Merge "Call into validateBufferSize and getTransportSize" into qt-dev
diff --git a/automotive/evs/1.0/vts/functional/FormatConvert.cpp b/automotive/evs/1.0/vts/functional/FormatConvert.cpp
index 1e8929d..3d82d32 100644
--- a/automotive/evs/1.0/vts/functional/FormatConvert.cpp
+++ b/automotive/evs/1.0/vts/functional/FormatConvert.cpp
@@ -38,7 +38,8 @@
}
-static uint32_t yuvToRgbx(const unsigned char Y, const unsigned char Uin, const unsigned char Vin) {
+static uint32_t yuvToRgbx(const unsigned char Y, const unsigned char Uin, const unsigned char Vin,
+ bool bgrxFormat = false) {
// Don't use this if you want to see the best performance. :)
// Better to do this in a pixel shader if we really have to, but on actual
// embedded hardware we expect to be able to texture directly from the YUV data
@@ -52,16 +53,24 @@
unsigned char G = (unsigned char)clamp(Gf, 0.0f, 255.0f);
unsigned char B = (unsigned char)clamp(Bf, 0.0f, 255.0f);
- return (R ) |
- (G << 8) |
- (B << 16) |
- 0xFF000000; // Fill the alpha channel with ones
+ if (!bgrxFormat) {
+ return (R ) |
+ (G << 8) |
+ (B << 16) |
+ 0xFF000000; // Fill the alpha channel with ones
+ } else {
+ return (R << 16) |
+ (G << 8) |
+ (B ) |
+ 0xFF000000; // Fill the alpha channel with ones
+ }
}
void copyNV21toRGB32(unsigned width, unsigned height,
uint8_t* src,
- uint32_t* dst, unsigned dstStridePixels)
+ uint32_t* dst, unsigned dstStridePixels,
+ bool bgrxFormat)
{
// The NV21 format provides a Y array of 8bit values, followed by a 1/2 x 1/2 interleaved
// U/V array. It assumes an even width and height for the overall image, and a horizontal
@@ -84,7 +93,7 @@
for (unsigned c = 0; c < width; c++) {
unsigned uCol = (c & ~1); // uCol is always even and repeats 1:2 with Y values
unsigned vCol = uCol | 1; // vCol is always odd
- rowDest[c] = yuvToRgbx(rowY[c], rowUV[uCol], rowUV[vCol]);
+ rowDest[c] = yuvToRgbx(rowY[c], rowUV[uCol], rowUV[vCol], bgrxFormat);
}
}
}
@@ -92,7 +101,8 @@
void copyYV12toRGB32(unsigned width, unsigned height,
uint8_t* src,
- uint32_t* dst, unsigned dstStridePixels)
+ uint32_t* dst, unsigned dstStridePixels,
+ bool bgrxFormat)
{
// The YV12 format provides a Y array of 8bit values, followed by a 1/2 x 1/2 U array, followed
// by another 1/2 x 1/2 V array. It assumes an even width and height for the overall image,
@@ -118,7 +128,7 @@
uint32_t* rowDest = dst + r*dstStridePixels;
for (unsigned c = 0; c < width; c++) {
- rowDest[c] = yuvToRgbx(rowY[c], rowU[c], rowV[c]);
+ rowDest[c] = yuvToRgbx(rowY[c], rowU[c], rowV[c], bgrxFormat);
}
}
}
@@ -126,7 +136,8 @@
void copyYUYVtoRGB32(unsigned width, unsigned height,
uint8_t* src, unsigned srcStridePixels,
- uint32_t* dst, unsigned dstStridePixels)
+ uint32_t* dst, unsigned dstStridePixels,
+ bool bgrxFormat)
{
uint32_t* srcWords = (uint32_t*)src;
@@ -144,8 +155,8 @@
uint8_t V = (srcPixel >> 24) & 0xFF;
// On the RGB output, we're writing one pixel at a time
- *(dst+0) = yuvToRgbx(Y1, U, V);
- *(dst+1) = yuvToRgbx(Y2, U, V);
+ *(dst+0) = yuvToRgbx(Y1, U, V, bgrxFormat);
+ *(dst+1) = yuvToRgbx(Y2, U, V, bgrxFormat);
dst += 2;
}
@@ -156,6 +167,30 @@
}
+void copyNV21toBGR32(unsigned width, unsigned height,
+ uint8_t* src,
+ uint32_t* dst, unsigned dstStridePixels)
+{
+ return copyNV21toRGB32(width, height, src, dst, dstStridePixels, true);
+}
+
+
+void copyYV12toBGR32(unsigned width, unsigned height,
+ uint8_t* src,
+ uint32_t* dst, unsigned dstStridePixels)
+{
+ return copyYV12toRGB32(width, height, src, dst, dstStridePixels, true);
+}
+
+
+void copyYUYVtoBGR32(unsigned width, unsigned height,
+ uint8_t* src, unsigned srcStridePixels,
+ uint32_t* dst, unsigned dstStridePixels)
+{
+ return copyYUYVtoRGB32(width, height, src, srcStridePixels, dst, dstStridePixels, true);
+}
+
+
void copyMatchedInterleavedFormats(unsigned width, unsigned height,
void* src, unsigned srcStridePixels,
void* dst, unsigned dstStridePixels,
diff --git a/automotive/evs/1.0/vts/functional/FormatConvert.h b/automotive/evs/1.0/vts/functional/FormatConvert.h
index 3ff1eec..4a94f99 100644
--- a/automotive/evs/1.0/vts/functional/FormatConvert.h
+++ b/automotive/evs/1.0/vts/functional/FormatConvert.h
@@ -21,31 +21,45 @@
#include <stdint.h>
-// Given an image buffer in NV21 format (HAL_PIXEL_FORMAT_YCRCB_420_SP), output 32bit RGBx values.
-// The NV21 format provides a Y array of 8bit values, followed by a 1/2 x 1/2 interleaved
+// Given an image buffer in NV21 format (HAL_PIXEL_FORMAT_YCRCB_420_SP), output 32bit RGBx/BGRx
+// values. The NV21 format provides a Y array of 8bit values, followed by a 1/2 x 1/2 interleaved
// U/V array. It assumes an even width and height for the overall image, and a horizontal
// stride that is an even multiple of 16 bytes for both the Y and UV arrays.
void copyNV21toRGB32(unsigned width, unsigned height,
uint8_t* src,
+ uint32_t* dst, unsigned dstStridePixels,
+ bool bgrxFormat = false);
+
+void copyNV21toBGR32(unsigned width, unsigned height,
+ uint8_t* src,
uint32_t* dst, unsigned dstStridePixels);
-// Given an image buffer in YV12 format (HAL_PIXEL_FORMAT_YV12), output 32bit RGBx values.
+// Given an image buffer in YV12 format (HAL_PIXEL_FORMAT_YV12), output 32bit RGBx/BGRx values.
// The YV12 format provides a Y array of 8bit values, followed by a 1/2 x 1/2 U array, followed
// by another 1/2 x 1/2 V array. It assumes an even width and height for the overall image,
// and a horizontal stride that is an even multiple of 16 bytes for each of the Y, U,
// and V arrays.
void copyYV12toRGB32(unsigned width, unsigned height,
uint8_t* src,
+ uint32_t* dst, unsigned dstStridePixels,
+ bool bgrxFormat = false);
+
+void copyYV12toBGR32(unsigned width, unsigned height,
+ uint8_t* src,
uint32_t* dst, unsigned dstStridePixels);
-
-// Given an image buffer in YUYV format (HAL_PIXEL_FORMAT_YCBCR_422_I), output 32bit RGBx values.
-// The NV21 format provides a Y array of 8bit values, followed by a 1/2 x 1/2 interleaved
+// Given an image buffer in YUYV format (HAL_PIXEL_FORMAT_YCBCR_422_I), output 32bit RGBx/BGRx
+// values. The NV21 format provides a Y array of 8bit values, followed by a 1/2 x 1/2 interleaved
// U/V array. It assumes an even width and height for the overall image, and a horizontal
// stride that is an even multiple of 16 bytes for both the Y and UV arrays.
void copyYUYVtoRGB32(unsigned width, unsigned height,
uint8_t* src, unsigned srcStrideBytes,
+ uint32_t* dst, unsigned dstStrideBytes,
+ bool bgrxFormat = false);
+
+void copyYUYVtoBGR32(unsigned width, unsigned height,
+ uint8_t* src, unsigned srcStrideBytes,
uint32_t* dst, unsigned dstStrideBytes);
diff --git a/automotive/evs/1.0/vts/functional/FrameHandler.cpp b/automotive/evs/1.0/vts/functional/FrameHandler.cpp
index a69f72b..d44ba41 100644
--- a/automotive/evs/1.0/vts/functional/FrameHandler.cpp
+++ b/automotive/evs/1.0/vts/functional/FrameHandler.cpp
@@ -231,16 +231,12 @@
uint8_t* srcPixels = nullptr;
src->lock(GRALLOC_USAGE_SW_READ_OFTEN, (void**)&srcPixels);
- // Lock our target buffer for writing (should be RGBA8888 format)
+ // Lock our target buffer for writing (should be either RGBA8888 or BGRA8888 format)
uint32_t* tgtPixels = nullptr;
tgt->lock(GRALLOC_USAGE_SW_WRITE_OFTEN, (void**)&tgtPixels);
if (srcPixels && tgtPixels) {
- if (tgtBuffer.format != HAL_PIXEL_FORMAT_RGBA_8888) {
- // We always expect 32 bit RGB for the display output for now. Is there a need for 565?
- ALOGE("Diplay buffer is always expected to be 32bit RGBA");
- success = false;
- } else {
+ if (tgtBuffer.format == HAL_PIXEL_FORMAT_RGBA_8888) {
if (srcBuffer.format == HAL_PIXEL_FORMAT_YCRCB_420_SP) { // 420SP == NV21
copyNV21toRGB32(width, height,
srcPixels,
@@ -258,7 +254,36 @@
srcPixels, srcBuffer.stride,
tgtPixels, tgtBuffer.stride,
tgtBuffer.pixelSize);
+ } else {
+ ALOGE("Camera buffer format is not supported");
+ success = false;
}
+ } else if (tgtBuffer.format == HAL_PIXEL_FORMAT_BGRA_8888) {
+ if (srcBuffer.format == HAL_PIXEL_FORMAT_YCRCB_420_SP) { // 420SP == NV21
+ copyNV21toBGR32(width, height,
+ srcPixels,
+ tgtPixels, tgtBuffer.stride);
+ } else if (srcBuffer.format == HAL_PIXEL_FORMAT_YV12) { // YUV_420P == YV12
+ copyYV12toBGR32(width, height,
+ srcPixels,
+ tgtPixels, tgtBuffer.stride);
+ } else if (srcBuffer.format == HAL_PIXEL_FORMAT_YCBCR_422_I) { // YUYV
+ copyYUYVtoBGR32(width, height,
+ srcPixels, srcBuffer.stride,
+ tgtPixels, tgtBuffer.stride);
+ } else if (srcBuffer.format == tgtBuffer.format) { // 32bit RGBA
+ copyMatchedInterleavedFormats(width, height,
+ srcPixels, srcBuffer.stride,
+ tgtPixels, tgtBuffer.stride,
+ tgtBuffer.pixelSize);
+ } else {
+ ALOGE("Camera buffer format is not supported");
+ success = false;
+ }
+ } else {
+ // We always expect 32 bit RGB for the display output for now. Is there a need for 565?
+ ALOGE("Diplay buffer is always expected to be 32bit RGBA");
+ success = false;
}
} else {
ALOGE("Failed to lock buffer contents for contents transfer");
diff --git a/broadcastradio/common/tests/Android.bp b/broadcastradio/common/tests/Android.bp
index ef8733c..0ace941 100644
--- a/broadcastradio/common/tests/Android.bp
+++ b/broadcastradio/common/tests/Android.bp
@@ -58,6 +58,7 @@
"android.hardware.broadcastradio@common-utils-2x-lib",
],
shared_libs: [
+ "libhidlbase",
"android.hardware.broadcastradio@2.0",
],
test_suites: ["general-tests"],
diff --git a/camera/device/3.4/default/ExternalCameraDevice.cpp b/camera/device/3.4/default/ExternalCameraDevice.cpp
index 3f04751..9a2fddf 100644
--- a/camera/device/3.4/default/ExternalCameraDevice.cpp
+++ b/camera/device/3.4/default/ExternalCameraDevice.cpp
@@ -342,8 +342,7 @@
256, 144,
240, 160,
256, 154,
- 240, 240,
- 320, 240};
+ 240, 180};
UPDATE(ANDROID_JPEG_AVAILABLE_THUMBNAIL_SIZES, jpegAvailableThumbnailSizes,
ARRAY_SIZE(jpegAvailableThumbnailSizes));
diff --git a/compatibility_matrices/compatibility_matrix.4.xml b/compatibility_matrices/compatibility_matrix.4.xml
index a34f746..7d6fc60 100644
--- a/compatibility_matrices/compatibility_matrix.4.xml
+++ b/compatibility_matrices/compatibility_matrix.4.xml
@@ -181,7 +181,12 @@
</hal>
<hal format="hidl" optional="true">
<name>android.hardware.gnss</name>
- <version>1.0-1</version>
+ <!--
+ - Both versions are listed here as a workaround for libvintf since 2.0 extends 1.1.
+ - Devices launched with Q must support gnss@2.0, see VtsTrebleVendorVintfTest
+ - test DeviceManifestTest#GnssHalVersionCompatibility.
