Fix possible crash in scale-invariant error calculation
The logic for the scale-invariant calculation was quite complex
in the existing code, and depended on some tricky chains of logical
dependence between scale-invariant errors and general errors.
This change firstly eliminates unnecessary nesting by pulling the
scale-invariant error calculation out of the loop – the full calculation
only occurs once per computeAtomFields call, within its own loop.
Secondly, instead of crashing under certain conditions when the
scale-invariant error count is zero, this changes the code to simply not
compute the error in this case. (The complex chain of logic I had
followed to initially add the fatal crash turned out to be fallacious.)
Finally, this adds a testcase that fails without the changes to the
MetricsManager implementation (see ag/26418604). This added testcase
represents skipped/dropped input events, or an input interval greater
than the prediction interval.
Test: atest frameworks/native/libs/input/tests/MotionPredictorMetricsManager_test.cpp
Test: the above test fails without the changes to MotionPredictionMetricsManager.cpp
Test: `statsd_testdrive 718`, then draw with stylus → reported metrics are reasonable
Bug: 325711945
Change-Id: Ic56c0f0c810ec1b85b1906e16a8640824187d1fb
diff --git a/libs/input/MotionPredictorMetricsManager.cpp b/libs/input/MotionPredictorMetricsManager.cpp
index 0412d08..6872af2 100644
--- a/libs/input/MotionPredictorMetricsManager.cpp
+++ b/libs/input/MotionPredictorMetricsManager.cpp
@@ -113,7 +113,12 @@
// Adds new predictions to mRecentPredictions and maintains the invariant that elements are
// sorted in ascending order of targetTimestamp.
void MotionPredictorMetricsManager::onPredict(const MotionEvent& predictionEvent) {
- for (size_t i = 0; i < predictionEvent.getHistorySize() + 1; ++i) {
+ const size_t numPredictions = predictionEvent.getHistorySize() + 1;
+ if (numPredictions > mMaxNumPredictions) {
+ LOG(WARNING) << "numPredictions (" << numPredictions << ") > mMaxNumPredictions ("
+ << mMaxNumPredictions << "). Ignoring extra predictions in metrics.";
+ }
+ for (size_t i = 0; (i < numPredictions) && (i < mMaxNumPredictions); ++i) {
// Convert MotionEvent to PredictionPoint.
const PointerCoords* coords =
predictionEvent.getHistoricalRawPointerCoords(/*pointerIndex=*/0, i);
@@ -325,42 +330,44 @@
mAtomFields[i].highVelocityOffTrajectoryRmse =
static_cast<int>(offTrajectoryRmse * 1000);
}
+ }
- // Scale-invariant errors: reported only for the last time bucket, where the values
- // represent an average across all time buckets.
- if (i + 1 == mMaxNumPredictions) {
- // Compute error averages.
- float alongTrajectoryRmseSum = 0;
- float offTrajectoryRmseSum = 0;
- for (size_t j = 0; j < mAggregatedMetrics.size(); ++j) {
- // If we have general errors (checked above), we should always also have
- // scale-invariant errors.
- LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantErrorsCount == 0,
- "mAggregatedMetrics[%zu].scaleInvariantErrorsCount is 0", j);
-
- LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse < 0,
- "mAggregatedMetrics[%zu].scaleInvariantAlongTrajectorySse = %f "
- "should not be negative",
- j, mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse);
- alongTrajectoryRmseSum +=
- std::sqrt(mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse /
- mAggregatedMetrics[j].scaleInvariantErrorsCount);
-
- LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantOffTrajectorySse < 0,
- "mAggregatedMetrics[%zu].scaleInvariantOffTrajectorySse = %f "
- "should not be negative",
- j, mAggregatedMetrics[j].scaleInvariantOffTrajectorySse);
- offTrajectoryRmseSum +=
- std::sqrt(mAggregatedMetrics[j].scaleInvariantOffTrajectorySse /
- mAggregatedMetrics[j].scaleInvariantErrorsCount);
+ // Scale-invariant errors: the average scale-invariant error across all time buckets
+ // is reported in the last time bucket.
+ {
+ // Compute error averages.
