Merge "Put composer 2.3 in the right cpuset." into qt-dev
diff --git a/automotive/vehicle/2.0/types.hal b/automotive/vehicle/2.0/types.hal
index b04d096..661c3d4 100644
--- a/automotive/vehicle/2.0/types.hal
+++ b/automotive/vehicle/2.0/types.hal
@@ -3249,6 +3249,16 @@
*/
enum VmsMessageType : int32_t {
/**
+ * A notification indicating that the sender has been reset.
+ *
+ * The receiving party must reset its internal state and respond to the
+ * sender with a START_SESSION message as acknowledgement.
+ *
+ * This message type uses enum VmsStartSessionMessageIntegerValuesIndex.
+ */
+ START_SESSION = 17,
+
+ /**
* A request from the subscribers to the VMS service to subscribe to a layer.
*
* This message type uses enum VmsMessageWithLayerIntegerValuesIndex.
@@ -3364,7 +3374,7 @@
*/
PUBLISHER_INFORMATION_RESPONSE = 16,
- LAST_VMS_MESSAGE_TYPE = PUBLISHER_INFORMATION_RESPONSE,
+ LAST_VMS_MESSAGE_TYPE = START_SESSION,
};
/**
@@ -3378,6 +3388,30 @@
};
/*
+ * Handshake data sent as part of a VmsMessageType.START_SESSION message.
+ *
+ * A new session is initiated by sending a START_SESSION message with the
+ * sender's identifier populated and the receiver's identifier set to -1.
+ *
+ * Identifier values are independently generated, but must be non-negative, and
+ * increase monotonically between reboots.
+ *
+ * Upon receiving a START_SESSION with a mis-matching identifier, the receiver
+ * must clear any cached VMS offering or subscription state and acknowledge the
+ * new session by responding with a START_SESSION message that populates both
+ * identifier fields.
+ *
+ * Any VMS messages received between initiation and completion of the handshake
+ * must be discarded.
+ */
+enum VmsStartSessionMessageIntegerValuesIndex : VmsBaseMessageIntegerValuesIndex {
+ /* Identifier field for the Android system service. */
+ SERVICE_ID = 1,
+ /* Identifier field for the HAL client process. */
+ CLIENT_ID = 2,
+};
+
+/*
* A VMS message with a layer is sent as part of a VmsMessageType.SUBSCRIBE or
* VmsMessageType.UNSUBSCRIBE messages.
*
diff --git a/current.txt b/current.txt
index 1f32263..64fd4ae 100644
--- a/current.txt
+++ b/current.txt
@@ -393,8 +393,10 @@
23780340c686ee86986aa5a9755c2d8566224fed177bbb22a5ebf06be574b60c android.hardware.camera.metadata@3.3::types
05d1ee760d81cdd2dc7a70ce0241af9fa830edae33b4be83d9bf5fffe05ddc6f android.hardware.camera.provider@2.4::ICameraProvider
da33234403ff5d60f3473711917b9948e6484a4260b5247acdafb111193a9de2 android.hardware.configstore@1.0::ISurfaceFlingerConfigs
+ede69710c3a95c2cbe818e6c8bb72c7816823face5fc21c17731b26f41d94d65 android.hardware.gnss@1.0::IGnss
21165b8e30c4b2d52980e4728f661420adc16e38bbe73476c06b2085be908f4c android.hardware.gnss@1.0::IGnssCallback
d702fb01dc2a0733aa820b7eb65435ee3334f75632ef880bafd2fb8803a20a58 android.hardware.gnss@1.0::IGnssMeasurementCallback
+b5f1f4c1bd6de71a8e71d70f57cdab904ac024a12f3dee3e2173770a4583bcc2 android.hardware.gnss@1.1::IGnss
7c7721c0f773fcf422b71a4f558545e9e36acc973e58ca51e5bd53905cf46bc0 android.hardware.graphics.bufferqueue@1.0::IGraphicBufferProducer
d4fea995378bb4f421b4e24ccf68cad2734ab07fe4f874a126ba558b99df5766 android.hardware.graphics.composer@2.1::IComposerClient
f7d7cb747dc01a9fdb2d39a80003b4d8df9be733d65f5842198802eb6209db69 android.hardware.graphics.mapper@2.0::IMapper
@@ -467,7 +469,7 @@
7f460e795f5d1ed5e378935f98c6db4d39497de988aef1b4c2a4a07a6c400392 android.hardware.gnss@2.0::IAGnss
2e5ad983734069e84a760004b32da0d09e4170c05380abe27e6eb80e4aa70d5a android.hardware.gnss@2.0::IAGnssCallback
1f4ac068a88a72360280d94a7f6fd7c63813c1eea4891a0eb01394d3e7e775f2 android.hardware.gnss@2.0::IAGnssRil
-4deafcdcffa2d002119e7f58810b767a84666e76475aae68e757ec2845d9756d android.hardware.gnss@2.0::IGnss
+f5605f48c2fb9f231615dd932bf730ae9540f4f98b5b7ae2b269975f452f6d73 android.hardware.gnss@2.0::IGnss
db6bdf6dfc5edf6c85d2944976db899227abb51079c893874353c322342c50b6 android.hardware.gnss@2.0::IGnssBatching
1f89392f1ebb693d8fa6f50324b1635fc79fab246d31900e63998e1b0e17511c android.hardware.gnss@2.0::IGnssBatchingCallback
64232037109a5e5f53ab0377e755ec494ae93fcb5279e6eea71dec2e7ac6fbfc android.hardware.gnss@2.0::IGnssCallback
diff --git a/gnss/1.0/IGnss.hal b/gnss/1.0/IGnss.hal
index 602c615..d32bc63 100644
--- a/gnss/1.0/IGnss.hal
+++ b/gnss/1.0/IGnss.hal
@@ -75,8 +75,13 @@
};
/**
- * Opens the interface and provides the callback routines
- * to the implementation of this interface.