+ -->
+ <version>1.1</version>
<version>2.0</version>
<interface>
<name>IGnss</name>
@@ -494,14 +499,6 @@
</interface>
</hal>
<hal format="hidl" optional="true">
- <name>android.hardware.wifi.offload</name>
- <version>1.0</version>
- <interface>
- <name>IOffload</name>
- <instance>default</instance>
- </interface>
- </hal>
- <hal format="hidl" optional="true">
<name>android.hardware.wifi.supplicant</name>
<version>1.0-2</version>
<interface>
diff --git a/current.txt b/current.txt
index 1d1b80a..3083947 100644
--- a/current.txt
+++ b/current.txt
@@ -401,8 +401,8 @@
65a021fa89085b62fc96b2b6d3bef2f9103cf4d63379c68bc154fd9eef672852 android.hardware.health@1.0::types
b7ecf29927055ec422ec44bf776223f07d79ad9f92ccf9becf167e62c2607e7a android.hardware.keymaster@4.0::IKeymasterDevice
574e8f1499436fb4075894dcae0b36682427956ecb114f17f1fe22d116a83c6b android.hardware.neuralnetworks@1.0::IPreparedModel
-417ab60fe1ef786778047e4486f3d868ebce570d91addd8fe4251515213072de android.hardware.neuralnetworks@1.0::types
-ec8aa14fe9b03f2b3fb9845346a4005b6d098ebe2277b2564f73a548a0fd14a7 android.hardware.neuralnetworks@1.1::types
+e75759b40a1c5f97b463b30aab91954012c9ea9e454dde308db853a56796e5a6 android.hardware.neuralnetworks@1.0::types
+eb754b58c93e5591613208b4c972811288b0fa16a82430d602f107c91a908b22 android.hardware.neuralnetworks@1.1::types
1d4a5776614c08b5d794a5ec5ab04697260cbd4b3441d5935cd53ee71d19da02 android.hardware.radio@1.0::IRadioResponse
ed9da80ec0c96991fd03f0a46107815d0e50f764656e49dba4980fa5c31d5bc3 android.hardware.radio@1.0::types
1d19720d4fd38b1095f0f555a4bd92b3b12c9b1d0f560b0e9a474cd6dcc20db6 android.hardware.radio@1.2::IRadio
@@ -515,7 +515,7 @@
92714960d1a53fc2ec557302b41c7cc93d2636d8364a44bd0f85be0c92927ff8 android.hardware.neuralnetworks@1.2::IExecutionCallback
36e1064c869965dee533c537cefbe87e54db8bd8cd45be7e0e93e00e8a43863a android.hardware.neuralnetworks@1.2::IPreparedModel
e1c734d1545e1a4ae749ff1dd9704a8e594c59aea7c8363159dc258e93e0df3b android.hardware.neuralnetworks@1.2::IPreparedModelCallback
-b75126d572c1788682a679ab53c2dbdf3fcd75f754b1370dbf09aaad0e19d397 android.hardware.neuralnetworks@1.2::types
+e3b6176e3bf235c4e0e4e451b0166e396c7ee176cfe167c9147c3d46d7b34f0c android.hardware.neuralnetworks@1.2::types
cf7a4ba516a638f9b82a249c91fb603042c2d9ca43fd5aad9cf6c0401ed2a5d7 android.hardware.nfc@1.2::INfc
abf98c2ae08bf765db54edc8068e36d52eb558cff6706b6fd7c18c65a1f3fc18 android.hardware.nfc@1.2::types
4cb252dc6372a874aef666b92a6e9529915aa187521a700f0789065c3c702ead android.hardware.power.stats@1.0::IPowerStats
diff --git a/gnss/2.0/vts/functional/gnss_hal_test.cpp b/gnss/2.0/vts/functional/gnss_hal_test.cpp
index da6092b..febd0f1 100644
--- a/gnss/2.0/vts/functional/gnss_hal_test.cpp
+++ b/gnss/2.0/vts/functional/gnss_hal_test.cpp
@@ -23,38 +23,34 @@
using ::android::hardware::gnss::common::Utils;
// Implementations for the main test class for GNSS HAL
-GnssHalTest::GnssHalTest()
- : info_called_count_(0),
- capabilities_called_count_(0),
- measurement_corrections_capabilities_called_count_(0),
- location_called_count_(0),
- name_called_count_(0),
- notify_count_(0) {}
+GnssHalTest::GnssHalTest() {}
void GnssHalTest::SetUp() {
gnss_hal_ = ::testing::VtsHalHidlTargetTestBase::getService<IGnss>(
GnssHidlEnvironment::Instance()->getServiceName<IGnss>());
- list_vec_gnss_sv_info_.clear();
ASSERT_NE(gnss_hal_, nullptr);
SetUpGnssCallback();
}
void GnssHalTest::TearDown() {
- // Reset counters
- info_called_count_ = 0;
- capabilities_called_count_ = 0;
- measurement_corrections_capabilities_called_count_ = 0;
- location_called_count_ = 0;
- name_called_count_ = 0;
- measurement_called_count_ = 0;
-
if (gnss_hal_ != nullptr) {
gnss_hal_->cleanup();
}
- if (notify_count_ > 0) {
- ALOGW("%d unprocessed callbacks discarded", notify_count_);
+
+ int unprocessedEventsCount = measurement_cbq_.size() + location_cbq_.size();
+ if (unprocessedEventsCount > 0) {
+ ALOGW("%d unprocessed callbacks discarded", unprocessedEventsCount);
}
+
+ // Reset all callback event queues.
+ info_cbq_.reset();
+ name_cbq_.reset();
+ top_hal_capabilities_cbq_.reset();
+ measurement_corrections_capabilities_cbq_.reset();
+ measurement_cbq_.reset();
+ location_cbq_.reset();
+ sv_info_cbq_.reset();
}
void GnssHalTest::SetUpGnssCallback() {
@@ -72,13 +68,13 @@
/*
* All capabilities, name and systemInfo callbacks should trigger
*/
- EXPECT_EQ(std::cv_status::no_timeout, wait(TIMEOUT_SEC));
- EXPECT_EQ(std::cv_status::no_timeout, wait(TIMEOUT_SEC));
- EXPECT_EQ(std::cv_status::no_timeout, wait(TIMEOUT_SEC));
+ EXPECT_TRUE(top_hal_capabilities_cbq_.retrieve(last_capabilities_, TIMEOUT_SEC));
+ EXPECT_TRUE(info_cbq_.retrieve(last_info_, TIMEOUT_SEC));
+ EXPECT_TRUE(name_cbq_.retrieve(last_name_, TIMEOUT_SEC));
- EXPECT_EQ(capabilities_called_count_, 1);
- EXPECT_EQ(info_called_count_, 1);
- EXPECT_EQ(name_called_count_, 1);
+ EXPECT_EQ(top_hal_capabilities_cbq_.calledCount(), 1);
+ EXPECT_EQ(info_cbq_.calledCount(), 1);
+ EXPECT_EQ(name_cbq_.calledCount(), 1);
}
void GnssHalTest::StopAndClearLocations() {
@@ -92,9 +88,8 @@
* the last reply for final startup messages to arrive (esp. system
* info.)
*/
- while (wait(TIMEOUT_SEC) == std::cv_status::no_timeout) {
- }
- location_called_count_ = 0;
+ location_cbq_.waitUntilEmpty(TIMEOUT_SEC);
+ location_cbq_.reset();
}
void GnssHalTest::SetPositionMode(const int min_interval_msec, const bool low_power_mode) {
@@ -121,10 +116,11 @@
*/
const int kFirstGnssLocationTimeoutSeconds = 75;
- wait(kFirstGnssLocationTimeoutSeconds);
- EXPECT_EQ(location_called_count_, 1);
+ EXPECT_TRUE(location_cbq_.retrieve(last_location_, kFirstGnssLocationTimeoutSeconds));
+ int locationCalledCount = location_cbq_.calledCount();
+ EXPECT_EQ(locationCalledCount, 1);
- if (location_called_count_ > 0) {
+ if (locationCalledCount > 0) {
// don't require speed on first fix
CheckLocation(last_location_, false);
return true;
@@ -133,7 +129,7 @@
}
void GnssHalTest::CheckLocation(const GnssLocation_2_0& location, bool check_speed) {
- const bool check_more_accuracies = (info_called_count_ > 0 && last_info_.yearOfHw >= 2017);
+ const bool check_more_accuracies = (info_cbq_.calledCount() > 0 && last_info_.yearOfHw >= 2017);
Utils::checkLocation(location.v1_0, check_speed, check_more_accuracies);
}
@@ -148,77 +144,39 @@
EXPECT_TRUE(StartAndCheckFirstLocation());
for (int i = 1; i < count; i++) {
- EXPECT_EQ(std::cv_status::no_timeout, wait(kLocationTimeoutSubsequentSec));
- EXPECT_EQ(location_called_count_, i + 1);
+ EXPECT_TRUE(location_cbq_.retrieve(last_location_, kLocationTimeoutSubsequentSec));
+ int locationCalledCount = location_cbq_.calledCount();
+ EXPECT_EQ(locationCalledCount, i + 1);
// Don't cause confusion by checking details if no location yet
- if (location_called_count_ > 0) {
+ if (locationCalledCount > 0) {
// Should be more than 1 location by now, but if not, still don't check first fix speed
- CheckLocation(last_location_, location_called_count_ > 1);
+ CheckLocation(last_location_, locationCalledCount > 1);
}
}
}
-void GnssHalTest::notify() {
- {
- std::unique_lock<std::mutex> lock(mtx_);
- notify_count_++;
- }
- cv_.notify_one();
-}
-
-std::cv_status GnssHalTest::wait(int timeout_seconds) {
- std::unique_lock<std::mutex> lock(mtx_);
-
- auto status = std::cv_status::no_timeout;
- while (notify_count_ == 0) {
- status = cv_.wait_for(lock, std::chrono::seconds(timeout_seconds));
- if (status == std::cv_status::timeout) return status;
- }
- notify_count_--;
- return status;
-}
-
-std::cv_status GnssHalTest::waitForMeasurementCorrectionsCapabilities(int timeout_seconds) {
- std::unique_lock<std::mutex> lock(mtx_);
- auto status = std::cv_status::no_timeout;
- while (measurement_corrections_capabilities_called_count_ == 0) {
- status = cv_.wait_for(lock, std::chrono::seconds(timeout_seconds));
- if (status == std::cv_status::timeout) return status;
- }
- notify_count_--;
- return status;
-}
-
Return<void> GnssHalTest::GnssCallback::gnssSetSystemInfoCb(
const IGnssCallback_1_0::GnssSystemInfo& info) {
ALOGI("Info received, year %d", info.yearOfHw);
- parent_.info_called_count_++;
- parent_.last_info_ = info;
- parent_.notify();
+ parent_.info_cbq_.store(info);
return Void();
}
Return<void> GnssHalTest::GnssCallback::gnssSetCapabilitesCb(uint32_t capabilities) {
ALOGI("Capabilities received %d", capabilities);
- parent_.capabilities_called_count_++;
- parent_.last_capabilities_ = capabilities;
- parent_.notify();
+ parent_.top_hal_capabilities_cbq_.store(capabilities);
return Void();
}
Return<void> GnssHalTest::GnssCallback::gnssSetCapabilitiesCb_2_0(uint32_t capabilities) {
ALOGI("Capabilities (v2.0) received %d", capabilities);
- parent_.capabilities_called_count_++;
- parent_.last_capabilities_ = capabilities;
- parent_.notify();
+ parent_.top_hal_capabilities_cbq_.store(capabilities);
return Void();
}
Return<void> GnssHalTest::GnssCallback::gnssNameCb(const android::hardware::hidl_string& name) {
ALOGI("Name received: %s", name.c_str());
- parent_.name_called_count_++;
- parent_.last_name_ = name;
- parent_.notify();
+ parent_.name_cbq_.store(name);
return Void();
}
@@ -235,40 +193,32 @@
}
Return<void> GnssHalTest::GnssCallback::gnssLocationCbImpl(const GnssLocation_2_0& location) {
- parent_.location_called_count_++;
- parent_.last_location_ = location;
- parent_.notify();
+ parent_.location_cbq_.store(location);
return Void();
}
Return<void> GnssHalTest::GnssCallback::gnssSvStatusCb(const IGnssCallback_1_0::GnssSvStatus&) {
ALOGI("gnssSvStatusCb");
-
return Void();
}
Return<void> GnssHalTest::GnssMeasurementCallback::gnssMeasurementCb_2_0(
const IGnssMeasurementCallback_2_0::GnssData& data) {
ALOGD("GnssMeasurement received. Size = %d", (int)data.measurements.size());
- parent_.measurement_called_count_++;
- parent_.last_measurement_ = data;
- parent_.notify();
+ parent_.measurement_cbq_.store(data);
return Void();
}
Return<void> GnssHalTest::GnssMeasurementCorrectionsCallback::setCapabilitiesCb(
uint32_t capabilities) {
ALOGI("GnssMeasurementCorrectionsCallback capabilities received %d", capabilities);
- parent_.measurement_corrections_capabilities_called_count_++;
- parent_.last_measurement_corrections_capabilities_ = capabilities;
- parent_.notify();
+ parent_.measurement_corrections_capabilities_cbq_.store(capabilities);
return Void();
}
Return<void> GnssHalTest::GnssCallback::gnssSvStatusCb_2_0(
const hidl_vec<IGnssCallback_2_0::GnssSvInfo>& svInfoList) {
ALOGI("gnssSvStatusCb_2_0. Size = %d", (int)svInfoList.size());
- parent_.list_vec_gnss_sv_info_.emplace_back(svInfoList);
- parent_.notify();
+ parent_.sv_info_cbq_.store(svInfoList);
return Void();
}
diff --git a/gnss/2.0/vts/functional/gnss_hal_test.h b/gnss/2.0/vts/functional/gnss_hal_test.h
index 737815f..8e440ff 100644
--- a/gnss/2.0/vts/functional/gnss_hal_test.h
+++ b/gnss/2.0/vts/functional/gnss_hal_test.h
@@ -22,7 +22,7 @@
#include <VtsHalHidlTargetTestEnvBase.h>
#include <condition_variable>
-#include <list>
+#include <deque>
#include <mutex>
using android::hardware::hidl_vec;
@@ -125,7 +125,7 @@
/* Callback class for GnssMeasurement. */
class GnssMeasurementCallback : public IGnssMeasurementCallback_2_0 {
- public:
+ public:
GnssHalTest& parent_;
GnssMeasurementCallback(GnssHalTest& parent) : parent_(parent){};
virtual ~GnssMeasurementCallback() = default;
@@ -155,6 +155,77 @@
Return<void> setCapabilitiesCb(uint32_t capabilities) override;
};
+ /* Producer/consumer queue for storing/retrieving callback events from GNSS HAL */
+ template <class T>
+ class CallbackQueue {
+ public:
+ CallbackQueue() : called_count_(0){};
+
+ /* Adds callback event to the end of the queue. */
+ void store(const T& event) {
+ std::unique_lock<std::recursive_mutex> lock(mtx_);
+ events_.push_back(event);
+ ++called_count_;
+ lock.unlock();
+ cv_.notify_all();
+ }
+
+ /*
+ * Removes the callack event at the front of the queue, stores it in event parameter
+ * and returns true. If the timeout occurs waiting for callback event, returns false.
