), 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'stddev'), 'ms', 0)
+
+ for tracked_name in gpu_timeline.TRACKED_NAMES.values():
+ for source_type in ('cpu', 'gpu'):
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(tracked_name, source_type, 'max'),
+ 'ms', 0)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(tracked_name, source_type, 'mean'),
+ 'ms', 0)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(tracked_name, source_type, 'stddev'),
+ 'ms', 0)
+
+ def testNoDeviceTraceResults(self):
+ """Test expected results when missing device traces."""
+ model = model_module.TimelineModel()
+ test_thread = model.GetOrCreateProcess(1).GetOrCreateThread(2)
+ service_slice, _ = _CreateGPUSlices(test_thread, 'test_item', 100, 10)
+ _AddSliceToThread(test_thread, service_slice)
+ model.FinalizeImport()
+
+ metric = gpu_timeline.GPUTimelineMetric()
+ results = self.GetResults(metric, model=model, renderer_thread=test_thread,
+ interaction_records=INTERACTION_RECORDS)
+
+ for source_type in (None, 'cpu'):
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'max'), 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'mean'), 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'stddev'), 'ms', 0)
+
+ self.assertRaises(AssertionError, results.GetPageSpecificValueNamed,
+ gpu_timeline.TimelineName('total', 'gpu', 'max'))
+ self.assertRaises(AssertionError, results.GetPageSpecificValueNamed,
+ gpu_timeline.TimelineName('total', 'gpu', 'mean'))
+ self.assertRaises(AssertionError, results.GetPageSpecificValueNamed,
+ gpu_timeline.TimelineName('total', 'gpu', 'stddev'))
+
+ for name in gpu_timeline.TRACKED_NAMES.values():
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(name, 'cpu', 'max'), 'ms', 0)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(name, 'cpu', 'mean'), 'ms', 0)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(name, 'cpu', 'stddev'), 'ms', 0)
+
+ self.assertRaises(AssertionError, results.GetPageSpecificValueNamed,
+ gpu_timeline.TimelineName(name, 'gpu', 'max'))
+ self.assertRaises(AssertionError, results.GetPageSpecificValueNamed,
+ gpu_timeline.TimelineName(name, 'gpu', 'mean'))
+ self.assertRaises(AssertionError, results.GetPageSpecificValueNamed,
+ gpu_timeline.TimelineName(name, 'gpu', 'stddev'))
+
+ def testFrameSeparation(self):
+ """Test frames are correctly calculated using the frame end marker."""
+ model = model_module.TimelineModel()
+ test_thread = model.GetOrCreateProcess(1).GetOrCreateThread(2)
+
+ # First frame is 10 seconds.
+ for slice_item in _CreateGPUSlices(test_thread, 'test_item', 100, 10):
+ _AddSliceToThread(test_thread, slice_item)
+
+ # Mark frame end.
+ for slice_item in _CreateFrameEndSlices(test_thread, 105, 5):
+ _AddSliceToThread(test_thread, slice_item)
+
+ # Second frame is 20 seconds.
+ for slice_item in _CreateGPUSlices(test_thread, 'test_item', 110, 20):
+ _AddSliceToThread(test_thread, slice_item)
+
+ model.FinalizeImport()
+
+ metric = gpu_timeline.GPUTimelineMetric()
+ results = self.GetResults(metric, model=model, renderer_thread=test_thread,
+ interaction_records=INTERACTION_RECORDS)
+
+ for source_type in (None, 'cpu', 'gpu'):
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'max'), 'ms', 20)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'mean'), 'ms', 15)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'stddev'), 'ms', 5)
+
+ def testFrameSeparationBeforeMarker(self):
+ """Test frames are correctly calculated using the frame end marker."""
+ model = model_module.TimelineModel()
+ test_thread = model.GetOrCreateProcess(1).GetOrCreateThread(2)
+
+ # Mark frame end.
+ for slice_item in _CreateFrameEndSlices(test_thread, 105, 5):
+ _AddSliceToThread(test_thread, slice_item)
+
+ # First frame is 10 seconds.
+ for slice_item in _CreateGPUSlices(test_thread, 'test_item', 100, 10):
+ _AddSliceToThread(test_thread, slice_item)
+
+ # Second frame is 20 seconds.
+ for slice_item in _CreateGPUSlices(test_thread, 'test_item', 110, 20):
+ _AddSliceToThread(test_thread, slice_item)
+
+ model.FinalizeImport()
+
+ metric = gpu_timeline.GPUTimelineMetric()
+ results = self.GetResults(metric, model=model, renderer_thread=test_thread,
+ interaction_records=INTERACTION_RECORDS)
+
+ for source_type in (None, 'cpu', 'gpu'):
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'max'), 'ms', 20)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'mean'), 'ms', 15)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName('total', source_type, 'stddev'), 'ms', 5)
+
+ def testTrackedNameTraces(self):
+ """Be sure tracked names are being recorded correctly."""
