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Merge "Consolidate NNAPI VTS utility code"

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Michael Butler 2019-09-11 19:03:06 +00:00 committed by Gerrit Code Review
commit 71cb010ba3
25 changed files with 278 additions and 476 deletions
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4
neuralnetworks/1.0/vts/functional/BasicTests.cpp
View file

@ -25,7 +25,7 @@ TEST_F(NeuralnetworksHidlTest, CreateDevice) {}
// status test
TEST_F(NeuralnetworksHidlTest, StatusTest) {
Return<DeviceStatus> status = device->getStatus();
Return<DeviceStatus> status = kDevice->getStatus();
ASSERT_TRUE(status.isOk());
EXPECT_EQ(DeviceStatus::AVAILABLE, static_cast<DeviceStatus>(status));
}
@ -33,7 +33,7 @@ TEST_F(NeuralnetworksHidlTest, StatusTest) {
// initialization
TEST_F(NeuralnetworksHidlTest, GetCapabilitiesTest) {
Return<void> ret =
device->getCapabilities([](ErrorStatus status, const Capabilities& capabilities) {
kDevice->getCapabilities([](ErrorStatus status, const Capabilities& capabilities) {
EXPECT_EQ(ErrorStatus::NONE, status);
EXPECT_LT(0.0f, capabilities.float32Performance.execTime);
EXPECT_LT(0.0f, capabilities.float32Performance.powerUsage);

55
neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
View file

@ -122,9 +122,15 @@ Model createModel(const TestModel& testModel) {
// Top level driver for models and examples generated by test_generator.py
// Test driver for those generated from ml/nn/runtime/test/spec
void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel) {
void Execute(const sp<IDevice>& device, const TestModel& testModel) {
const Model model = createModel(testModel);
const Request request = createRequest(testModel);
// Create IPreparedModel.
sp<IPreparedModel> preparedModel;
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
// Launch execution.
sp<ExecutionCallback> executionCallback = new ExecutionCallback();
Return<ErrorStatus> executionLaunchStatus = preparedModel->execute(request, executionCallback);
@ -143,53 +149,10 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo
}
// Tag for the generated tests
class GeneratedTest : public GeneratedTestBase {
protected:
void Execute(const TestModel& testModel) {
Model model = createModel(testModel);
// see if service can handle model
bool fullySupportsModel = false;
Return<void> supportedCall = device->getSupportedOperations(
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(supportedCall.isOk());
// launch prepare model
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
Return<ErrorStatus> prepareLaunchStatus =
device->prepareModel(model, preparedModelCallback);
ASSERT_TRUE(prepareLaunchStatus.isOk());
ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
// retrieve prepared model
preparedModelCallback->wait();
ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
// early termination if vendor service cannot fully prepare model
if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
ASSERT_EQ(nullptr, preparedModel.get());
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 "
"prepare model that it does not support."
<< std::endl;
GTEST_SKIP();
}
EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel.get());
EvaluatePreparedModel(preparedModel, testModel);
}
};
class GeneratedTest : public GeneratedTestBase {};
TEST_P(GeneratedTest, Test) {
Execute(*mTestModel);
Execute(kDevice, kTestModel);
}
INSTANTIATE_GENERATED_TEST(GeneratedTest,

20
neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h
View file

@ -25,32 +25,20 @@ namespace android::hardware::neuralnetworks::V1_0::vts::functional {
class GeneratedTestBase
: public NeuralnetworksHidlTest,
public ::testing::WithParamInterface<test_helper::TestModelManager::TestParam> {
public testing::WithParamInterface<test_helper::TestModelManager::TestParam> {
protected:
void SetUp() override {
NeuralnetworksHidlTest::SetUp();
ASSERT_NE(mTestModel, nullptr);
}
const test_helper::TestModel* mTestModel = GetParam().second;
const test_helper::TestModel& kTestModel = *GetParam().second;
};
#define INSTANTIATE_GENERATED_TEST(TestSuite, filter) \
INSTANTIATE_TEST_SUITE_P( \
TestGenerated, TestSuite, \
::testing::ValuesIn(::test_helper::TestModelManager::get().getTestModels(filter)), \
testing::ValuesIn(::test_helper::TestModelManager::get().getTestModels(filter)), \
[](const auto& info) { return info.param.first; })
// Tag for the validation tests, instantiated in VtsHalNeuralnetworks.cpp.
// TODO: Clean up the hierarchy for ValidationTest.
class ValidationTest : public GeneratedTestBase {
protected:
void validateEverything(const Model& model, const Request& request);
private:
void validateModel(const Model& model);
void validateRequest(const sp<IPreparedModel>& preparedModel, const Request& request);
};
class ValidationTest : public GeneratedTestBase {};
Model createModel(const ::test_helper::TestModel& testModel);