+ */
+ bool retrieve(T& event, int timeout_seconds) {
+ std::unique_lock<std::recursive_mutex> lock(mtx_);
+ cv_.wait_for(lock, std::chrono::seconds(timeout_seconds),
+ [&] { return !events_.empty(); });
+ if (events_.empty()) {
+ return false;
+ }
+ event = events_.front();
+ events_.pop_front();
+ return true;
+ }
+
+ /* Returns the number of events pending to be retrieved from the callback event queue. */
+ int size() const {
+ std::unique_lock<std::recursive_mutex> lock(mtx_);
+ return events_.size();
+ }
+
+ /* Returns the number of callback events received since last reset(). */
+ int calledCount() const {
+ std::unique_lock<std::recursive_mutex> lock(mtx_);
+ return called_count_;
+ }
+
+ /* Clears the callback event queue and resets the calledCount() to 0. */
+ void reset() {
+ std::unique_lock<std::recursive_mutex> lock(mtx_);
+ events_.clear();
+ called_count_ = 0;
+ }
+
+ /*
+ * Blocks the calling thread until the callback event queue becomes empty or timeout
+ * occurs. Returns false on timeout.
+ */
+ bool waitUntilEmpty(int timeout_seconds) {
+ std::unique_lock<std::recursive_mutex> lock(mtx_);
+ cv_.wait_for(lock, std::chrono::seconds(timeout_seconds),
+ [&] { return events_.empty(); });
+ return !events_.empty();
+ }
+
+ private:
+ CallbackQueue(const CallbackQueue&) = delete;
+ CallbackQueue& operator=(const CallbackQueue&) = delete;
+
+ mutable std::recursive_mutex mtx_;
+ std::condition_variable_any cv_;
+ std::deque<T> events_;
+ int called_count_;
+ };
+
/*
* SetUpGnssCallback:
* Set GnssCallback and verify the result.
@@ -205,30 +276,19 @@
sp<IGnss> gnss_hal_; // GNSS HAL to call into
sp<IGnssCallback_2_0> gnss_cb_; // Primary callback interface
- // TODO: make these variables thread-safe.
- /* Count of calls to set the following items, and the latest item (used by
- * test.)
- */
- int info_called_count_;
- int capabilities_called_count_;
- int measurement_corrections_capabilities_called_count_;
- int location_called_count_;
- int measurement_called_count_;
- int name_called_count_;
-
IGnssCallback_1_0::GnssSystemInfo last_info_;
uint32_t last_capabilities_;
uint32_t last_measurement_corrections_capabilities_;
GnssLocation_2_0 last_location_;
- IGnssMeasurementCallback_2_0::GnssData last_measurement_;
android::hardware::hidl_string last_name_;
- list<hidl_vec<IGnssCallback_2_0::GnssSvInfo>> list_vec_gnss_sv_info_;
-
- private:
- std::mutex mtx_;
- std::condition_variable cv_;
- int notify_count_;
+ CallbackQueue<IGnssCallback_1_0::GnssSystemInfo> info_cbq_;
+ CallbackQueue<android::hardware::hidl_string> name_cbq_;
+ CallbackQueue<uint32_t> top_hal_capabilities_cbq_;
+ CallbackQueue<uint32_t> measurement_corrections_capabilities_cbq_;
+ CallbackQueue<IGnssMeasurementCallback_2_0::GnssData> measurement_cbq_;
+ CallbackQueue<GnssLocation_2_0> location_cbq_;
+ CallbackQueue<hidl_vec<IGnssCallback_2_0::GnssSvInfo>> sv_info_cbq_;
};
#endif // GNSS_HAL_TEST_H_
diff --git a/gnss/2.0/vts/functional/gnss_hal_test_cases.cpp b/gnss/2.0/vts/functional/gnss_hal_test_cases.cpp
index be182a9..009f43d 100644
--- a/gnss/2.0/vts/functional/gnss_hal_test_cases.cpp
+++ b/gnss/2.0/vts/functional/gnss_hal_test_cases.cpp
@@ -29,6 +29,7 @@
using IGnssMeasurement_1_1 = android::hardware::gnss::V1_1::IGnssMeasurement;
using IGnssMeasurement_1_0 = android::hardware::gnss::V1_0::IGnssMeasurement;
using IAGnssRil_2_0 = android::hardware::gnss::V2_0::IAGnssRil;
+using IAGnssRil_1_0 = android::hardware::gnss::V1_0::IAGnssRil;
using IAGnss_2_0 = android::hardware::gnss::V2_0::IAGnss;
using IAGnss_1_0 = android::hardware::gnss::V1_0::IAGnss;
using IAGnssCallback_2_0 = android::hardware::gnss::V2_0::IAGnssCallback;
@@ -125,16 +126,21 @@
* TestAGnssRilExtension:
* Gets the AGnssRilExtension and verifies that it returns an actual extension.
*
- * The GNSS HAL 2.0 implementation must support @2.0::IAGnssRil interface due to the deprecation
- * of framework network API methods needed to support the @1.0::IAGnssRil interface.
- *
- * TODO (b/121287858): Enforce gnss@2.0 HAL package is supported on devices launched with Q or later
+ * If IAGnssRil interface is supported, then the GNSS HAL 2.0 implementation must support
+ * @2.0::IAGnssRil interface due to the deprecation of framework network API methods needed
+ * to support the @1.0::IAGnssRil interface.
*/
TEST_F(GnssHalTest, TestAGnssRilExtension) {
- auto agnssRil = gnss_hal_->getExtensionAGnssRil_2_0();
- ASSERT_TRUE(agnssRil.isOk());
- sp<IAGnssRil_2_0> iAGnssRil = agnssRil;
- ASSERT_NE(iAGnssRil, nullptr);
+ auto agnssRil_2_0 = gnss_hal_->getExtensionAGnssRil_2_0();
+ ASSERT_TRUE(agnssRil_2_0.isOk());
+ sp<IAGnssRil_2_0> iAGnssRil_2_0 = agnssRil_2_0;
+ if (iAGnssRil_2_0 == nullptr) {
+ // Verify IAGnssRil 1.0 is not supported.
+ auto agnssRil_1_0 = gnss_hal_->getExtensionAGnssRil();
+ ASSERT_TRUE(agnssRil_1_0.isOk());
+ sp<IAGnssRil_1_0> iAGnssRil_1_0 = agnssRil_1_0;
+ ASSERT_EQ(iAGnssRil_1_0, nullptr);
+ }
}
/*
@@ -146,7 +152,9 @@
auto agnssRil = gnss_hal_->getExtensionAGnssRil_2_0();
ASSERT_TRUE(agnssRil.isOk());
sp<IAGnssRil_2_0> iAGnssRil = agnssRil;
- ASSERT_NE(iAGnssRil, nullptr);
+ if (iAGnssRil == nullptr) {
+ return;
+ }
// Update GNSS HAL that a network has connected.
IAGnssRil_2_0::NetworkAttributes networkAttributes = {
@@ -191,10 +199,11 @@
ASSERT_TRUE(result.isOk());
EXPECT_EQ(result, IGnssMeasurement_1_0::GnssMeasurementStatus::SUCCESS);
- wait(kFirstGnssMeasurementTimeoutSeconds);
- EXPECT_EQ(measurement_called_count_, 1);
- ASSERT_TRUE(last_measurement_.measurements.size() > 0);
- for (auto measurement : last_measurement_.measurements) {
+ IGnssMeasurementCallback_2_0::GnssData lastMeasurement;
+ ASSERT_TRUE(measurement_cbq_.retrieve(lastMeasurement, kFirstGnssMeasurementTimeoutSeconds));
+ EXPECT_EQ(measurement_cbq_.calledCount(), 1);
+ ASSERT_TRUE(lastMeasurement.measurements.size() > 0);
+ for (auto measurement : lastMeasurement.measurements) {
// Verify CodeType is valid.
ASSERT_NE(measurement.codeType, "");
@@ -219,44 +228,35 @@
/*
* TestAGnssExtension:
- * Gets the AGnssExtension and verifies that it supports @2.0::IAGnss interface by invoking
- * a method.
+ * Gets the AGnssExtension and verifies that it returns an actual extension.
*
- * The GNSS HAL 2.0 implementation must support @2.0::IAGnss interface due to the deprecation
- * of framework network API methods needed to support the @1.0::IAGnss interface.
- *
- * TODO (b/121287858): Enforce gnss@2.0 HAL package is supported on devices launched with Q or later
+ * If IAGnss interface is supported, then the GNSS HAL 2.0 implementation must support
+ * @2.0::IAGnss interface due to the deprecation of framework network API methods needed
+ * to support the @1.0::IAGnss interface.
*/
TEST_F(GnssHalTest, TestAGnssExtension) {
- // Verify IAGnss 2.0 is supported.
- auto agnss = gnss_hal_->getExtensionAGnss_2_0();
- ASSERT_TRUE(agnss.isOk());
- sp<IAGnss_2_0> iAGnss = agnss;
- ASSERT_NE(iAGnss, nullptr);
+ auto agnss_2_0 = gnss_hal_->getExtensionAGnss_2_0();
+ ASSERT_TRUE(agnss_2_0.isOk());
+ sp<IAGnss_2_0> iAGnss_2_0 = agnss_2_0;
+ if (iAGnss_2_0 == nullptr) {
+ // Verify IAGnss 1.0 is not supported.
+ auto agnss_1_0 = gnss_hal_->getExtensionAGnss();
+ ASSERT_TRUE(agnss_1_0.isOk());
+ sp<IAGnss_1_0> iAGnss_1_0 = agnss_1_0;
+ ASSERT_EQ(iAGnss_1_0, nullptr);
+ return;
+ }
// Set SUPL server host/port
- auto result = iAGnss->setServer(IAGnssCallback_2_0::AGnssType::SUPL, "supl.google.com", 7275);
+ auto result =
+ iAGnss_2_0->setServer(IAGnssCallback_2_0::AGnssType::SUPL, "supl.google.com", 7275);
ASSERT_TRUE(result.isOk());
EXPECT_TRUE(result);
}
/*
- * TestAGnssExtension_1_0_Deprecation:
- * Gets the @1.0::IAGnss extension and verifies that it is a nullptr.
- *
- * TODO (b/121287858): Enforce gnss@2.0 HAL package is supported on devices launched with Q or later
- */
-TEST_F(GnssHalTest, TestAGnssExtension_1_0_Deprecation) {
- // Verify IAGnss 1.0 is not supported.
- auto agnss_1_0 = gnss_hal_->getExtensionAGnss();
- ASSERT_TRUE(!agnss_1_0.isOk() || ((sp<IAGnss_1_0>)agnss_1_0) == nullptr);
-}
-
-/*
* TestGnssNiExtension_Deprecation:
* Gets the @1.0::IGnssNi extension and verifies that it is a nullptr.
- *
- * TODO (b/121287858): Enforce gnss@2.0 HAL package is supported on devices launched with Q or later
*/
TEST_F(GnssHalTest, TestGnssNiExtension_Deprecation) {
// Verify IGnssNi 1.0 is not supported.
@@ -266,22 +266,19 @@
/*
* TestGnssVisibilityControlExtension:
- * Gets the GnssVisibilityControlExtension and verifies that it supports the
- * gnss.visibility_control@1.0::IGnssVisibilityControl interface by invoking a method.
- *
- * The GNSS HAL 2.0 implementation must support gnss.visibility_control@1.0::IGnssVisibilityControl.
- *
- * TODO (b/121287858): Enforce gnss@2.0 HAL package is supported on devices launched with Q or later
+ * Gets the GnssVisibilityControlExtension and if it is not null, verifies that it supports
+ * the gnss.visibility_control@1.0::IGnssVisibilityControl interface by invoking a method.
*/
TEST_F(GnssHalTest, TestGnssVisibilityControlExtension) {
- // Verify IGnssVisibilityControl is supported.
auto gnssVisibilityControl = gnss_hal_->getExtensionVisibilityControl();
ASSERT_TRUE(gnssVisibilityControl.isOk());
sp<IGnssVisibilityControl> iGnssVisibilityControl = gnssVisibilityControl;
- ASSERT_NE(iGnssVisibilityControl, nullptr);
+ if (iGnssVisibilityControl == nullptr) {
+ return;
+ }
// Set non-framework proxy apps.
- hidl_vec<hidl_string> proxyApps{"ims.example.com", "mdt.example.com"};
+ hidl_vec<hidl_string> proxyApps{"com.example.ims", "com.example.mdt"};
auto result = iGnssVisibilityControl->enableNfwLocationAccess(proxyApps);
ASSERT_TRUE(result.isOk());
EXPECT_TRUE(result);
@@ -309,8 +306,10 @@
iMeasurementCorrections->setCallback(iMeasurementCorrectionsCallback);
const int kMeasurementCorrectionsCapabilitiesTimeoutSeconds = 5;
- waitForMeasurementCorrectionsCapabilities(kMeasurementCorrectionsCapabilitiesTimeoutSeconds);
- ASSERT_TRUE(measurement_corrections_capabilities_called_count_ > 0);
+ measurement_corrections_capabilities_cbq_.retrieve(
+ last_measurement_corrections_capabilities_,
+ kMeasurementCorrectionsCapabilitiesTimeoutSeconds);
+ ASSERT_TRUE(measurement_corrections_capabilities_cbq_.calledCount() > 0);
using Capabilities = IMeasurementCorrectionsCallback::Capabilities;
ASSERT_TRUE((last_measurement_corrections_capabilities_ &
(Capabilities::LOS_SATS | Capabilities::EXCESS_PATH_LENGTH)) != 0);
@@ -337,8 +336,11 @@
iMeasurementCorrections->setCallback(iMeasurementCorrectionsCallback);
const int kMeasurementCorrectionsCapabilitiesTimeoutSeconds = 5;
- waitForMeasurementCorrectionsCapabilities(kMeasurementCorrectionsCapabilitiesTimeoutSeconds);
- ASSERT_TRUE(measurement_corrections_capabilities_called_count_ > 0);
+ measurement_corrections_capabilities_cbq_.retrieve(
+ last_measurement_corrections_capabilities_,
+ kMeasurementCorrectionsCapabilitiesTimeoutSeconds);
+ ASSERT_TRUE(measurement_corrections_capabilities_cbq_.calledCount() > 0);
+
// Set a mock MeasurementCorrections.
auto result = iMeasurementCorrections->setCorrections(Utils::getMockMeasurementCorrections());
ASSERT_TRUE(result.isOk());
@@ -369,16 +371,17 @@
ASSERT_TRUE(result.isOk());
EXPECT_EQ(result, IGnssMeasurement_1_0::GnssMeasurementStatus::SUCCESS);
- wait(kFirstGnssMeasurementTimeoutSeconds);
- EXPECT_EQ(measurement_called_count_, 1);
+ IGnssMeasurementCallback_2_0::GnssData lastMeasurement;
+ ASSERT_TRUE(measurement_cbq_.retrieve(lastMeasurement, kFirstGnssMeasurementTimeoutSeconds));
+ EXPECT_EQ(measurement_cbq_.calledCount(), 1);
- ASSERT_TRUE((int)last_measurement_.elapsedRealtime.flags <=
+ ASSERT_TRUE((int)lastMeasurement.elapsedRealtime.flags <=
(int)(ElapsedRealtimeFlags::HAS_TIMESTAMP_NS |
ElapsedRealtimeFlags::HAS_TIME_UNCERTAINTY_NS));
// We expect a non-zero timestamp when set.