+ float alongTrajectoryRmseSum = 0;
+ float offTrajectoryRmseSum = 0;
+ int bucket_count = 0;
+ for (size_t j = 0; j < mAggregatedMetrics.size(); ++j) {
+ if (mAggregatedMetrics[j].scaleInvariantErrorsCount == 0) {
+ continue;
}
- const float averageAlongTrajectoryRmse =
- alongTrajectoryRmseSum / mAggregatedMetrics.size();
+ LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse < 0,
+ "mAggregatedMetrics[%zu].scaleInvariantAlongTrajectorySse = %f "
+ "should not be negative",
+ j, mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse);
+ alongTrajectoryRmseSum +=
+ std::sqrt(mAggregatedMetrics[j].scaleInvariantAlongTrajectorySse /
+ mAggregatedMetrics[j].scaleInvariantErrorsCount);
+
+ LOG_ALWAYS_FATAL_IF(mAggregatedMetrics[j].scaleInvariantOffTrajectorySse < 0,
+ "mAggregatedMetrics[%zu].scaleInvariantOffTrajectorySse = %f "
+ "should not be negative",
+ j, mAggregatedMetrics[j].scaleInvariantOffTrajectorySse);
+ offTrajectoryRmseSum += std::sqrt(mAggregatedMetrics[j].scaleInvariantOffTrajectorySse /
+ mAggregatedMetrics[j].scaleInvariantErrorsCount);
+
+ ++bucket_count;
+ }
+
+ if (bucket_count > 0) {
+ const float averageAlongTrajectoryRmse = alongTrajectoryRmseSum / bucket_count;
mAtomFields.back().scaleInvariantAlongTrajectoryRmse =
static_cast<int>(averageAlongTrajectoryRmse * 1000);
- const float averageOffTrajectoryRmse = offTrajectoryRmseSum / mAggregatedMetrics.size();
+ const float averageOffTrajectoryRmse = offTrajectoryRmseSum / bucket_count;
mAtomFields.back().scaleInvariantOffTrajectoryRmse =
static_cast<int>(averageOffTrajectoryRmse * 1000);
}
diff --git a/libs/input/tests/MotionPredictorMetricsManager_test.cpp b/libs/input/tests/MotionPredictorMetricsManager_test.cpp
index 31cc145..cc41eeb 100644
--- a/libs/input/tests/MotionPredictorMetricsManager_test.cpp
+++ b/libs/input/tests/MotionPredictorMetricsManager_test.cpp
@@ -238,14 +238,17 @@
// --- Ground-truth-generation helper functions. ---
+// Generates numPoints ground truth points with values equal to those of the given
+// GroundTruthPoint, and with consecutive timestamps separated by the given inputInterval.
std::vector<GroundTruthPoint> generateConstantGroundTruthPoints(
- const GroundTruthPoint& groundTruthPoint, size_t numPoints) {
+ const GroundTruthPoint& groundTruthPoint, size_t numPoints,
+ nsecs_t inputInterval = TEST_PREDICTION_INTERVAL_NANOS) {
std::vector<GroundTruthPoint> groundTruthPoints;
nsecs_t timestamp = groundTruthPoint.timestamp;
for (size_t i = 0; i < numPoints; ++i) {
groundTruthPoints.emplace_back(groundTruthPoint);
groundTruthPoints.back().timestamp = timestamp;
- timestamp += TEST_PREDICTION_INTERVAL_NANOS;
+ timestamp += inputInterval;
}
return groundTruthPoints;
}
@@ -280,7 +283,8 @@
const GroundTruthPoint groundTruthPoint{{.position = Eigen::Vector2f(10, 20), .pressure = 0.3f},
.timestamp = TEST_INITIAL_TIMESTAMP};
const std::vector<GroundTruthPoint> groundTruthPoints =
- generateConstantGroundTruthPoints(groundTruthPoint, /*numPoints=*/3);
+ generateConstantGroundTruthPoints(groundTruthPoint, /*numPoints=*/3,
+ /*inputInterval=*/10);
ASSERT_EQ(3u, groundTruthPoints.size());
// First point.
@@ -290,11 +294,11 @@
// Second point.