+ * Opens the interface and provides the callback routines to the implementation of this
+ * interface.
+ *
+ * The framework calls this method to instruct the GPS engine to prepare for serving requests
+ * from the framework. The GNSS HAL implementation must respond to all GNSS requests from the
+ * framework upon successful return from this method until cleanup() method is called to
+ * close this interface.
*
* @param callback Callback interface for IGnss.
*
@@ -105,6 +110,18 @@
/**
* Closes the interface.
+ *
+ * The cleanup() method is called by the framework to tell the GNSS HAL implementation to
+ * not expect any GNSS requests in the immediate future - e.g. this may be called when
+ * location is disabled by a user setting or low battery conditions. The GNSS HAL
+ * implementation must immediately stop responding to any existing requests until the
+ * setCallback() method is called again and the requests are re-initiated by the framework.
+ *
+ * After this method is called, the GNSS HAL implementation may choose to modify GNSS hardware
+ * states to save power. It is expected that when setCallback() method is called again to
+ * reopen this interface, to serve requests, there may be some minor delays in GNSS response
+ * requests as hardware readiness states are restored, not to exceed those that occur on normal
+ * device boot up.
*/
cleanup();
@@ -153,7 +170,7 @@
* @param mode Parameter must be one of MS_BASED or STANDALONE.
* It is allowed by the platform (and it is recommended) to fallback to
* MS_BASED if MS_ASSISTED is passed in, and MS_BASED is supported.
- * @recurrence GNSS postion recurrence value, either periodic or single.
+ * @recurrence GNSS position recurrence value, either periodic or single.
* @param minIntervalMs Represents the time between fixes in milliseconds.
* @param preferredAccuracyMeters Represents the requested fix accuracy in meters.
* @param preferredTimeMs Represents the requested time to first fix in milliseconds.
diff --git a/gnss/1.1/IGnss.hal b/gnss/1.1/IGnss.hal
index 672f742..3400807 100644
--- a/gnss/1.1/IGnss.hal
+++ b/gnss/1.1/IGnss.hal
@@ -29,6 +29,11 @@
* Opens the interface and provides the callback routines to the implementation of this
* interface.
*
+ * The framework calls this method to instruct the GPS engine to prepare for serving requests
+ * from the framework. The GNSS HAL implementation must respond to all GNSS requests from the
+ * framework upon successful return from this method until cleanup() method is called to
+ * close this interface.
+ *
* @param callback Callback interface for IGnss.
*
* @return success Returns true on success.
@@ -42,7 +47,7 @@
* @param mode Parameter must be one of MS_BASED or STANDALONE. It is allowed by the platform
* (and it is recommended) to fallback to MS_BASED if MS_ASSISTED is passed in, and MS_BASED
* is supported.
- * @param recurrence GNSS postion recurrence value, either periodic or single.
+ * @param recurrence GNSS position recurrence value, either periodic or single.
* @param minIntervalMs Represents the time between fixes in milliseconds.
* @param preferredAccuracyMeters Represents the requested fix accuracy in meters.