- if (last_measurement_.elapsedRealtime.flags & ElapsedRealtimeFlags::HAS_TIMESTAMP_NS) {
- ASSERT_TRUE(last_measurement_.elapsedRealtime.timestampNs != 0);
+ if (lastMeasurement.elapsedRealtime.flags & ElapsedRealtimeFlags::HAS_TIMESTAMP_NS) {
+ ASSERT_TRUE(lastMeasurement.elapsedRealtime.timestampNs != 0);
}
iGnssMeasurement->close();
@@ -408,17 +411,10 @@
/*
* TestGnssBatchingExtension:
- * Gets the GnssBatchingExtension and verifies that it supports either the @1.0::IGnssBatching
- * or @2.0::IGnssBatching extension.
+ * Gets the @2.0::IGnssBatching extension and verifies that it doesn't return an error. Support
+ * for this interface is optional.
*/
TEST_F(GnssHalTest, TestGnssBatchingExtension) {
- auto gnssBatching_V2_0 = gnss_hal_->getExtensionGnssBatching_2_0();
- ASSERT_TRUE(gnssBatching_V2_0.isOk());
-
- auto gnssBatching_V1_0 = gnss_hal_->getExtensionGnssBatching();
- ASSERT_TRUE(gnssBatching_V1_0.isOk());
-
- sp<IGnssBatching_V1_0> iGnssBatching_V1_0 = gnssBatching_V1_0;
- sp<IGnssBatching_V2_0> iGnssBatching_V2_0 = gnssBatching_V2_0;
- ASSERT_TRUE(iGnssBatching_V1_0 != nullptr || iGnssBatching_V2_0 != nullptr);
+ auto gnssBatching_2_0 = gnss_hal_->getExtensionGnssBatching_2_0();
+ ASSERT_TRUE(gnssBatching_2_0.isOk());
}
diff --git a/keymaster/4.0/vts/functional/keymaster_hidl_hal_test.cpp b/keymaster/4.0/vts/functional/keymaster_hidl_hal_test.cpp
index fc96724..3d37e9f 100644
--- a/keymaster/4.0/vts/functional/keymaster_hidl_hal_test.cpp
+++ b/keymaster/4.0/vts/functional/keymaster_hidl_hal_test.cpp
@@ -371,7 +371,7 @@
strptime(date.c_str(), "%Y-%m-%d", &time);
// Day of the month (0-31)
- EXPECT_GT(time.tm_mday, 0);
+ EXPECT_GE(time.tm_mday, 0);
EXPECT_LT(time.tm_mday, 32);
// Months since Jan (0-11)
EXPECT_GE(time.tm_mon, 0);
@@ -414,7 +414,7 @@
EXPECT_NE(strcmp(property_value, "nogood"), 0);
string prop_string(property_value);
EXPECT_EQ(prop_string.size(), 64);
- EXPECT_EQ(0, memcmp(verified_boot_hash.data(), prop_string.data(), verified_boot_hash.size()));
+ EXPECT_EQ(prop_string, bin2hex(verified_boot_hash));
property_get("ro.boot.vbmeta.device_state", property_value, "nogood");
EXPECT_NE(property_value, "nogood");
diff --git a/neuralnetworks/1.0/types.hal b/neuralnetworks/1.0/types.hal
index 89af35a..b0a1c1a 100644
--- a/neuralnetworks/1.0/types.hal
+++ b/neuralnetworks/1.0/types.hal
@@ -1197,6 +1197,11 @@
* shape of the output tensor. The number of elements implied by shape
* must be the same as the number of elements in the input tensor.
*
+ * If one component of shape is the special value -1, the size of that
+ * dimension is computed so that the total size remains constant. In
+ * particular, a shape of [-1] flattens into 1-D. At most one component
+ * of shape can be -1.
+ *
* Outputs:
* * 0: The output tensor, of shape specified by the input shape.
*
@@ -1220,9 +1225,9 @@
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* * 1: An {@link OperandType::INT32} scalar, specifying the output
- * height of the output tensor.
- * * 2: An {@link OperandType::INT32} scalar, specifying the output
* width of the output tensor.
+ * * 2: An {@link OperandType::INT32} scalar, specifying the output
+ * height of the output tensor.
*
* Outputs:
* * 0: The output 4-D tensor, of shape
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
index 8883057..31638c4 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
@@ -68,6 +68,11 @@
::testing::VtsHalHidlTargetTestBase::TearDown();
}
+void ValidationTest::validateEverything(const Model& model, const std::vector<Request>& request) {
+ validateModel(model);
+ validateRequests(model, request);
+}
+
} // namespace functional
} // namespace vts
} // namespace V1_0
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
index d4c114d..559d678 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
@@ -63,8 +63,11 @@
// Tag for the validation tests
class ValidationTest : public NeuralnetworksHidlTest {
protected:
- void validateModel(const Model& model);
- void validateRequests(const Model& model, const std::vector<Request>& request);
+ void validateEverything(const Model& model, const std::vector<Request>& request);
+
+ private:
+ void validateModel(const Model& model);
+ void validateRequests(const Model& model, const std::vector<Request>& request);
};
// Tag for the generated tests
diff --git a/neuralnetworks/1.1/types.hal b/neuralnetworks/1.1/types.hal
index 99f873a..73705bb 100644
--- a/neuralnetworks/1.1/types.hal
+++ b/neuralnetworks/1.1/types.hal
@@ -104,9 +104,6 @@
* in axis. If keep_dims is true, the reduced dimensions are retained with
* length 1.
*
- * If dimensions to reduce have no entries, all dimensions are reduced, and
- * a tensor with a single element is returned.
- *
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT32}
* * {@link OperandType::TENSOR_QUANT8_ASYMM}
@@ -116,8 +113,14 @@
* Inputs:
* * 0: A tensor, specifying the input.
* * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}. The dimensions
- * to reduce. If None (the default), reduces all dimensions. Must be in
- * the range [-rank(input_tensor), rank(input_tensor)).
+ * to reduce. Must be in the range
+ * [-rank(input_tensor), rank(input_tensor)).
+ *
+ * NOTE: When the operation was introduced, the documentation
+ * incorrectly stated that if dimensions were empty, the operation
+ * would reduce across all dimensions. This behavior was never
+ * implemented.
+ *
* * 2: An {@link OperandType::INT32} scalar, keep_dims. If positive,
* retains reduced dimensions with length 1.
*
@@ -135,7 +138,7 @@
*
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT32}
- * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+ * * {@link OperandType::TENSOR_QUANT8_ASYMM} (the pad value is undefined)
*
* Supported tensor rank: up to 4
*
@@ -158,6 +161,9 @@
* output0.dimension[i] =
* padding[i, 0] + input0.dimension[i] + padding[i, 1]
*
+ * NOTE: The pad value for {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM}
+ * is undefined.
+ *
* Available since API level 28.
*/
PAD = 32,
diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
index 224a51d..11fa693 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
@@ -68,6 +68,11 @@
::testing::VtsHalHidlTargetTestBase::TearDown();
}
+void ValidationTest::validateEverything(const Model& model, const std::vector<Request>& request) {
+ validateModel(model);
+ validateRequests(model, request);
+}
+
} // namespace functional
} // namespace vts
} // namespace V1_1
diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
index 1c8c0e1..cea2b54 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
@@ -72,8 +72,11 @@
// Tag for the validation tests
class ValidationTest : public NeuralnetworksHidlTest {
protected:
- void validateModel(const Model& model);
- void validateRequests(const Model& model, const std::vector<Request>& request);
+ void validateEverything(const Model& model, const std::vector<Request>& request);
+
+ private:
+ void validateModel(const Model& model);
+ void validateRequests(const Model& model, const std::vector<Request>& request);
};
// Tag for the generated tests
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 839114f..c2e8f22 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -1005,12 +1005,21 @@
* the input.
* * 1: An {@link OperandType::INT32} scalar, specifying the radius of
* the normalization window.
- * * 2: An {@link OperandType::FLOAT32} scalar, specifying the bias, must
- * not be zero.
- * * 3: An {@link OperandType::FLOAT32} scalar, specifying the scale
- * factor, alpha.
- * * 4: An {@link OperandType::FLOAT32} scalar, specifying the exponent,
- * beta.
+ * * 2: A scalar, specifying the bias, must not be zero.
+ * For input tensor of {@link OperandType::TENSOR_FLOAT16}, the bias
+ * value must be of {@link OperandType::FLOAT16}.
+ * For input tensor of {@link OperandType::TENSOR_FLOAT32}, the bias
+ * value must be of {@link OperandType::FLOAT32}.
+ * * 3: A scalar, specifying the scale factor, alpha.
+ * For input tensor of {@link OperandType::TENSOR_FLOAT16}, the alpha
+ * value must be of {@link OperandType::FLOAT16}.
+ * For input tensor of {@link OperandType::TENSOR_FLOAT32}, the alpha
+ * value must be of {@link OperandType::FLOAT32}.
+ * * 4: A scalar, specifying the exponent, beta.
+ * For input tensor of {@link OperandType::TENSOR_FLOAT16}, the beta
+ * value must be of {@link OperandType::FLOAT16}.
+ * For input tensor of {@link OperandType::TENSOR_FLOAT32}, the beta
+ * value must be of {@link OperandType::FLOAT32}.
* * 5: An optional {@link OperandType::INT32} scalar, default to -1,
* specifying the dimension normalization would be performed on.
* Negative index is used to specify axis from the end (e.g. -1 for
@@ -1548,6 +1557,11 @@
* shape of the output tensor. The number of elements implied by shape
* must be the same as the number of elements in the input tensor.
*
+ * If one component of shape is the special value -1, the size of that
+ * dimension is computed so that the total size remains constant. In
+ * particular, a shape of [-1] flattens into 1-D. At most one component
+ * of shape can be -1.
+ *
* Outputs:
* * 0: The output tensor, of shape specified by the input shape.
*
@@ -1579,9 +1593,9 @@
* the input. Since API level 29, zero batches is supported for this
* tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the output
- * height of the output tensor.
- * * 2: An {@link OperandType::INT32} scalar, specifying the output
* width of the output tensor.
+ * * 2: An {@link OperandType::INT32} scalar, specifying the output
+ * height of the output tensor.
* * 3: An optional {@link OperandType::BOOL} scalar, default to false.
* Set to true to specify NCHW data layout for input0 and output0.
* Available since API level 29.
@@ -1589,15 +1603,15 @@
* Inputs (resizing by scale, since API level 29):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input. Zero batches is supported for this tensor.
- * * 1: A scalar, specifying height_scale, the scaling factor of the height
+ * * 1: A scalar, specifying width_scale, the scaling factor of the width
* dimension from the input tensor to the output tensor. The output
- * height is calculated as new_height = floor(height * height_scale).
+ * width is calculated as new_width = floor(width * width_scale).
* The scalar must be of {@link OperandType::FLOAT16} if input0 is
* of {@link OperandType::TENSOR_FLOAT16} and of
* {@link OperandType::FLOAT32} otherwise.
- * * 2: A scalar, specifying width_scale, the scaling factor of the width
+ * * 2: A scalar, specifying height_scale, the scaling factor of the height
* dimension from the input tensor to the output tensor. The output
- * width is calculated as new_width = floor(width * width_scale).
+ * height is calculated as new_height = floor(height * height_scale).
* The scalar must be of {@link OperandType::FLOAT16} if input0 is
* of {@link OperandType::TENSOR_FLOAT16} and of
* {@link OperandType::FLOAT32} otherwise.
@@ -1949,9 +1963,6 @@
* in axis. If keep_dims is true, the reduced dimensions are retained with
* length 1.
*
- * If dimensions to reduce have no entries, all dimensions are reduced, and
- * a tensor with a single element is returned.
- *
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT16} (since API level 29)
* * {@link OperandType::TENSOR_FLOAT32}
@@ -1962,8 +1973,14 @@
* Inputs:
* * 0: A tensor, specifying the input.
* * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}. The dimensions
- * to reduce. If None (the default), reduces all dimensions. Must be in
- * the range [-rank(input_tensor), rank(input_tensor)).
+ * to reduce. Must be in the range
+ * [-rank(input_tensor), rank(input_tensor)).
+ *
+ * NOTE: When the operation was introduced, the documentation
+ * incorrectly stated that if dimensions were empty, the operation
+ * would reduce across all dimensions. This behavior was never
+ * implemented.
+ *
* * 2: An {@link OperandType::INT32} scalar, keep_dims. If positive,
* retains reduced dimensions with length 1.
*
@@ -1982,7 +1999,8 @@
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT16} (since API level 29)
* * {@link OperandType::TENSOR_FLOAT32}
- * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+ * * {@link OperandType::TENSOR_QUANT8_ASYMM} (full support since API
+ * level 29, see the output section)
*
* Supported tensor rank: up to 4
*
@@ -2005,6 +2023,10 @@
* output0.dimension[i] =
* padding[i, 0] + input0.dimension[i] + padding[i, 1]
*
+ * NOTE: Before API level 29, the pad value for
+ * {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM} is undefined.
+ * Since API level 29, the pad value is always the logical zero.
+ *
* Available since API level 28.
*/
PAD = @1.1::OperationType:PAD,
@@ -3487,8 +3509,12 @@
*
* Inputs:
* * 0: A tensor specifying the input logits.
- * * 1: An {@link OperandType::FLOAT32} scalar, specifying the positive
- * scaling factor for the exponent, beta.
+ * * 1: A scalar, specifying the positive scaling factor for the exponent,
+ * beta.
+ * For input tensor of {@link OperandType::TENSOR_FLOAT16}, the beta
+ * value must be of {@link OperandType::FLOAT16}.