13
neuralnetworks/1.0/vts/functional/Utils.cpp
View file

@ -26,6 +26,7 @@
#include <hidlmemory/mapping.h>
#include <algorithm>
#include <iostream>
#include <vector>
namespace android::hardware::neuralnetworks {
@ -117,3 +118,15 @@ std::vector<TestBuffer> getOutputBuffers(const Request& request) {
}
} // namespace android::hardware::neuralnetworks
namespace android::hardware::neuralnetworks::V1_0 {
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus) {
return os << toString(errorStatus);
}
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus) {
return os << toString(deviceStatus);
}
} // namespace android::hardware::neuralnetworks::V1_0

44
neuralnetworks/1.0/vts/functional/ValidateModel.cpp
View file

@ -27,7 +27,7 @@ using implementation::PreparedModelCallback;
///////////////////////// UTILITY FUNCTIONS /////////////////////////
static void validateGetSupportedOperations(const sp<IDevice>& device, const std::string& message,
const V1_0::Model& model) {
const Model& model) {
SCOPED_TRACE(message + " [getSupportedOperations]");
Return<void> ret =
@ -38,7 +38,7 @@ static void validateGetSupportedOperations(const sp<IDevice>& device, const std:
}
static void validatePrepareModel(const sp<IDevice>& device, const std::string& message,
const V1_0::Model& model) {
const Model& model) {
SCOPED_TRACE(message + " [prepareModel]");
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
@ -57,7 +57,7 @@ static void validatePrepareModel(const sp<IDevice>& device, const std::string& m
// mutation to it to invalidate the model, then pass it to interface calls that
// use the model. Note that the model here is passed by value, and any mutation
// to the model does not leave this function.
static void validate(const sp<IDevice>& device, const std::string& message, V1_0::Model model,
static void validate(const sp<IDevice>& device, const std::string& message, Model model,
const std::function<void(Model*)>& mutation) {
mutation(&model);
validateGetSupportedOperations(device, message, model);
@ -113,7 +113,7 @@ static const int32_t invalidOperandTypes[] = {
static_cast<int32_t>(OperandType::TENSOR_OEM_BYTE) + 1, // upper bound OEM
};
static void mutateOperandTypeTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void mutateOperandTypeTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
for (int32_t invalidOperandType : invalidOperandTypes) {
const std::string message = "mutateOperandTypeTest: operand " +
@ -143,7 +143,7 @@ static uint32_t getInvalidRank(OperandType type) {
}
}
static void mutateOperandRankTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void mutateOperandRankTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
const uint32_t invalidRank = getInvalidRank(model.operands[operand].type);
const std::string message = "mutateOperandRankTest: operand " + std::to_string(operand) +
@ -172,7 +172,7 @@ static float getInvalidScale(OperandType type) {
}
}
static void mutateOperandScaleTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void mutateOperandScaleTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
const float invalidScale = getInvalidScale(model.operands[operand].type);
const std::string message = "mutateOperandScaleTest: operand " + std::to_string(operand) +
@ -200,7 +200,7 @@ static std::vector<int32_t> getInvalidZeroPoints(OperandType type) {
}
}
static void mutateOperandZeroPointTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void mutateOperandZeroPointTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
const std::vector<int32_t> invalidZeroPoints =
getInvalidZeroPoints(model.operands[operand].type);
@ -257,7 +257,7 @@ static void mutateOperand(Operand* operand, OperandType type) {
*operand = newOperand;
}
static bool mutateOperationOperandTypeSkip(size_t operand, const V1_0::Model& model) {
static bool mutateOperationOperandTypeSkip(size_t operand, const Model& model) {
// LSH_PROJECTION's second argument is allowed to have any type. This is the
// only operation that currently has a type that can be anything independent
// from any other type. Changing the operand type to any other type will
@ -271,7 +271,7 @@ static bool mutateOperationOperandTypeSkip(size_t operand, const V1_0::Model& mo
return false;
}
static void mutateOperationOperandTypeTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void mutateOperationOperandTypeTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
if (mutateOperationOperandTypeSkip(operand, model)) {
continue;
@ -302,7 +302,7 @@ static const int32_t invalidOperationTypes[] = {
static_cast<int32_t>(OperationType::OEM_OPERATION) + 1, // upper bound OEM
};
static void mutateOperationTypeTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void mutateOperationTypeTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
for (int32_t invalidOperationType : invalidOperationTypes) {
const std::string message = "mutateOperationTypeTest: operation " +