+ self.assertGreater(len(gpu_timeline.TRACKED_NAMES), 0)
+
+ marker_name, result_name = gpu_timeline.TRACKED_NAMES.iteritems().next()
+
+ model = model_module.TimelineModel()
+ test_thread = model.GetOrCreateProcess(1).GetOrCreateThread(2)
+ for slice_item in _CreateGPUSlices(test_thread, marker_name, 100, 10):
+ _AddSliceToThread(test_thread, slice_item)
+ model.FinalizeImport()
+
+ metric = gpu_timeline.GPUTimelineMetric()
+ results = self.GetResults(metric, model=model, renderer_thread=test_thread,
+ interaction_records=INTERACTION_RECORDS)
+
+ for source_type in ('cpu', 'gpu'):
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result_name, source_type, 'max'),
+ 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result_name, source_type, 'mean'),
+ 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result_name, source_type, 'stddev'),
+ 'ms', 0)
+
+ def testTrackedNameWithContextIDTraces(self):
+ """Be sure tracked names with context IDs are recorded correctly."""
+ self.assertGreater(len(gpu_timeline.TRACKED_NAMES), 0)
+
+ marker_name, result_name = gpu_timeline.TRACKED_NAMES.iteritems().next()
+ context_id = '-0x1234'
+
+ model = model_module.TimelineModel()
+ test_thread = model.GetOrCreateProcess(1).GetOrCreateThread(2)
+ for slice_item in _CreateGPUSlices(test_thread, marker_name + context_id,
+ 100, 10):
+ _AddSliceToThread(test_thread, slice_item)
+ model.FinalizeImport()
+
+ metric = gpu_timeline.GPUTimelineMetric()
+ results = self.GetResults(metric, model=model, renderer_thread=test_thread,
+ interaction_records=INTERACTION_RECORDS)
+
+ for source_type in ('cpu', 'gpu'):
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result_name, source_type, 'max'),
+ 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result_name, source_type, 'mean'),
+ 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result_name, source_type, 'stddev'),
+ 'ms', 0)
+
+ def testOutOfOrderDeviceTraces(self):
+ """Out of order device traces are still matched up to correct services."""
+ self.assertGreaterEqual(len(gpu_timeline.TRACKED_NAMES), 2)
+
+ tracked_names_iter = gpu_timeline.TRACKED_NAMES.iteritems()
+ marker1_name, result1_name = tracked_names_iter.next()
+ result2_name = result1_name
+ while result2_name == result1_name:
+ marker2_name, result2_name = tracked_names_iter.next()
+
+ model = model_module.TimelineModel()
+ test_thread = model.GetOrCreateProcess(1).GetOrCreateThread(2)
+
+ # marker1 lasts for 10 seconds.
+ service_item1, device_item1 = _CreateGPUSlices(test_thread, marker1_name,
+ 100, 10)
+ # marker2 lasts for 20 seconds.
+ service_item2, device_item2 = _CreateGPUSlices(test_thread, marker2_name,
+ 200, 20)
+
+ # Append out of order
+ _AddSliceToThread(test_thread, service_item1)
+ _AddSliceToThread(test_thread, service_item2)
+ _AddSliceToThread(test_thread, device_item2)
+ _AddSliceToThread(test_thread, device_item1)
+
+ model.FinalizeImport()
+
+ metric = gpu_timeline.GPUTimelineMetric()
+ results = self.GetResults(metric, model=model, renderer_thread=test_thread,
+ interaction_records=INTERACTION_RECORDS)
+
+ for source_type in ('cpu', 'gpu'):
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result1_name, source_type, 'max'),
+ 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result1_name, source_type, 'mean'),
+ 'ms', 10)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result1_name, source_type, 'stddev'),
+ 'ms', 0)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result2_name, source_type, 'max'),
+ 'ms', 20)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result2_name, source_type, 'mean'),
+ 'ms', 20)
+ results.AssertHasPageSpecificScalarValue(
+ gpu_timeline.TimelineName(result2_name, source_type, 'stddev'),
+ 'ms', 0)
« tools/perf/benchmarks/gpu_times.py ('K') | « tools/perf/metrics/gpu_timeline.py ('k') | tools/telemetry/telemetry/web_perf/timeline_based_measurement.py » ('j') | tools/telemetry/telemetry/web_perf/timeline_based_measurement.py » ('J')

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