+ * For input tensor of {@link OperandType::TENSOR_FLOAT32}, the beta
+ * value must be of {@link OperandType::FLOAT32}.
* * 2: An {@link OperandType::INT32} scalar specifying the axis to
* reduce across. Negative index is used to specify axis from the
* end (e.g. -1 for the last axis). Must be in the range [-n, n).
@@ -3510,6 +3536,8 @@
* * {@link OperandType::TENSOR_INT32}
* * {@link OperandType::TENSOR_QUANT8_ASYMM}
*
+ * Supported tensor rank: from 1.
+ *
* Inputs:
* * 0: A tensor.
* * 1: A tensor of the same {@link OperandType} and compatible dimensions
@@ -3531,6 +3559,8 @@
* * {@link OperandType::TENSOR_INT32}
* * {@link OperandType::TENSOR_QUANT8_ASYMM}
*
+ * Supported tensor rank: from 1.
+ *
* Inputs:
* * 0: A tensor.
* * 1: A tensor of the same {@link OperandType} and compatible dimensions
@@ -4638,24 +4668,24 @@
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input. Zero batches is supported for this tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the output
- * height of the output tensor.
- * * 2: An {@link OperandType::INT32} scalar, specifying the output
* width of the output tensor.
+ * * 2: An {@link OperandType::INT32} scalar, specifying the output
+ * height of the output tensor.
* * 3: An {@link OperandType::BOOL} scalar, default to false.
* Set to true to specify NCHW data layout for input0 and output0.
*
* Inputs (resizing by scale):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input. Zero batches is supported for this tensor.
- * * 1: A scalar, specifying height_scale, the scaling factor of the height
+ * * 1: A scalar, specifying width_scale, the scaling factor of the width
* dimension from the input tensor to the output tensor. The output
- * height is calculated as new_height = floor(height * height_scale).
+ * width is calculated as new_width = floor(width * width_scale).
* The scalar must be of {@link OperandType::FLOAT16} if input0 is
* of {@link OperandType::TENSOR_FLOAT16} and of
* {@link OperandType::FLOAT32} otherwise.
- * * 2: A scalar, specifying width_scale, the scaling factor of the width
+ * * 2: A scalar, specifying height_scale, the scaling factor of the height
* dimension from the input tensor to the output tensor. The output
- * width is calculated as new_width = floor(width * width_scale).
+ * height is calculated as new_height = floor(height * height_scale).
* The scalar must be of {@link OperandType::FLOAT16} if input0 is
* of {@link OperandType::TENSOR_FLOAT16} and of
* {@link OperandType::FLOAT32} otherwise.
diff --git a/neuralnetworks/1.2/vts/functional/Android.bp b/neuralnetworks/1.2/vts/functional/Android.bp
index 891b414..6c26820 100644
--- a/neuralnetworks/1.2/vts/functional/Android.bp
+++ b/neuralnetworks/1.2/vts/functional/Android.bp
@@ -20,6 +20,7 @@
defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
srcs: [
"GeneratedTestsV1_0.cpp",
+ "ValidateBurst.cpp",
],
cflags: [
"-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
@@ -32,6 +33,7 @@
defaults: ["VtsHalNeuralNetworksTargetTestDefaults"],
srcs: [
"GeneratedTestsV1_1.cpp",
+ "ValidateBurst.cpp",
],
cflags: [
"-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
@@ -46,6 +48,7 @@
"BasicTests.cpp",
"CompilationCachingTests.cpp",
"GeneratedTests.cpp",
+ "ValidateBurst.cpp",
],
cflags: [
"-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
@@ -58,6 +61,7 @@
srcs: [
"BasicTests.cpp",
"GeneratedTests.cpp",
+ "ValidateBurst.cpp",
],
cflags: [
"-DNN_TEST_DYNAMIC_OUTPUT_SHAPE",
diff --git a/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp b/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
index 167fc09..bf91560 100644
--- a/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
+++ b/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
@@ -16,21 +16,22 @@
#define LOG_TAG "neuralnetworks_hidl_hal_test"
-#include "VtsHalNeuralnetworks.h"
+#include <android-base/logging.h>
+#include <android/hidl/memory/1.0/IMemory.h>
+#include <ftw.h>
+#include <gtest/gtest.h>
+#include <hidlmemory/mapping.h>
+#include <unistd.h>
+
+#include <cstdio>
+#include <cstdlib>
+#include <random>
#include "Callbacks.h"
#include "GeneratedTestHarness.h"
#include "TestHarness.h"
#include "Utils.h"
-
-#include <android-base/logging.h>
-#include <android/hidl/memory/1.0/IMemory.h>
-#include <hidlmemory/mapping.h>
-#include <cstdio>
-#include <cstdlib>
-#include <random>
-
-#include <gtest/gtest.h>
+#include "VtsHalNeuralnetworks.h"
namespace android {
namespace hardware {
@@ -46,7 +47,7 @@
namespace {
-// In frameworks/ml/nn/runtime/tests/generated/, creates a hidl model of mobilenet.
+// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of mobilenet.
#include "examples/mobilenet_224_gender_basic_fixed.example.cpp"
#include "vts_models/mobilenet_224_gender_basic_fixed.model.cpp"
@@ -89,6 +90,118 @@
createCacheHandles(fileGroups, std::vector<AccessMode>(fileGroups.size(), mode), handles);
}
+// Create a chain of broadcast operations. The second operand is always constant tensor [1].
+// For simplicity, activation scalar is shared. The second operand is not shared
+// in the model to let driver maintain a non-trivial size of constant data and the corresponding
+// data locations in cache.
+//
+// --------- activation --------
+// ↓ ↓ ↓ ↓
+// E.g. input -> ADD -> ADD -> ADD -> ... -> ADD -> output
+// ↑ ↑ ↑ ↑
+// [1] [1] [1] [1]
+//
+Model createLargeTestModel(OperationType op, uint32_t len) {
+ // Model operations and operands.
+ std::vector<Operation> operations(len);
+ std::vector<Operand> operands(len * 2 + 2);
+
+ // The constant buffer pool. This contains the activation scalar, followed by the
+ // per-operation constant operands.
+ std::vector<uint8_t> operandValues(sizeof(int32_t) + len * sizeof(float));
+
+ // The activation scalar, value = 0.
+ operands[0] = {
+ .type = OperandType::INT32,
+ .dimensions = {},
+ .numberOfConsumers = len,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .lifetime = OperandLifeTime::CONSTANT_COPY,
+ .location = {.poolIndex = 0, .offset = 0, .length = sizeof(int32_t)},
+ };
+ memset(operandValues.data(), 0, sizeof(int32_t));
+
+ const float floatBufferValue = 1.0f;
+ for (uint32_t i = 0; i < len; i++) {
+ const uint32_t firstInputIndex = i * 2 + 1;
+ const uint32_t secondInputIndex = firstInputIndex + 1;
+ const uint32_t outputIndex = secondInputIndex + 1;
+
+ // The first operation input.
+ operands[firstInputIndex] = {
+ .type = OperandType::TENSOR_FLOAT32,
+ .dimensions = {1},
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .lifetime = (i == 0 ? OperandLifeTime::MODEL_INPUT
+ : OperandLifeTime::TEMPORARY_VARIABLE),
+ .location = {},
+ };
+
+ // The second operation input, value = 1.
+ operands[secondInputIndex] = {
+ .type = OperandType::TENSOR_FLOAT32,
+ .dimensions = {1},
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .lifetime = OperandLifeTime::CONSTANT_COPY,
+ .location = {.poolIndex = 0,
+ .offset = static_cast<uint32_t>(i * sizeof(float) + sizeof(int32_t)),
+ .length = sizeof(float)},
+ };
+ memcpy(operandValues.data() + sizeof(int32_t) + i * sizeof(float), &floatBufferValue,
+ sizeof(float));
+
+ // The operation. All operations share the same activation scalar.
+ // The output operand is created as an input in the next iteration of the loop, in the case
+ // of all but the last member of the chain; and after the loop as a model output, in the
+ // case of the last member of the chain.
+ operations[i] = {
+ .type = op,
+ .inputs = {firstInputIndex, secondInputIndex, /*activation scalar*/ 0},
+ .outputs = {outputIndex},
+ };
+ }
+
+ // The model output.
+ operands.back() = {
+ .type = OperandType::TENSOR_FLOAT32,
+ .dimensions = {1},
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .lifetime = OperandLifeTime::MODEL_OUTPUT,
+ .location = {},
+ };
+
+ const std::vector<uint32_t> inputIndexes = {1};
+ const std::vector<uint32_t> outputIndexes = {len * 2 + 1};
+ const std::vector<hidl_memory> pools = {};
+
+ return {
+ .operands = operands,
+ .operations = operations,
+ .inputIndexes = inputIndexes,
+ .outputIndexes = outputIndexes,
+ .operandValues = operandValues,
+ .pools = pools,
+ };
+}
+
+// MixedTypedExample is defined in frameworks/ml/nn/tools/test_generator/include/TestHarness.h.
+// This function assumes the operation is always ADD.
+std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
+ float outputValue = 1.0f + static_cast<float>(len);
+ return {{.operands = {
+ // Input
+ {.operandDimensions = {{0, {1}}}, .float32Operands = {{0, {1.0f}}}},
+ // Output
+ {.operandDimensions = {{0, {1}}}, .float32Operands = {{0, {outputValue}}}}}}};
+};
+
} // namespace
// Tag for the compilation caching tests.
@@ -139,21 +252,19 @@
}
void TearDown() override {
- // The tmp directory is only removed when the driver reports caching not supported,
- // otherwise it is kept for debugging purpose.
- if (!mIsCachingSupported) {
- remove(mTmpCache.c_str());
- rmdir(mCacheDir.c_str());
+ // If the test passes, remove the tmp directory. Otherwise, keep it for debugging purposes.
+ if (!::testing::Test::HasFailure()) {
+ // Recursively remove the cache directory specified by mCacheDir.
+ auto callback = [](const char* entry, const struct stat*, int, struct FTW*) {
+ return remove(entry);
+ };
+ nftw(mCacheDir.c_str(), callback, 128, FTW_DEPTH | FTW_MOUNT | FTW_PHYS);
}
NeuralnetworksHidlTest::TearDown();
}
- void saveModelToCache(const V1_2::Model& model, const hidl_vec<hidl_handle>& modelCache,
- const hidl_vec<hidl_handle>& dataCache, bool* supported,
- sp<IPreparedModel>* preparedModel = nullptr) {
- if (preparedModel != nullptr) *preparedModel = nullptr;
-
- // See if service can handle model.
+ // See if the service can handle the model.
+ bool isModelFullySupported(const V1_2::Model& model) {
bool fullySupportsModel = false;
Return<void> supportedCall = device->getSupportedOperations_1_2(
model,
@@ -163,9 +274,14 @@
fullySupportsModel = std::all_of(supported.begin(), supported.end(),
[](bool valid) { return valid; });
});
- ASSERT_TRUE(supportedCall.isOk());
- *supported = fullySupportsModel;
- if (!fullySupportsModel) return;
+ EXPECT_TRUE(supportedCall.isOk());
+ return fullySupportsModel;
+ }
+
+ void saveModelToCache(const V1_2::Model& model, const hidl_vec<hidl_handle>& modelCache,
+ const hidl_vec<hidl_handle>& dataCache,
+ sp<IPreparedModel>* preparedModel = nullptr) {
+ if (preparedModel != nullptr) *preparedModel = nullptr;
// Launch prepare model.
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
@@ -199,8 +315,8 @@
return false;
}
- bool checkEarlyTermination(bool supported) {
- if (!supported) {
+ bool checkEarlyTermination(const V1_2::Model& model) {
+ if (!isModelFullySupported(model)) {
LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
"prepare model that it does not support.";
std::cout << "[ ] Early termination of test because vendor service cannot "
@@ -254,17 +370,16 @@
TEST_F(CompilationCachingTest, CacheSavingAndRetrieval) {
// Create test HIDL model and compile.
- Model testModel = createTestModel();
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
sp<IPreparedModel> preparedModel = nullptr;
// Save the compilation to cache.
{
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- saveModelToCache(testModel, modelCache, dataCache, &supported);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache);
}
// Retrieve preparedModel from cache.
@@ -296,12 +411,12 @@
TEST_F(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
// Create test HIDL model and compile.
- Model testModel = createTestModel();
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
sp<IPreparedModel> preparedModel = nullptr;
// Save the compilation to cache.
{
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
@@ -318,8 +433,7 @@
write(dataCache[i].getNativeHandle()->data[0], &dummyBytes, sizeof(dummyBytes)),
sizeof(dummyBytes));
}
- saveModelToCache(testModel, modelCache, dataCache, &supported);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache);
}
// Retrieve preparedModel from cache.
@@ -360,11 +474,11 @@
TEST_F(CompilationCachingTest, SaveToCacheInvalidNumCache) {
// Create test HIDL model and compile.
- Model testModel = createTestModel();
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
// Test with number of model cache files greater than mNumModelCache.
{
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
// Pass an additional cache file for model cache.
mModelCache.push_back({mTmpCache});
@@ -372,8 +486,7 @@
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
mModelCache.pop_back();
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -392,7 +505,6 @@
// Test with number of model cache files smaller than mNumModelCache.
if (mModelCache.size() > 0) {
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
// Pop out the last cache file.
auto tmp = mModelCache.back();
@@ -401,8 +513,7 @@
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
mModelCache.push_back(tmp);
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -421,7 +532,6 @@
// Test with number of data cache files greater than mNumDataCache.
{
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
// Pass an additional cache file for data cache.
mDataCache.push_back({mTmpCache});
@@ -429,8 +539,7 @@
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
mDataCache.pop_back();
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -449,7 +558,6 @@
// Test with number of data cache files smaller than mNumDataCache.
if (mDataCache.size() > 0) {
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
// Pop out the last cache file.
auto tmp = mDataCache.back();
@@ -458,8 +566,7 @@
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
mDataCache.push_back(tmp);
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -479,16 +586,15 @@
TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
// Create test HIDL model and compile.
- Model testModel = createTestModel();
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
// Save the compilation to cache.
{
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- saveModelToCache(testModel, modelCache, dataCache, &supported);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache);
}
// Test with number of model cache files greater than mNumModelCache.
@@ -560,11 +666,11 @@
TEST_F(CompilationCachingTest, SaveToCacheInvalidNumFd) {
// Create test HIDL model and compile.