EXPECT_EQ(groundTruthPoints[1].position, groundTruthPoint.position);
EXPECT_EQ(groundTruthPoints[1].pressure, groundTruthPoint.pressure);
- EXPECT_GT(groundTruthPoints[1].timestamp, groundTruthPoints[0].timestamp);
+ EXPECT_EQ(groundTruthPoints[1].timestamp, groundTruthPoint.timestamp + 10);
// Third point.
EXPECT_EQ(groundTruthPoints[2].position, groundTruthPoint.position);
EXPECT_EQ(groundTruthPoints[2].pressure, groundTruthPoint.pressure);
- EXPECT_GT(groundTruthPoints[2].timestamp, groundTruthPoints[1].timestamp);
+ EXPECT_EQ(groundTruthPoints[2].timestamp, groundTruthPoint.timestamp + 20);
}
TEST(GenerateCircularArcGroundTruthTest, StraightLineUpwards) {
@@ -333,16 +337,19 @@
// --- Prediction-generation helper functions. ---
-// Creates a sequence of predictions with values equal to those of the given GroundTruthPoint.
-std::vector<PredictionPoint> generateConstantPredictions(const GroundTruthPoint& groundTruthPoint) {
+// Generates TEST_MAX_NUM_PREDICTIONS predictions with values equal to those of the given
+// GroundTruthPoint, and with consecutive timestamps separated by the given predictionInterval.
+std::vector<PredictionPoint> generateConstantPredictions(
+ const GroundTruthPoint& groundTruthPoint,
+ nsecs_t predictionInterval = TEST_PREDICTION_INTERVAL_NANOS) {
std::vector<PredictionPoint> predictions;
- nsecs_t predictionTimestamp = groundTruthPoint.timestamp + TEST_PREDICTION_INTERVAL_NANOS;
+ nsecs_t predictionTimestamp = groundTruthPoint.timestamp + predictionInterval;
for (size_t j = 0; j < TEST_MAX_NUM_PREDICTIONS; ++j) {
predictions.push_back(PredictionPoint{{.position = groundTruthPoint.position,
.pressure = groundTruthPoint.pressure},
.originTimestamp = groundTruthPoint.timestamp,
.targetTimestamp = predictionTimestamp});
- predictionTimestamp += TEST_PREDICTION_INTERVAL_NANOS;
+ predictionTimestamp += predictionInterval;
}
return predictions;
}
@@ -375,8 +382,9 @@
TEST(GeneratePredictionsTest, GenerateConstantPredictions) {
const GroundTruthPoint groundTruthPoint{{.position = Eigen::Vector2f(10, 20), .pressure = 0.3f},
.timestamp = TEST_INITIAL_TIMESTAMP};
+ const nsecs_t predictionInterval = 10;
const std::vector<PredictionPoint> predictionPoints =
- generateConstantPredictions(groundTruthPoint);
+ generateConstantPredictions(groundTruthPoint, predictionInterval);
ASSERT_EQ(TEST_MAX_NUM_PREDICTIONS, predictionPoints.size());
for (size_t i = 0; i < predictionPoints.size(); ++i) {
@@ -385,8 +393,7 @@
EXPECT_THAT(predictionPoints[i].pressure, FloatNear(groundTruthPoint.pressure, 1e-6));
EXPECT_EQ(predictionPoints[i].originTimestamp, groundTruthPoint.timestamp);
EXPECT_EQ(predictionPoints[i].targetTimestamp,
- groundTruthPoint.timestamp +
- static_cast<nsecs_t>(i + 1) * TEST_PREDICTION_INTERVAL_NANOS);
+ TEST_INITIAL_TIMESTAMP + static_cast<nsecs_t>(i + 1) * predictionInterval);
}
}
@@ -678,12 +685,9 @@
// • groundTruthPoints: chronologically-ordered ground truth points, with at least 2 elements.
// • predictionPoints: the first index points to a vector of predictions corresponding to the
// source ground truth point with the same index.
-// - The first element should be empty, because there are not expected to be predictions until
-// we have received 2 ground truth points.
-// - The last element may be empty, because there will be no future ground truth points to
-// associate with those predictions (if not empty, it will be ignored).
+// - For empty prediction vectors, MetricsManager::onPredict will not be called.