* @param preferredTimeMs Represents the requested time to first fix in milliseconds.
diff --git a/gnss/2.0/IGnss.hal b/gnss/2.0/IGnss.hal
index f19f8d0..9935bf9 100644
--- a/gnss/2.0/IGnss.hal
+++ b/gnss/2.0/IGnss.hal
@@ -36,13 +36,18 @@
* the interface @1.0::IGnssNi.hal and @1.0::IGnssNiCallback.hal are deprecated in this version
* and are not supported by the framework. The GNSS HAL implementation of this interface
* must return nullptr for the following @1.0::IGnss method.
- * getExtensionGnssNi() generates (IGnssNi gnssNiIface);
+ * getExtensionGnssNi() generates (IGnssNi gnssNiIface);
*/
interface IGnss extends @1.1::IGnss {
/**
* Opens the interface and provides the callback routines to the implementation of this
* interface.
*
+ * The framework calls this method to instruct the GPS engine to prepare for serving requests
+ * from the framework. The GNSS HAL implementation must respond to all GNSS requests from the
+ * framework upon successful return from this method until cleanup() method is called to
+ * close this interface.
+ *
* @param callback Callback interface for IGnss.
*
* @return success Returns true on success.
@@ -83,8 +88,9 @@
/**
* This method returns the IGnssMeasurement interface.
*
- * Exactly one of getExtensionGnssMeasurement_1_1() and getExtensionGnssMeasurement_2_0() must
- * return a non-null handle, and the other method must return nullptr.
+ * Exactly one of getExtensionGnssMeasurement(), getExtensionGnssMeasurement_1_1(), and
+ * getExtensionGnssMeasurement_2_0() methods must return a non-null handle, and the other
+ * methods must return nullptr.
*
* @return gnssMeasurementIface Handle to the IGnssMeasurement interface.
*/
diff --git a/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp b/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
index bf91560..4411b90 100644
--- a/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
+++ b/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
@@ -45,9 +45,9 @@
using ::android::nn::allocateSharedMemory;
using ::test_helper::MixedTypedExample;
-namespace {
+namespace float32_model {
-// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of mobilenet.
+// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of float32 mobilenet.
#include "examples/mobilenet_224_gender_basic_fixed.example.cpp"
#include "vts_models/mobilenet_224_gender_basic_fixed.model.cpp"
@@ -55,6 +55,44 @@
[[maybe_unused]] auto dummy_createTestModel = createTestModel_dynamic_output_shape;
[[maybe_unused]] auto dummy_get_examples = get_examples_dynamic_output_shape;
+// 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 float32_model
+
+namespace quant8_model {
+
+// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of quant8 mobilenet.
+#include "examples/mobilenet_quantized.example.cpp"
+#include "vts_models/mobilenet_quantized.model.cpp"
+
+// Prevent the compiler from complaining about an otherwise unused function.
+[[maybe_unused]] auto dummy_createTestModel = createTestModel_dynamic_output_shape;
+[[maybe_unused]] auto dummy_get_examples = get_examples_dynamic_output_shape;
+
+// 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) {
+ uint8_t outputValue = 1 + static_cast<uint8_t>(len);
+ return {{.operands = {// Input
+ {.operandDimensions = {{0, {1}}}, .quant8AsymmOperands = {{0, {1}}}},
+ // Output
+ {.operandDimensions = {{0, {1}}},
+ .quant8AsymmOperands = {{0, {outputValue}}}}}}};
+}
+
+} // namespace quant8_model
+
+namespace {
+
enum class AccessMode { READ_WRITE, READ_ONLY, WRITE_ONLY };
// Creates cache handles based on provided file groups.
@@ -101,14 +139,18 @@
// ↑ ↑ ↑ ↑
// [1] [1] [1] [1]
//
-Model createLargeTestModel(OperationType op, uint32_t len) {
+// This function assumes the operation is either ADD or MUL.
+template <typename CppType, OperandType operandType>
+Model createLargeTestModelImpl(OperationType op, uint32_t len) {
+ EXPECT_TRUE(op == OperationType::ADD || op == OperationType::MUL);
+
// 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));
+ std::vector<uint8_t> operandValues(sizeof(int32_t) + len * sizeof(CppType));
// The activation scalar, value = 0.
operands[0] = {
@@ -122,7 +164,26 @@
};
memset(operandValues.data(), 0, sizeof(int32_t));
- const float floatBufferValue = 1.0f;
+ // The buffer value of the constant second operand. The logical value is always 1.0f.
+ CppType bufferValue;
+ // The scale of the first and second operand.
+ float scale1, scale2;
+ if (operandType == OperandType::TENSOR_FLOAT32) {
+ bufferValue = 1.0f;
+ scale1 = 0.0f;
+ scale2 = 0.0f;
+ } else if (op == OperationType::ADD) {
+ bufferValue = 1;
+ scale1 = 1.0f;
+ scale2 = 1.0f;
+ } else {
+ // To satisfy the constraint on quant8 MUL: input0.scale * input1.scale < output.scale,
+ // set input1 to have scale = 0.5f and bufferValue = 2, i.e. 1.0f in floating point.