- Model testModel = createTestModel();
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
// Go through each handle in model cache, test with NumFd greater than 1.
for (uint32_t i = 0; i < mNumModelCache; i++) {
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
// Pass an invalid number of fds for handle i.
mModelCache[i].push_back(mTmpCache);
@@ -572,8 +678,7 @@
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
mModelCache[i].pop_back();
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -592,7 +697,6 @@
// Go through each handle in model cache, test with NumFd equal to 0.
for (uint32_t i = 0; i < mNumModelCache; i++) {
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
// Pass an invalid number of fds for handle i.
auto tmp = mModelCache[i].back();
@@ -601,8 +705,7 @@
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
mModelCache[i].push_back(tmp);
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -621,7 +724,6 @@
// Go through each handle in data cache, test with NumFd greater than 1.
for (uint32_t i = 0; i < mNumDataCache; i++) {
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
// Pass an invalid number of fds for handle i.
mDataCache[i].push_back(mTmpCache);
@@ -629,8 +731,7 @@
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
mDataCache[i].pop_back();
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -649,7 +750,6 @@
// Go through each handle in data cache, test with NumFd equal to 0.
for (uint32_t i = 0; i < mNumDataCache; i++) {
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
// Pass an invalid number of fds for handle i.
auto tmp = mDataCache[i].back();
@@ -658,8 +758,7 @@
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
mDataCache[i].push_back(tmp);
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -679,16 +778,15 @@
TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidNumFd) {
// Create test HIDL model and compile.
- Model testModel = createTestModel();
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
// Save the compilation to cache.
{
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- saveModelToCache(testModel, modelCache, dataCache, &supported);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache);
}
// Go through each handle in model cache, test with NumFd greater than 1.
@@ -760,21 +858,20 @@
TEST_F(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
// Create test HIDL model and compile.
- Model testModel = createTestModel();
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
std::vector<AccessMode> modelCacheMode(mNumModelCache, AccessMode::READ_WRITE);
std::vector<AccessMode> dataCacheMode(mNumDataCache, AccessMode::READ_WRITE);
// Go through each handle in model cache, test with invalid access mode.
for (uint32_t i = 0; i < mNumModelCache; i++) {
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
modelCacheMode[i] = AccessMode::READ_ONLY;
createCacheHandles(mModelCache, modelCacheMode, &modelCache);
createCacheHandles(mDataCache, dataCacheMode, &dataCache);
modelCacheMode[i] = AccessMode::READ_WRITE;
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -793,15 +890,13 @@
// Go through each handle in data cache, test with invalid access mode.
for (uint32_t i = 0; i < mNumDataCache; i++) {
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
dataCacheMode[i] = AccessMode::READ_ONLY;
createCacheHandles(mModelCache, modelCacheMode, &modelCache);
createCacheHandles(mDataCache, dataCacheMode, &dataCache);
dataCacheMode[i] = AccessMode::READ_WRITE;
sp<IPreparedModel> preparedModel = nullptr;
- saveModelToCache(testModel, modelCache, dataCache, &supported, &preparedModel);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
generated_tests::EvaluatePreparedModel(preparedModel, [](int) { return false; },
@@ -821,18 +916,17 @@
TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
// Create test HIDL model and compile.
- Model testModel = createTestModel();
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
std::vector<AccessMode> modelCacheMode(mNumModelCache, AccessMode::READ_WRITE);
std::vector<AccessMode> dataCacheMode(mNumDataCache, AccessMode::READ_WRITE);
// Save the compilation to cache.
{
- bool supported;
hidl_vec<hidl_handle> modelCache, dataCache;
createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- saveModelToCache(testModel, modelCache, dataCache, &supported);
- if (checkEarlyTermination(supported)) return;
+ saveModelToCache(testModel, modelCache, dataCache);
}
// Go through each handle in model cache, test with invalid access mode.
@@ -864,6 +958,212 @@
}
}
+// Copy file contents between file groups.
+// The outer vector corresponds to handles and the inner vector is for fds held by each handle.
+// The outer vector sizes must match and the inner vectors must have size = 1.
+static void copyCacheFiles(const std::vector<std::vector<std::string>>& from,
+ const std::vector<std::vector<std::string>>& to) {
+ constexpr size_t kBufferSize = 1000000;
+ uint8_t buffer[kBufferSize];
+
+ ASSERT_EQ(from.size(), to.size());
+ for (uint32_t i = 0; i < from.size(); i++) {
+ ASSERT_EQ(from[i].size(), 1u);
+ ASSERT_EQ(to[i].size(), 1u);
+ int fromFd = open(from[i][0].c_str(), O_RDONLY);
+ int toFd = open(to[i][0].c_str(), O_WRONLY | O_CREAT, S_IRUSR | S_IWUSR);
+ ASSERT_GE(fromFd, 0);
+ ASSERT_GE(toFd, 0);
+
+ ssize_t readBytes;
+ while ((readBytes = read(fromFd, &buffer, kBufferSize)) > 0) {
+ ASSERT_EQ(write(toFd, &buffer, readBytes), readBytes);
+ }
+ ASSERT_GE(readBytes, 0);
+
+ close(fromFd);
+ close(toFd);
+ }
+}
+
+// Number of operations in the large test model.
+constexpr uint32_t kLargeModelSize = 100;
+constexpr uint32_t kNumIterationsTOCTOU = 100;
+
+TEST_F(CompilationCachingTest, SaveToCache_TOCTOU) {
+ if (!mIsCachingSupported) return;
+
+ // Create test models and check if fully supported by the service.
+ const Model testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+ if (checkEarlyTermination(testModelMul)) return;
+ const Model testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+ if (checkEarlyTermination(testModelAdd)) return;
+
+ // Save the testModelMul compilation to cache.
+ auto modelCacheMul = mModelCache;
+ for (auto& cache : modelCacheMul) {
+ cache[0].append("_mul");
+ }
+ {
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+ saveModelToCache(testModelMul, modelCache, dataCache);
+ }
+
+ // Use a different token for testModelAdd.
+ mToken[0]++;
+
+ // This test is probabilistic, so we run it multiple times.
+ for (uint32_t i = 0; i < kNumIterationsTOCTOU; i++) {
+ // Save the testModelAdd compilation to cache.
+ {
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+
+ // Spawn a thread to copy the cache content concurrently while saving to cache.
+ std::thread thread(copyCacheFiles, std::cref(modelCacheMul), std::cref(mModelCache));
+ saveModelToCache(testModelAdd, modelCache, dataCache);
+ thread.join();
+ }
+
+ // Retrieve preparedModel from cache.
+ {
+ sp<IPreparedModel> preparedModel = nullptr;
+ ErrorStatus status;
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+ prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+
+ // The preparation may fail or succeed, but must not crash. If the preparation succeeds,
+ // the prepared model must be executed with the correct result and not crash.
+ if (status != ErrorStatus::NONE) {
+ ASSERT_EQ(preparedModel, nullptr);
+ } else {
+ ASSERT_NE(preparedModel, nullptr);
+ generated_tests::EvaluatePreparedModel(
+ preparedModel, [](int) { return false; },
+ getLargeModelExamples(kLargeModelSize),
+ testModelAdd.relaxComputationFloat32toFloat16,
+ /*testDynamicOutputShape=*/false);
+ }
+ }
+ }
+}
+
+TEST_F(CompilationCachingTest, PrepareFromCache_TOCTOU) {
+ if (!mIsCachingSupported) return;
+
+ // Create test models and check if fully supported by the service.
+ const Model testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+ if (checkEarlyTermination(testModelMul)) return;
+ const Model testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+ if (checkEarlyTermination(testModelAdd)) return;
+
+ // Save the testModelMul compilation to cache.
+ auto modelCacheMul = mModelCache;
+ for (auto& cache : modelCacheMul) {
+ cache[0].append("_mul");
+ }
+ {
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+ saveModelToCache(testModelMul, modelCache, dataCache);
+ }
+
+ // Use a different token for testModelAdd.
+ mToken[0]++;
+
+ // This test is probabilistic, so we run it multiple times.
+ for (uint32_t i = 0; i < kNumIterationsTOCTOU; i++) {
+ // Save the testModelAdd compilation to cache.
+ {
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+ saveModelToCache(testModelAdd, modelCache, dataCache);
+ }
+
+ // Retrieve preparedModel from cache.
+ {
+ sp<IPreparedModel> preparedModel = nullptr;
+ ErrorStatus status;
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+
+ // Spawn a thread to copy the cache content concurrently while preparing from cache.
+ std::thread thread(copyCacheFiles, std::cref(modelCacheMul), std::cref(mModelCache));
+ prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+ thread.join();
+
+ // The preparation may fail or succeed, but must not crash. If the preparation succeeds,
+ // the prepared model must be executed with the correct result and not crash.
+ if (status != ErrorStatus::NONE) {
+ ASSERT_EQ(preparedModel, nullptr);
+ } else {
+ ASSERT_NE(preparedModel, nullptr);
+ generated_tests::EvaluatePreparedModel(
+ preparedModel, [](int) { return false; },
+ getLargeModelExamples(kLargeModelSize),
+ testModelAdd.relaxComputationFloat32toFloat16,
+ /*testDynamicOutputShape=*/false);
+ }
+ }
+ }
+}
+
+TEST_F(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
+ if (!mIsCachingSupported) return;
+
+ // Create test models and check if fully supported by the service.
+ const Model testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
+ if (checkEarlyTermination(testModelMul)) return;
+ const Model testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
+ if (checkEarlyTermination(testModelAdd)) return;
+
+ // Save the testModelMul compilation to cache.
+ auto modelCacheMul = mModelCache;
+ for (auto& cache : modelCacheMul) {
+ cache[0].append("_mul");
+ }
+ {
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+ saveModelToCache(testModelMul, modelCache, dataCache);
+ }
+
+ // Use a different token for testModelAdd.
+ mToken[0]++;
+
+ // Save the testModelAdd compilation to cache.
+ {
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+ saveModelToCache(testModelAdd, modelCache, dataCache);
+ }
+
+ // Replace the model cache of testModelAdd with testModelMul.
+ copyCacheFiles(modelCacheMul, mModelCache);
+
+ // Retrieve the preparedModel from cache, expect failure.
+ {
+ sp<IPreparedModel> preparedModel = nullptr;
+ ErrorStatus status;
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+ prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
+ ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+ ASSERT_EQ(preparedModel, nullptr);
+ }
+}
+
class CompilationCachingSecurityTest : public CompilationCachingTest,
public ::testing::WithParamInterface<uint32_t> {
protected:
@@ -879,34 +1179,15 @@
return dis(generator);
}
- const uint32_t kSeed = GetParam();
- std::mt19937 generator;
-};
-
-TEST_P(CompilationCachingSecurityTest, CorruptedSecuritySensitiveCache) {
- if (!mIsCachingSupported) return;
-
- // Create test HIDL model and compile.
- Model testModel = createTestModel();
-
- for (uint32_t i = 0; i < mNumModelCache; i++) {
- // Save the compilation to cache.
- {
- bool supported;
- hidl_vec<hidl_handle> modelCache, dataCache;
- createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
- createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- saveModelToCache(testModel, modelCache, dataCache, &supported);
- if (checkEarlyTermination(supported)) return;
- }
-
- // Randomly flip one single bit of the cache entry.
- FILE* pFile = fopen(mModelCache[i][0].c_str(), "r+");
+ // Randomly flip one single bit of the cache entry.
+ void flipOneBitOfCache(const std::string& filename, bool* skip) {
+ FILE* pFile = fopen(filename.c_str(), "r+");
ASSERT_EQ(fseek(pFile, 0, SEEK_END), 0);
long int fileSize = ftell(pFile);
if (fileSize == 0) {
fclose(pFile);
- continue;
+ *skip = true;
+ return;
}
ASSERT_EQ(fseek(pFile, getRandomInt(0l, fileSize - 1), SEEK_SET), 0);
int readByte = fgetc(pFile);
@@ -914,47 +1195,43 @@
ASSERT_EQ(fseek(pFile, -1, SEEK_CUR), 0);
ASSERT_NE(fputc(static_cast<uint8_t>(readByte) ^ (1U << getRandomInt(0, 7)), pFile), EOF);
fclose(pFile);
-
- // Retrieve preparedModel from cache, expect failure.
- {
- sp<IPreparedModel> preparedModel = nullptr;
- ErrorStatus status;
- hidl_vec<hidl_handle> modelCache, dataCache;
- createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
- createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
- ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
- ASSERT_EQ(preparedModel, nullptr);
- }
+ *skip = false;
}
-}
-TEST_P(CompilationCachingSecurityTest, WrongLengthSecuritySensitiveCache) {
- if (!mIsCachingSupported) return;
-
- // Create test HIDL model and compile.
- Model testModel = createTestModel();
-
- for (uint32_t i = 0; i < mNumModelCache; i++) {
- // Save the compilation to cache.
- {
- bool supported;
- hidl_vec<hidl_handle> modelCache, dataCache;
- createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
- createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- saveModelToCache(testModel, modelCache, dataCache, &supported);
- if (checkEarlyTermination(supported)) return;
- }
-
- // Randomly append bytes to the cache entry.
- FILE* pFile = fopen(mModelCache[i][0].c_str(), "a");
+ // Randomly append bytes to the cache entry.
+ void appendBytesToCache(const std::string& filename, bool* skip) {
+ FILE* pFile = fopen(filename.c_str(), "a");
uint32_t appendLength = getRandomInt(1, 256);
for (uint32_t i = 0; i < appendLength; i++) {
ASSERT_NE(fputc(getRandomInt<uint8_t>(0, 255), pFile), EOF);
}
fclose(pFile);
+ *skip = false;
+ }
- // Retrieve preparedModel from cache, expect failure.
+ enum class ExpectedResult { GENERAL_FAILURE, NOT_CRASH };
+
+ // Test if the driver behaves as expected when given corrupted cache or token.
+ // The modifier will be invoked after save to cache but before prepare from cache.
+ // The modifier accepts one pointer argument "skip" as the returning value, indicating
+ // whether the test should be skipped or not.
+ void testCorruptedCache(ExpectedResult expected, std::function<void(bool*)> modifier) {
+ const Model testModel = createTestModel();
+ if (checkEarlyTermination(testModel)) return;
+
+ // Save the compilation to cache.
+ {
+ hidl_vec<hidl_handle> modelCache, dataCache;
+ createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
+ createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
+ saveModelToCache(testModel, modelCache, dataCache);
+ }
+
+ bool skip = false;
+ modifier(&skip);
+ if (skip) return;
+
+ // Retrieve preparedModel from cache.
