Merge "Remove VehicleApPowerStateConfigFlag comment."
diff --git a/current.txt b/current.txt
index e57182d..e1b3356 100644
--- a/current.txt
+++ b/current.txt
@@ -449,7 +449,7 @@
92714960d1a53fc2ec557302b41c7cc93d2636d8364a44bd0f85be0c92927ff8 android.hardware.neuralnetworks@1.2::IExecutionCallback
83885d366f22ada42c00d8854f0b7e7ba4cf73ddf80bb0d8e168ce132cec57ea android.hardware.neuralnetworks@1.2::IPreparedModel
e1c734d1545e1a4ae749ff1dd9704a8e594c59aea7c8363159dc258e93e0df3b android.hardware.neuralnetworks@1.2::IPreparedModelCallback
-447dda9186280d119e95937d707e8ae4729af9a922d22a29f069952da269c8c1 android.hardware.neuralnetworks@1.2::types
+896d1827541d620996720a79c6476edb902a58d515bf908f67a5bdef4d2c318c 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/health/2.0/vts/functional/VtsHalHealthV2_0TargetTest.cpp b/health/2.0/vts/functional/VtsHalHealthV2_0TargetTest.cpp
index 4af8a5d..74fe4fb 100644
--- a/health/2.0/vts/functional/VtsHalHealthV2_0TargetTest.cpp
+++ b/health/2.0/vts/functional/VtsHalHealthV2_0TargetTest.cpp
@@ -17,6 +17,8 @@
#define LOG_TAG "health_hidl_hal_test"
#include <mutex>
+#include <set>
+#include <string>
#include <VtsHalHidlTargetTestBase.h>
#include <android-base/logging.h>
@@ -32,6 +34,39 @@
DEFINE_bool(force, false, "Force test healthd even when the default instance is present.");
+// If GTEST_SKIP is not implemented, use our own skipping mechanism
+#ifndef GTEST_SKIP
+static std::mutex gSkippedTestsMutex;
+static std::set<std::string> gSkippedTests;
+static std::string GetCurrentTestName() {
+ const auto& info = ::testing::UnitTest::GetInstance()->current_test_info();
+#ifdef GTEST_REMOVE_LEGACY_TEST_CASEAPI_
+ std::string test_suite = info->test_suite_name();
+#else
+ std::string test_suite = info->test_case_name();
+#endif
+ return test_suite + "." + info->name();
+}
+
+#define GTEST_SKIP() \
+ do { \
+ std::unique_lock<std::mutex> lock(gSkippedTestsMutex); \
+ gSkippedTests.insert(GetCurrentTestName()); \
+ return; \
+ } while (0)
+
+#define SKIP_IF_SKIPPED() \
+ do { \
+ std::unique_lock<std::mutex> lock(gSkippedTestsMutex); \
+ if (gSkippedTests.find(GetCurrentTestName()) != gSkippedTests.end()) { \
+ std::cerr << "[ SKIPPED ] " << GetCurrentTestName() << std::endl; \
+ return; \
+ } \
+ } while (0)
+#else
+#define SKIP_IF_SKIPPED()
+#endif
+
namespace android {
namespace hardware {
namespace health {
@@ -122,6 +157,7 @@
* unregisterCallback, and update.
*/
TEST_F(HealthHidlTest, Callbacks) {
+ SKIP_IF_SKIPPED();
using namespace std::chrono_literals;
sp<Callback> firstCallback = new Callback();
sp<Callback> secondCallback = new Callback();
@@ -158,6 +194,7 @@
}
TEST_F(HealthHidlTest, UnregisterNonExistentCallback) {
+ SKIP_IF_SKIPPED();
sp<Callback> callback = new Callback();
auto ret = mHealth->unregisterCallback(callback);
ASSERT_OK(ret);
@@ -236,6 +273,7 @@
* Tests the values returned by getChargeCounter() from interface IHealth.
*/
TEST_F(HealthHidlTest, getChargeCounter) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getChargeCounter([](auto result, auto value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(result, std::to_string(value), value > 0);
}));
@@ -245,6 +283,7 @@
* Tests the values returned by getCurrentNow() from interface IHealth.
*/
TEST_F(HealthHidlTest, getCurrentNow) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getCurrentNow([](auto result, auto value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(result, std::to_string(value), value != INT32_MIN);
}));
@@ -254,6 +293,7 @@
* Tests the values returned by getCurrentAverage() from interface IHealth.
*/
TEST_F(HealthHidlTest, getCurrentAverage) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getCurrentAverage([](auto result, auto value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(result, std::to_string(value), value != INT32_MIN);
}));
@@ -263,6 +303,7 @@
* Tests the values returned by getCapacity() from interface IHealth.
*/
TEST_F(HealthHidlTest, getCapacity) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getCapacity([](auto result, auto value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(result, std::to_string(value), 0 <= value && value <= 100);
}));
@@ -272,6 +313,7 @@
* Tests the values returned by getEnergyCounter() from interface IHealth.
*/
TEST_F(HealthHidlTest, getEnergyCounter) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getEnergyCounter([](auto result, auto value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(result, std::to_string(value), value != INT64_MIN);
}));
@@ -281,6 +323,7 @@
* Tests the values returned by getChargeStatus() from interface IHealth.
*/
TEST_F(HealthHidlTest, getChargeStatus) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getChargeStatus([](auto result, auto value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(
result, toString(value),
@@ -292,6 +335,7 @@
* Tests the values returned by getStorageInfo() from interface IHealth.
*/
TEST_F(HealthHidlTest, getStorageInfo) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getStorageInfo([](auto result, auto& value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(result, toString(value), verifyStorageInfo(value));
}));
@@ -301,6 +345,7 @@
* Tests the values returned by getDiskStats() from interface IHealth.
*/
TEST_F(HealthHidlTest, getDiskStats) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getDiskStats([](auto result, auto& value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(result, toString(value), true);
}));
@@ -310,6 +355,7 @@
* Tests the values returned by getHealthInfo() from interface IHealth.
*/
TEST_F(HealthHidlTest, getHealthInfo) {
+ SKIP_IF_SKIPPED();
EXPECT_OK(mHealth->getHealthInfo([](auto result, auto& value) {
EXPECT_VALID_OR_UNSUPPORTED_PROP(result, toString(value), verifyHealthInfo(value));
}));
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index bb5d777..bb14dec 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -4223,7 +4223,7 @@
TOPK_V2 = 90,
/**
- * Performs the tranpose of 2-D convolution operation.
+ * Performs the transpose of 2-D convolution operation.
*
* This operation is sometimes called "deconvolution" after Deconvolutional
* Networks, but is actually the transpose (gradient) of