+ bufferValue = 2;
+ scale1 = 1.0f;
+ scale2 = 0.5f;
+ }
+
for (uint32_t i = 0; i < len; i++) {
const uint32_t firstInputIndex = i * 2 + 1;
const uint32_t secondInputIndex = firstInputIndex + 1;
@@ -130,10 +191,10 @@
// The first operation input.
operands[firstInputIndex] = {
- .type = OperandType::TENSOR_FLOAT32,
+ .type = operandType,
.dimensions = {1},
.numberOfConsumers = 1,
- .scale = 0.0f,
+ .scale = scale1,
.zeroPoint = 0,
.lifetime = (i == 0 ? OperandLifeTime::MODEL_INPUT
: OperandLifeTime::TEMPORARY_VARIABLE),
@@ -142,18 +203,18 @@
// The second operation input, value = 1.
operands[secondInputIndex] = {
- .type = OperandType::TENSOR_FLOAT32,
+ .type = operandType,
.dimensions = {1},
.numberOfConsumers = 1,
- .scale = 0.0f,
+ .scale = scale2,
.zeroPoint = 0,
.lifetime = OperandLifeTime::CONSTANT_COPY,
.location = {.poolIndex = 0,
- .offset = static_cast<uint32_t>(i * sizeof(float) + sizeof(int32_t)),
- .length = sizeof(float)},
+ .offset = static_cast<uint32_t>(i * sizeof(CppType) + sizeof(int32_t)),
+ .length = sizeof(CppType)},
};
- memcpy(operandValues.data() + sizeof(int32_t) + i * sizeof(float), &floatBufferValue,
- sizeof(float));
+ memcpy(operandValues.data() + sizeof(int32_t) + i * sizeof(CppType), &bufferValue,
+ sizeof(CppType));
// 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
@@ -168,10 +229,10 @@
// The model output.
operands.back() = {
- .type = OperandType::TENSOR_FLOAT32,
+ .type = operandType,
.dimensions = {1},
.numberOfConsumers = 0,
- .scale = 0.0f,
+ .scale = scale1,
.zeroPoint = 0,
.lifetime = OperandLifeTime::MODEL_OUTPUT,
.location = {},
@@ -191,22 +252,13 @@
};
}
-// 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.
-class CompilationCachingTest : public NeuralnetworksHidlTest {
+class CompilationCachingTestBase : public NeuralnetworksHidlTest {
protected:
+ CompilationCachingTestBase(OperandType type) : kOperandType(type) {}
+
void SetUp() override {
NeuralnetworksHidlTest::SetUp();
ASSERT_NE(device.get(), nullptr);
@@ -263,6 +315,40 @@
NeuralnetworksHidlTest::TearDown();
}
+ // Model and examples creators. According to kOperandType, the following methods will return
+ // either float32 model/examples or the quant8 variant.
+ Model createTestModel() {
+ if (kOperandType == OperandType::TENSOR_FLOAT32) {
+ return float32_model::createTestModel();
+ } else {
+ return quant8_model::createTestModel();
+ }
+ }
+
+ std::vector<MixedTypedExample> get_examples() {
+ if (kOperandType == OperandType::TENSOR_FLOAT32) {
+ return float32_model::get_examples();
+ } else {
+ return quant8_model::get_examples();
+ }
+ }
+
+ Model createLargeTestModel(OperationType op, uint32_t len) {
+ if (kOperandType == OperandType::TENSOR_FLOAT32) {
+ return createLargeTestModelImpl<float, OperandType::TENSOR_FLOAT32>(op, len);
+ } else {
+ return createLargeTestModelImpl<uint8_t, OperandType::TENSOR_QUANT8_ASYMM>(op, len);
+ }
+ }
+
+ std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
+ if (kOperandType == OperandType::TENSOR_FLOAT32) {
+ return float32_model::getLargeModelExamples(len);
+ } else {
+ return quant8_model::getLargeModelExamples(len);
+ }
+ }
+
// See if the service can handle the model.
bool isModelFullySupported(const V1_2::Model& model) {
bool fullySupportsModel = false;
@@ -366,9 +452,20 @@
uint32_t mNumModelCache;
uint32_t mNumDataCache;
uint32_t mIsCachingSupported;
+
+ // The primary data type of the testModel.