{
sp<IPreparedModel> preparedModel = nullptr;
ErrorStatus status;
@@ -962,43 +1239,66 @@
createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
- ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
- ASSERT_EQ(preparedModel, nullptr);
+
+ switch (expected) {
+ case ExpectedResult::GENERAL_FAILURE:
+ ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+ ASSERT_EQ(preparedModel, nullptr);
+ break;
+ case ExpectedResult::NOT_CRASH:
+ ASSERT_EQ(preparedModel == nullptr, status != ErrorStatus::NONE);
+ break;
+ default:
+ FAIL();
+ }
}
}
+
+ const uint32_t kSeed = GetParam();
+ std::mt19937 generator;
+};
+
+TEST_P(CompilationCachingSecurityTest, CorruptedModelCache) {
+ if (!mIsCachingSupported) return;
+ for (uint32_t i = 0; i < mNumModelCache; i++) {
+ testCorruptedCache(ExpectedResult::GENERAL_FAILURE,
+ [this, i](bool* skip) { flipOneBitOfCache(mModelCache[i][0], skip); });
+ }
+}
+
+TEST_P(CompilationCachingSecurityTest, WrongLengthModelCache) {
+ if (!mIsCachingSupported) return;
+ for (uint32_t i = 0; i < mNumModelCache; i++) {
+ testCorruptedCache(ExpectedResult::GENERAL_FAILURE,
+ [this, i](bool* skip) { appendBytesToCache(mModelCache[i][0], skip); });
+ }
+}
+
+TEST_P(CompilationCachingSecurityTest, CorruptedDataCache) {
+ if (!mIsCachingSupported) return;
+ for (uint32_t i = 0; i < mNumDataCache; i++) {
+ testCorruptedCache(ExpectedResult::NOT_CRASH,
+ [this, i](bool* skip) { flipOneBitOfCache(mDataCache[i][0], skip); });
+ }
+}
+
+TEST_P(CompilationCachingSecurityTest, WrongLengthDataCache) {
+ if (!mIsCachingSupported) return;
+ for (uint32_t i = 0; i < mNumDataCache; i++) {
+ testCorruptedCache(ExpectedResult::NOT_CRASH,
+ [this, i](bool* skip) { appendBytesToCache(mDataCache[i][0], skip); });
+ }
}
TEST_P(CompilationCachingSecurityTest, WrongToken) {
if (!mIsCachingSupported) return;
-
- // Create test HIDL model and compile.
- Model testModel = createTestModel();
-
- // Save the compilation to cache.
- {
- bool supported;
- hidl_vec<hidl_handle> modelCache, dataCache;
- createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
- createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- saveModelToCache(testModel, modelCache, dataCache, &supported);
- if (checkEarlyTermination(supported)) return;
- }
-
- // Randomly flip one single bit in mToken.
- uint32_t ind = getRandomInt(0u, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN) - 1);
- mToken[ind] ^= (1U << getRandomInt(0, 7));
-
- // Retrieve the preparedModel from cache, expect failure.
- {
- sp<IPreparedModel> preparedModel = nullptr;
- ErrorStatus status;
- hidl_vec<hidl_handle> modelCache, dataCache;
- createCacheHandles(mModelCache, AccessMode::READ_WRITE, &modelCache);
- createCacheHandles(mDataCache, AccessMode::READ_WRITE, &dataCache);
- prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
- ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
- ASSERT_EQ(preparedModel, nullptr);
- }
+ testCorruptedCache(ExpectedResult::GENERAL_FAILURE, [this](bool* skip) {
+ // Randomly flip one single bit in mToken.
+ uint32_t ind =
+ getRandomInt(0u, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN) - 1);
+ mToken[ind] ^= (1U << getRandomInt(0, 7));
+ *skip = false;
+ });
}
INSTANTIATE_TEST_CASE_P(TestCompilationCaching, CompilationCachingSecurityTest,
diff --git a/neuralnetworks/1.2/vts/functional/ValidateBurst.cpp b/neuralnetworks/1.2/vts/functional/ValidateBurst.cpp
new file mode 100644
index 0000000..386c141
--- /dev/null
+++ b/neuralnetworks/1.2/vts/functional/ValidateBurst.cpp
@@ -0,0 +1,333 @@
+/*
+ * Copyright (C) 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_hidl_hal_test"
+
+#include "VtsHalNeuralnetworks.h"
+
+#include "Callbacks.h"
+#include "ExecutionBurstController.h"
+#include "ExecutionBurstServer.h"
+#include "TestHarness.h"
+#include "Utils.h"
+
+#include <android-base/logging.h>
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+namespace V1_2 {
+namespace vts {
+namespace functional {
+
+using ::android::nn::ExecutionBurstController;
+using ::android::nn::RequestChannelSender;
+using ::android::nn::ResultChannelReceiver;
+using ExecutionBurstCallback = ::android::nn::ExecutionBurstController::ExecutionBurstCallback;
+
+constexpr size_t kExecutionBurstChannelLength = 1024;
+constexpr size_t kExecutionBurstChannelSmallLength = 8;
+
+///////////////////////// UTILITY FUNCTIONS /////////////////////////
+
+static bool badTiming(Timing timing) {
+ return timing.timeOnDevice == UINT64_MAX && timing.timeInDriver == UINT64_MAX;
+}
+
+static void createBurst(const sp<IPreparedModel>& preparedModel, const sp<IBurstCallback>& callback,
+ std::unique_ptr<RequestChannelSender>* sender,
+ std::unique_ptr<ResultChannelReceiver>* receiver,
+ sp<IBurstContext>* context) {
+ ASSERT_NE(nullptr, preparedModel.get());
+ ASSERT_NE(nullptr, sender);
+ ASSERT_NE(nullptr, receiver);
+ ASSERT_NE(nullptr, context);
+
+ // create FMQ objects
+ auto [fmqRequestChannel, fmqRequestDescriptor] =
+ RequestChannelSender::create(kExecutionBurstChannelLength, /*blocking=*/true);
+ auto [fmqResultChannel, fmqResultDescriptor] =
+ ResultChannelReceiver::create(kExecutionBurstChannelLength, /*blocking=*/true);
+ ASSERT_NE(nullptr, fmqRequestChannel.get());
+ ASSERT_NE(nullptr, fmqResultChannel.get());
+ ASSERT_NE(nullptr, fmqRequestDescriptor);
+ ASSERT_NE(nullptr, fmqResultDescriptor);
+
+ // configure burst
+ ErrorStatus errorStatus;
+ sp<IBurstContext> burstContext;
+ const Return<void> ret = preparedModel->configureExecutionBurst(
+ callback, *fmqRequestDescriptor, *fmqResultDescriptor,
+ [&errorStatus, &burstContext](ErrorStatus status, const sp<IBurstContext>& context) {
+ errorStatus = status;
+ burstContext = context;
+ });
+ ASSERT_TRUE(ret.isOk());
+ ASSERT_EQ(ErrorStatus::NONE, errorStatus);
+ ASSERT_NE(nullptr, burstContext.get());
+
+ // return values
+ *sender = std::move(fmqRequestChannel);
+ *receiver = std::move(fmqResultChannel);
+ *context = burstContext;
+}
+
+static void createBurstWithResultChannelLength(
+ const sp<IPreparedModel>& preparedModel,
+ std::shared_ptr<ExecutionBurstController>* controller, size_t resultChannelLength) {
+ ASSERT_NE(nullptr, preparedModel.get());
+ ASSERT_NE(nullptr, controller);
+
+ // create FMQ objects
+ auto [fmqRequestChannel, fmqRequestDescriptor] =
+ RequestChannelSender::create(kExecutionBurstChannelLength, /*blocking=*/true);
+ auto [fmqResultChannel, fmqResultDescriptor] =
+ ResultChannelReceiver::create(resultChannelLength, /*blocking=*/true);
+ ASSERT_NE(nullptr, fmqRequestChannel.get());
+ ASSERT_NE(nullptr, fmqResultChannel.get());
+ ASSERT_NE(nullptr, fmqRequestDescriptor);
+ ASSERT_NE(nullptr, fmqResultDescriptor);
+
+ // configure burst
+ sp<ExecutionBurstCallback> callback = new ExecutionBurstCallback();
+ ErrorStatus errorStatus;
+ sp<IBurstContext> burstContext;
+ const Return<void> ret = preparedModel->configureExecutionBurst(
+ callback, *fmqRequestDescriptor, *fmqResultDescriptor,
+ [&errorStatus, &burstContext](ErrorStatus status, const sp<IBurstContext>& context) {
+ errorStatus = status;
+ burstContext = context;
+ });
+ ASSERT_TRUE(ret.isOk());
+ ASSERT_EQ(ErrorStatus::NONE, errorStatus);
+ ASSERT_NE(nullptr, burstContext.get());
+
+ // return values
+ *controller = std::make_shared<ExecutionBurstController>(
+ std::move(fmqRequestChannel), std::move(fmqResultChannel), burstContext, callback);
+}
+
+// Primary validation function. This function will take a valid serialized
+// request, apply a mutation to it to invalidate the serialized request, then
+// pass it to interface calls that use the serialized request. Note that the
+// serialized request here is passed by value, and any mutation to the
+// serialized request does not leave this function.
+static void validate(RequestChannelSender* sender, ResultChannelReceiver* receiver,
+ const std::string& message, std::vector<FmqRequestDatum> serialized,
+ const std::function<void(std::vector<FmqRequestDatum>*)>& mutation) {
+ mutation(&serialized);
+
+ // skip if packet is too large to send
+ if (serialized.size() > kExecutionBurstChannelLength) {
+ return;
+ }
+
+ SCOPED_TRACE(message);
+
+ // send invalid packet
+ sender->sendPacket(serialized);
+
+ // receive error
+ auto results = receiver->getBlocking();
+ ASSERT_TRUE(results.has_value());
+ const auto [status, outputShapes, timing] = std::move(*results);
+ EXPECT_NE(ErrorStatus::NONE, status);
+ EXPECT_EQ(0u, outputShapes.size());
+ EXPECT_TRUE(badTiming(timing));
+}
+
+static std::vector<FmqRequestDatum> createUniqueDatum() {
+ const FmqRequestDatum::PacketInformation packetInformation = {
+ /*.packetSize=*/10, /*.numberOfInputOperands=*/10, /*.numberOfOutputOperands=*/10,
+ /*.numberOfPools=*/10};
+ const FmqRequestDatum::OperandInformation operandInformation = {
+ /*.hasNoValue=*/false, /*.location=*/{}, /*.numberOfDimensions=*/10};
+ const int32_t invalidPoolIdentifier = std::numeric_limits<int32_t>::max();
+ std::vector<FmqRequestDatum> unique(7);
+ unique[0].packetInformation(packetInformation);
+ unique[1].inputOperandInformation(operandInformation);
+ unique[2].inputOperandDimensionValue(0);
+ unique[3].outputOperandInformation(operandInformation);
+ unique[4].outputOperandDimensionValue(0);
+ unique[5].poolIdentifier(invalidPoolIdentifier);
+ unique[6].measureTiming(MeasureTiming::YES);
+ return unique;
+}
+
+static const std::vector<FmqRequestDatum>& getUniqueDatum() {
+ static const std::vector<FmqRequestDatum> unique = createUniqueDatum();
+ return unique;
+}
+
+///////////////////////// REMOVE DATUM ////////////////////////////////////
+
+static void removeDatumTest(RequestChannelSender* sender, ResultChannelReceiver* receiver,
+ const std::vector<FmqRequestDatum>& serialized) {
+ for (size_t index = 0; index < serialized.size(); ++index) {
+ const std::string message = "removeDatum: removed datum at index " + std::to_string(index);
+ validate(sender, receiver, message, serialized,
+ [index](std::vector<FmqRequestDatum>* serialized) {
+ serialized->erase(serialized->begin() + index);
+ });
+ }
+}
+
+///////////////////////// ADD DATUM ////////////////////////////////////
+
+static void addDatumTest(RequestChannelSender* sender, ResultChannelReceiver* receiver,
+ const std::vector<FmqRequestDatum>& serialized) {
+ const std::vector<FmqRequestDatum>& extra = getUniqueDatum();
+ for (size_t index = 0; index <= serialized.size(); ++index) {
+ for (size_t type = 0; type < extra.size(); ++type) {
+ const std::string message = "addDatum: added datum type " + std::to_string(type) +
+ " at index " + std::to_string(index);
+ validate(sender, receiver, message, serialized,
+ [index, type, &extra](std::vector<FmqRequestDatum>* serialized) {
+ serialized->insert(serialized->begin() + index, extra[type]);
+ });
+ }
+ }
+}
+
+///////////////////////// MUTATE DATUM ////////////////////////////////////
+
+static bool interestingCase(const FmqRequestDatum& lhs, const FmqRequestDatum& rhs) {
+ using Discriminator = FmqRequestDatum::hidl_discriminator;
+
+ const bool differentValues = (lhs != rhs);
+ const bool sameSumType = (lhs.getDiscriminator() == rhs.getDiscriminator());
+ const auto discriminator = rhs.getDiscriminator();
+ const bool isDimensionValue = (discriminator == Discriminator::inputOperandDimensionValue ||
+ discriminator == Discriminator::outputOperandDimensionValue);
+
+ return differentValues && !(sameSumType && isDimensionValue);
+}
+
+static void mutateDatumTest(RequestChannelSender* sender, ResultChannelReceiver* receiver,
+ const std::vector<FmqRequestDatum>& serialized) {
+ const std::vector<FmqRequestDatum>& change = getUniqueDatum();
+ for (size_t index = 0; index < serialized.size(); ++index) {
+ for (size_t type = 0; type < change.size(); ++type) {
+ if (interestingCase(serialized[index], change[type])) {
+ const std::string message = "mutateDatum: changed datum at index " +
+ std::to_string(index) + " to datum type " +
+ std::to_string(type);
+ validate(sender, receiver, message, serialized,
+ [index, type, &change](std::vector<FmqRequestDatum>* serialized) {
+ (*serialized)[index] = change[type];
+ });
+ }
+ }
+ }
+}
+
+///////////////////////// BURST VALIATION TESTS ////////////////////////////////////
+
+static void validateBurstSerialization(const sp<IPreparedModel>& preparedModel,
+ const std::vector<Request>& requests) {
+ // create burst
+ std::unique_ptr<RequestChannelSender> sender;
+ std::unique_ptr<ResultChannelReceiver> receiver;
+ sp<ExecutionBurstCallback> callback = new ExecutionBurstCallback();
+ sp<IBurstContext> context;
+ ASSERT_NO_FATAL_FAILURE(createBurst(preparedModel, callback, &sender, &receiver, &context));
+ ASSERT_NE(nullptr, sender.get());
+ ASSERT_NE(nullptr, receiver.get());
+ ASSERT_NE(nullptr, context.get());
+
+ // validate each request
+ for (const Request& request : requests) {
+ // load memory into callback slots
+ std::vector<intptr_t> keys(request.pools.size());
+ for (size_t i = 0; i < keys.size(); ++i) {
+ keys[i] = reinterpret_cast<intptr_t>(&request.pools[i]);
+ }
+ const std::vector<int32_t> slots = callback->getSlots(request.pools, keys);
+
+ // ensure slot std::numeric_limits<int32_t>::max() doesn't exist (for
+ // subsequent slot validation testing)
+ const auto maxElement = std::max_element(slots.begin(), slots.end());