// - To test all prediction buckets, there should be at least TEST_MAX_NUM_PREDICTIONS non-empty
-// prediction sets (that is, excluding the first and last). Thus, groundTruthPoints and
+// prediction vectors (that is, excluding the first and last). Thus, groundTruthPoints and
// predictionPoints should have size at least TEST_MAX_NUM_PREDICTIONS + 2.
//
// When the function returns, outReportedAtomFields will contain the reported AtomFields.
@@ -697,19 +701,12 @@
createMockReportAtomFunction(
outReportedAtomFields));
- // Validate structure of groundTruthPoints and predictionPoints.
- ASSERT_EQ(predictionPoints.size(), groundTruthPoints.size());
ASSERT_GE(groundTruthPoints.size(), 2u);
- ASSERT_EQ(predictionPoints[0].size(), 0u);
- for (size_t i = 1; i + 1 < predictionPoints.size(); ++i) {
- SCOPED_TRACE(testing::Message() << "i = " << i);
- ASSERT_EQ(predictionPoints[i].size(), TEST_MAX_NUM_PREDICTIONS);
- }
+ ASSERT_EQ(predictionPoints.size(), groundTruthPoints.size());
- // Pass ground truth points and predictions (for all except first and last ground truth).
for (size_t i = 0; i < groundTruthPoints.size(); ++i) {
metricsManager.onRecord(makeMotionEvent(groundTruthPoints[i]));
- if ((i > 0) && (i + 1 < predictionPoints.size())) {
+ if (!predictionPoints[i].empty()) {
metricsManager.onPredict(makeMotionEvent(predictionPoints[i]));
}
}
@@ -738,7 +735,7 @@
// Perfect predictions test:
// • Input: constant input events, perfect predictions matching the input events.
// • Expectation: all error metrics should be zero, or NO_DATA_SENTINEL for "unreported" metrics.
-// (For example, scale-invariant errors are only reported for the final time bucket.)
+// (For example, scale-invariant errors are only reported for the last time bucket.)
TEST(MotionPredictorMetricsManagerTest, ConstantGroundTruthPerfectPredictions) {
GroundTruthPoint groundTruthPoint{{.position = Eigen::Vector2f(10.0f, 20.0f), .pressure = 0.6f},
.timestamp = TEST_INITIAL_TIMESTAMP};
@@ -977,5 +974,35 @@
}
}
+// Robustness test:
+// • Input: input events separated by a significantly greater time interval than the interval
+// between predictions.
+// • Expectation: the MetricsManager should not crash in this case. (No assertions are made about
+// the resulting metrics.)
+//
+// In practice, this scenario could arise either if the input and prediction intervals are
+// mismatched, or if input events are missing (dropped or skipped for some reason).
+TEST(MotionPredictorMetricsManagerTest, MismatchedInputAndPredictionInterval) {
+ // Create two ground truth points separated by MAX_NUM_PREDICTIONS * PREDICTION_INTERVAL,
+ // so that the second ground truth point corresponds to the last prediction bucket. This
+ // ensures that the scale-invariant error codepath will be run, giving full code coverage.
+ GroundTruthPoint groundTruthPoint{{.position = Eigen::Vector2f(0.0f, 0.0f), .pressure = 0.5f},
+ .timestamp = TEST_INITIAL_TIMESTAMP};
+ const nsecs_t inputInterval = TEST_MAX_NUM_PREDICTIONS * TEST_PREDICTION_INTERVAL_NANOS;
+ const std::vector<GroundTruthPoint> groundTruthPoints =
+ generateConstantGroundTruthPoints(groundTruthPoint, /*numPoints=*/2, inputInterval);
+
+ // Create predictions separated by the prediction interval.
+ std::vector<std::vector<PredictionPoint>> predictionPoints;
+ for (size_t i = 0; i < groundTruthPoints.size(); ++i) {
+ predictionPoints.push_back(
+ generateConstantPredictions(groundTruthPoints[i], TEST_PREDICTION_INTERVAL_NANOS));
+ }
+
+ // Test that we can run the MetricsManager without crashing.
+ std::vector<AtomFields> reportedAtomFields;
+ runMetricsManager(groundTruthPoints, predictionPoints, reportedAtomFields);
+}
+
} // namespace
} // namespace android