+ const OperandType kOperandType;
};
-TEST_F(CompilationCachingTest, CacheSavingAndRetrieval) {
+// A parameterized fixture of CompilationCachingTestBase. Every test will run twice, with the first
+// pass running with float32 models and the second pass running with quant8 models.
+class CompilationCachingTest : public CompilationCachingTestBase,
+ public ::testing::WithParamInterface<OperandType> {
+ protected:
+ CompilationCachingTest() : CompilationCachingTestBase(GetParam()) {}
+};
+
+TEST_P(CompilationCachingTest, CacheSavingAndRetrieval) {
// Create test HIDL model and compile.
const Model testModel = createTestModel();
if (checkEarlyTermination(testModel)) return;
@@ -409,7 +506,7 @@
/*testDynamicOutputShape=*/false);
}
-TEST_F(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
+TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
// Create test HIDL model and compile.
const Model testModel = createTestModel();
if (checkEarlyTermination(testModel)) return;
@@ -472,7 +569,7 @@
/*testDynamicOutputShape=*/false);
}
-TEST_F(CompilationCachingTest, SaveToCacheInvalidNumCache) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
// Create test HIDL model and compile.
const Model testModel = createTestModel();
if (checkEarlyTermination(testModel)) return;
@@ -584,7 +681,7 @@
}
}
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
// Create test HIDL model and compile.
const Model testModel = createTestModel();
if (checkEarlyTermination(testModel)) return;
@@ -664,7 +761,7 @@
}
}
-TEST_F(CompilationCachingTest, SaveToCacheInvalidNumFd) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) {
// Create test HIDL model and compile.
const Model testModel = createTestModel();
if (checkEarlyTermination(testModel)) return;
@@ -776,7 +873,7 @@
}
}
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidNumFd) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidNumFd) {
// Create test HIDL model and compile.
const Model testModel = createTestModel();
if (checkEarlyTermination(testModel)) return;
@@ -856,7 +953,7 @@
}
}
-TEST_F(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
// Create test HIDL model and compile.
const Model testModel = createTestModel();
if (checkEarlyTermination(testModel)) return;
@@ -914,7 +1011,7 @@
}
}
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
// Create test HIDL model and compile.
const Model testModel = createTestModel();
if (checkEarlyTermination(testModel)) return;
@@ -990,7 +1087,7 @@
constexpr uint32_t kLargeModelSize = 100;
constexpr uint32_t kNumIterationsTOCTOU = 100;
-TEST_F(CompilationCachingTest, SaveToCache_TOCTOU) {
+TEST_P(CompilationCachingTest, SaveToCache_TOCTOU) {
if (!mIsCachingSupported) return;
// Create test models and check if fully supported by the service.
@@ -1053,7 +1150,7 @@
}
}
-TEST_F(CompilationCachingTest, PrepareFromCache_TOCTOU) {
+TEST_P(CompilationCachingTest, PrepareFromCache_TOCTOU) {
if (!mIsCachingSupported) return;
// Create test models and check if fully supported by the service.
@@ -1116,7 +1213,7 @@
}
}
-TEST_F(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
+TEST_P(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
if (!mIsCachingSupported) return;
// Create test models and check if fully supported by the service.
@@ -1164,11 +1261,19 @@
}
}
-class CompilationCachingSecurityTest : public CompilationCachingTest,
- public ::testing::WithParamInterface<uint32_t> {
+static const auto kOperandTypeChoices =
+ ::testing::Values(OperandType::TENSOR_FLOAT32, OperandType::TENSOR_QUANT8_ASYMM);
+
+INSTANTIATE_TEST_CASE_P(TestCompilationCaching, CompilationCachingTest, kOperandTypeChoices);
+
+class CompilationCachingSecurityTest
+ : public CompilationCachingTestBase,
+ public ::testing::WithParamInterface<std::tuple<OperandType, uint32_t>> {
protected:
+ CompilationCachingSecurityTest() : CompilationCachingTestBase(std::get<0>(GetParam())) {}
+
void SetUp() {
- CompilationCachingTest::SetUp();
+ CompilationCachingTestBase::SetUp();
generator.seed(kSeed);
}
@@ -1254,7 +1359,7 @@
}
}
- const uint32_t kSeed = GetParam();
+ const uint32_t kSeed = std::get<1>(GetParam());
std::mt19937 generator;
};
@@ -1302,7 +1407,7 @@
}
INSTANTIATE_TEST_CASE_P(TestCompilationCaching, CompilationCachingSecurityTest,
- ::testing::Range(0U, 10U));
+ ::testing::Combine(kOperandTypeChoices, ::testing::Range(0U, 10U)));
} // namespace functional
} // namespace vts