+ ASSERT_NE(slots.end(), maxElement);
+ ASSERT_NE(std::numeric_limits<int32_t>::max(), *maxElement);
+
+ // serialize the request
+ const auto serialized = ::android::nn::serialize(request, MeasureTiming::YES, slots);
+
+ // validations
+ removeDatumTest(sender.get(), receiver.get(), serialized);
+ addDatumTest(sender.get(), receiver.get(), serialized);
+ mutateDatumTest(sender.get(), receiver.get(), serialized);
+ }
+}
+
+static void validateBurstFmqLength(const sp<IPreparedModel>& preparedModel,
+ const std::vector<Request>& requests) {
+ // create regular burst
+ std::shared_ptr<ExecutionBurstController> controllerRegular;
+ ASSERT_NO_FATAL_FAILURE(createBurstWithResultChannelLength(preparedModel, &controllerRegular,
+ kExecutionBurstChannelLength));
+ ASSERT_NE(nullptr, controllerRegular.get());
+
+ // create burst with small output channel
+ std::shared_ptr<ExecutionBurstController> controllerSmall;
+ ASSERT_NO_FATAL_FAILURE(createBurstWithResultChannelLength(preparedModel, &controllerSmall,
+ kExecutionBurstChannelSmallLength));
+ ASSERT_NE(nullptr, controllerSmall.get());
+
+ // validate each request
+ for (const Request& request : requests) {
+ // load memory into callback slots
+ std::vector<intptr_t> keys(request.pools.size());
+ for (size_t i = 0; i < keys.size(); ++i) {
+ keys[i] = reinterpret_cast<intptr_t>(&request.pools[i]);
+ }
+
+ // collect serialized result by running regular burst
+ const auto [status1, outputShapes1, timing1] =
+ controllerRegular->compute(request, MeasureTiming::NO, keys);
+
+ // skip test if synchronous output isn't useful
+ const std::vector<FmqResultDatum> serialized =
+ ::android::nn::serialize(status1, outputShapes1, timing1);
+ if (status1 != ErrorStatus::NONE ||
+ serialized.size() <= kExecutionBurstChannelSmallLength) {
+ continue;
+ }
+
+ // by this point, execution should fail because the result channel isn't
+ // large enough to return the serialized result
+ const auto [status2, outputShapes2, timing2] =
+ controllerSmall->compute(request, MeasureTiming::NO, keys);
+ EXPECT_NE(ErrorStatus::NONE, status2);
+ EXPECT_EQ(0u, outputShapes2.size());
+ EXPECT_TRUE(badTiming(timing2));
+ }
+}
+
+///////////////////////////// ENTRY POINT //////////////////////////////////
+
+void ValidationTest::validateBurst(const sp<IPreparedModel>& preparedModel,
+ const std::vector<Request>& requests) {
+ ASSERT_NO_FATAL_FAILURE(validateBurstSerialization(preparedModel, requests));
+ ASSERT_NO_FATAL_FAILURE(validateBurstFmqLength(preparedModel, requests));
+}
+
+} // namespace functional
+} // namespace vts
+} // namespace V1_2
+} // namespace neuralnetworks
+} // namespace hardware
+} // namespace android
diff --git a/neuralnetworks/1.2/vts/functional/ValidateRequest.cpp b/neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
index 870d017..9703c2d 100644
--- a/neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
+++ b/neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
@@ -35,9 +35,7 @@
namespace functional {
using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
-using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
using ::android::hidl::memory::V1_0::IMemory;
-using HidlToken = hidl_array<uint8_t, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN)>;
using test_helper::for_all;
using test_helper::MixedTyped;
using test_helper::MixedTypedExample;
@@ -48,55 +46,6 @@
return timing.timeOnDevice == UINT64_MAX && timing.timeInDriver == UINT64_MAX;
}
-static void createPreparedModel(const sp<IDevice>& device, const Model& model,
- sp<IPreparedModel>* preparedModel) {
- ASSERT_NE(nullptr, preparedModel);
-
- // see if service can handle model
- bool fullySupportsModel = false;
- Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_2(
- model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
- ASSERT_EQ(ErrorStatus::NONE, status);
- ASSERT_NE(0ul, supported.size());
- fullySupportsModel =
- std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; });
- });
- ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
-
- // launch prepare model
- sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
- ASSERT_NE(nullptr, preparedModelCallback.get());
- Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_2(
- model, ExecutionPreference::FAST_SINGLE_ANSWER, hidl_vec<hidl_handle>(),
- hidl_vec<hidl_handle>(), HidlToken(), preparedModelCallback);
- ASSERT_TRUE(prepareLaunchStatus.isOk());
- ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
-
- // retrieve prepared model
- preparedModelCallback->wait();
- ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
- *preparedModel = getPreparedModel_1_2(preparedModelCallback);
-
- // The getSupportedOperations_1_2 call returns a list of operations that are
- // guaranteed not to fail if prepareModel_1_2 is called, and
- // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
- // If a driver has any doubt that it can prepare an operation, it must
- // return false. So here, if a driver isn't sure if it can support an
- // operation, but reports that it successfully prepared the model, the test
- // can continue.
- if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
- ASSERT_EQ(nullptr, preparedModel->get());
- LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
- "prepare model that it does not support.";
- std::cout << "[ ] Unable to test Request validation because vendor service "
- "cannot prepare model that it does not support."
- << std::endl;
- return;
- }
- ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
- ASSERT_NE(nullptr, preparedModel->get());
-}
-
// Primary validation function. This function will take a valid request, apply a
// mutation to it to invalidate the request, then pass it to interface calls
// that use the request. Note that the request here is passed by value, and any
@@ -316,14 +265,8 @@
return requests;
}
-void ValidationTest::validateRequests(const Model& model, const std::vector<Request>& requests) {
- // create IPreparedModel
- sp<IPreparedModel> preparedModel;
- ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
- if (preparedModel == nullptr) {
- return;
- }
-
+void ValidationTest::validateRequests(const sp<IPreparedModel>& preparedModel,
+ const std::vector<Request>& requests) {
// validate each request
for (const Request& request : requests) {
removeInputTest(preparedModel, request);
diff --git a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
index 4728c28..93182f1 100644
--- a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
@@ -18,6 +18,10 @@
#include "VtsHalNeuralnetworks.h"
+#include <android-base/logging.h>
+
+#include "Callbacks.h"
+
namespace android {
namespace hardware {
namespace neuralnetworks {
@@ -25,6 +29,61 @@
namespace vts {
namespace functional {
+using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
+using HidlToken = hidl_array<uint8_t, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN)>;
+using V1_1::ExecutionPreference;
+
+// internal helper function
+static void createPreparedModel(const sp<IDevice>& device, const Model& model,
+ sp<IPreparedModel>* preparedModel) {
+ ASSERT_NE(nullptr, preparedModel);
+
+ // see if service can handle model
+ bool fullySupportsModel = false;
+ Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_2(
+ model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
+ ASSERT_EQ(ErrorStatus::NONE, status);
+ ASSERT_NE(0ul, supported.size());
+ fullySupportsModel = std::all_of(supported.begin(), supported.end(),
+ [](bool valid) { return valid; });
+ });
+ ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
+
+ // launch prepare model
+ sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+ ASSERT_NE(nullptr, preparedModelCallback.get());
+ Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_2(
+ model, ExecutionPreference::FAST_SINGLE_ANSWER, hidl_vec<hidl_handle>(),
+ hidl_vec<hidl_handle>(), HidlToken(), preparedModelCallback);
+ ASSERT_TRUE(prepareLaunchStatus.isOk());
+ ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
+
+ // retrieve prepared model
+ preparedModelCallback->wait();
+ ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+ *preparedModel = getPreparedModel_1_2(preparedModelCallback);
+
+ // The getSupportedOperations_1_2 call returns a list of operations that are
+ // guaranteed not to fail if prepareModel_1_2 is called, and
+ // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
+ // If a driver has any doubt that it can prepare an operation, it must
+ // return false. So here, if a driver isn't sure if it can support an
+ // operation, but reports that it successfully prepared the model, the test
+ // can continue.
+ if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
+ ASSERT_EQ(nullptr, preparedModel->get());
+ LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
+ "prepare model that it does not support.";
+ std::cout << "[ ] Unable to test Request validation because vendor service "
+ "cannot prepare model that it does not support."
+ << std::endl;
+ return;
+ }
+ ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+ ASSERT_NE(nullptr, preparedModel->get());
+}
+
// A class for test environment setup
NeuralnetworksHidlEnvironment::NeuralnetworksHidlEnvironment() {}
@@ -68,6 +127,20 @@
::testing::VtsHalHidlTargetTestBase::TearDown();
}
+void ValidationTest::validateEverything(const Model& model, const std::vector<Request>& request) {
+ validateModel(model);
+
+ // create IPreparedModel
+ sp<IPreparedModel> preparedModel;
+ ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
+ if (preparedModel == nullptr) {
+ return;
+ }
+
+ validateRequests(preparedModel, request);
+ validateBurst(preparedModel, request);
+}
+
sp<IPreparedModel> getPreparedModel_1_2(
const sp<V1_2::implementation::PreparedModelCallback>& callback) {
sp<V1_0::IPreparedModel> preparedModelV1_0 = callback->getPreparedModel();
diff --git a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
index 404eec0..36e73a4 100644
--- a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
@@ -72,8 +72,14 @@
// Tag for the validation tests
class ValidationTest : public NeuralnetworksHidlTest {
protected:
- void validateModel(const Model& model);
- void validateRequests(const Model& model, const std::vector<Request>& request);
+ void validateEverything(const Model& model, const std::vector<Request>& request);
+
+ private:
+ void validateModel(const Model& model);
+ void validateRequests(const sp<IPreparedModel>& preparedModel,
+ const std::vector<Request>& requests);
+ void validateBurst(const sp<IPreparedModel>& preparedModel,
+ const std::vector<Request>& requests);
};
// Tag for the generated tests
diff --git a/radio/1.3/vts/functional/radio_hidl_hal_api.cpp b/radio/1.3/vts/functional/radio_hidl_hal_api.cpp
index 1bebae7..030f489 100644
--- a/radio/1.3/vts/functional/radio_hidl_hal_api.cpp
+++ b/radio/1.3/vts/functional/radio_hidl_hal_api.cpp
@@ -78,6 +78,8 @@
/*
* Test IRadio.setSystemSelectionChannels() for the response returned.
+ *
+ * This test is excluded from manifest, due to non-implementation in Q. Tracked by b/130254624.
*/
TEST_F(RadioHidlTest_v1_3, setSystemSelectionChannels) {
serial = GetRandomSerialNumber();
diff --git a/soundtrigger/2.2/vts/functional/Android.bp b/soundtrigger/2.2/vts/functional/Android.bp
new file mode 100644
index 0000000..08ccd7b
--- /dev/null
+++ b/soundtrigger/2.2/vts/functional/Android.bp
@@ -0,0 +1,27 @@
+//
+// Copyright (C) 2019 The Android Open Source Project
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+
+cc_test {
+ name: "VtsHalSoundtriggerV2_2TargetTest",
+ defaults: ["VtsHalTargetTestDefaults"],
+ srcs: ["VtsHalSoundtriggerV2_2TargetTest.cpp"],
+ static_libs: [
+ "android.hardware.soundtrigger@2.0",
+ "android.hardware.soundtrigger@2.1",
+ "android.hardware.soundtrigger@2.2",
+ ],
+ test_suites: ["general-tests"],
+}
diff --git a/wifi/1.0/vts/functional/wifi_sta_iface_hidl_test.cpp b/wifi/1.0/vts/functional/wifi_sta_iface_hidl_test.cpp
index a22cd72..a413863 100644
--- a/wifi/1.0/vts/functional/wifi_sta_iface_hidl_test.cpp
+++ b/wifi/1.0/vts/functional/wifi_sta_iface_hidl_test.cpp
@@ -258,6 +258,11 @@
* code.
*/
TEST_F(WifiStaIfaceHidlTest, SetScanningMacOui) {
+ if (!isCapabilitySupported(
+ IWifiStaIface::StaIfaceCapabilityMask::SCAN_RAND)) {
+ // No-op if SetScanningMacOui is not supported.
+ return;
+ }
const android::hardware::hidl_array<uint8_t, 3> kOui{
std::array<uint8_t, 3>{{0x10, 0x22, 0x33}}};
EXPECT_EQ(WifiStatusCode::SUCCESS,
diff --git a/wifi/1.3/default/wifi_chip.cpp b/wifi/1.3/default/wifi_chip.cpp
index 25eb289..b768959 100644
--- a/wifi/1.3/default/wifi_chip.cpp
+++ b/wifi/1.3/default/wifi_chip.cpp
@@ -1436,14 +1436,11 @@
}
std::string WifiChip::getFirstActiveWlanIfaceName() {
- for (unsigned idx = 0; idx < kMaxWlanIfaces; idx++) {
- const auto ifname = getWlanIfaceName(idx);
- if (findUsingName(sta_ifaces_, ifname)) return ifname;
- if (findUsingName(ap_ifaces_, ifname)) return ifname;
- }
+ if (sta_ifaces_.size() > 0) return sta_ifaces_[0]->getName();
+ if (ap_ifaces_.size() > 0) return ap_ifaces_[0]->getName();
// This could happen if the chip call is made before any STA/AP
// iface is created. Default to wlan0 for such cases.
- LOG(WARNING) << "No active wlan interfaces in use!";
+ LOG(WARNING) << "No active wlan interfaces in use! Using default";
return getWlanIfaceName(0);
}