@ -318,8 +318,7 @@ static void mutateOperationTypeTest(const sp<IDevice>& device, const V1_0::Model
///////////////////////// VALIDATE MODEL OPERATION INPUT OPERAND INDEX /////////////////////////
static void mutateOperationInputOperandIndexTest(const sp<IDevice>& device,
const V1_0::Model& model) {
static void mutateOperationInputOperandIndexTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const uint32_t invalidOperand = model.operands.size();
for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) {
@ -335,8 +334,7 @@ static void mutateOperationInputOperandIndexTest(const sp<IDevice>& device,
///////////////////////// VALIDATE MODEL OPERATION OUTPUT OPERAND INDEX /////////////////////////
static void mutateOperationOutputOperandIndexTest(const sp<IDevice>& device,
const V1_0::Model& model) {
static void mutateOperationOutputOperandIndexTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const uint32_t invalidOperand = model.operands.size();
for (size_t output = 0; output < model.operations[operation].outputs.size(); ++output) {
@ -374,7 +372,7 @@ static void removeOperand(Model* model, uint32_t index) {
removeValueAndDecrementGreaterValues(&model->outputIndexes, index);
}
static void removeOperandTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void removeOperandTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
const std::string message = "removeOperandTest: operand " + std::to_string(operand);
validate(device, message, model,
@ -391,7 +389,7 @@ static void removeOperation(Model* model, uint32_t index) {
hidl_vec_removeAt(&model->operations, index);
}
static void removeOperationTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void removeOperationTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const std::string message = "removeOperationTest: operation " + std::to_string(operation);
validate(device, message, model,
@ -401,14 +399,14 @@ static void removeOperationTest(const sp<IDevice>& device, const V1_0::Model& mo
///////////////////////// REMOVE OPERATION INPUT /////////////////////////
static void removeOperationInputTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void removeOperationInputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) {
const V1_0::Operation& op = model.operations[operation];
const Operation& op = model.operations[operation];
// CONCATENATION has at least 2 inputs, with the last element being
// INT32. Skip this test if removing one of CONCATENATION's
// inputs still produces a valid model.
if (op.type == V1_0::OperationType::CONCATENATION && op.inputs.size() > 2 &&
if (op.type == OperationType::CONCATENATION && op.inputs.size() > 2 &&
input != op.inputs.size() - 1) {
continue;
}
@ -426,7 +424,7 @@ static void removeOperationInputTest(const sp<IDevice>& device, const V1_0::Mode
///////////////////////// REMOVE OPERATION OUTPUT /////////////////////////
static void removeOperationOutputTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void removeOperationOutputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
for (size_t output = 0; output < model.operations[operation].outputs.size(); ++output) {
const std::string message = "removeOperationOutputTest: operation " +
@ -447,7 +445,7 @@ static void removeOperationOutputTest(const sp<IDevice>& device, const V1_0::Mod
///////////////////////// ADD OPERATION INPUT /////////////////////////
static void addOperationInputTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void addOperationInputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const std::string message = "addOperationInputTest: operation " + std::to_string(operation);
validate(device, message, model, [operation](Model* model) {
@ -460,7 +458,7 @@ static void addOperationInputTest(const sp<IDevice>& device, const V1_0::Model&
///////////////////////// ADD OPERATION OUTPUT /////////////////////////
static void addOperationOutputTest(const sp<IDevice>& device, const V1_0::Model& model) {
static void addOperationOutputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const std::string message =
"addOperationOutputTest: operation " + std::to_string(operation);
@ -474,7 +472,7 @@ static void addOperationOutputTest(const sp<IDevice>& device, const V1_0::Model&
////////////////////////// ENTRY POINT //////////////////////////////
void ValidationTest::validateModel(const V1_0::Model& model) {
void validateModel(const sp<IDevice>& device, const Model& model) {
mutateOperandTypeTest(device, model);
mutateOperandRankTest(device, model);
mutateOperandScaleTest(device, model);

3
neuralnetworks/1.0/vts/functional/ValidateRequest.cpp
View file

@ -87,8 +87,7 @@ static void removeOutputTest(const sp<IPreparedModel>& preparedModel, const Requ
///////////////////////////// ENTRY POINT //////////////////////////////////
void ValidationTest::validateRequest(const sp<IPreparedModel>& preparedModel,
const Request& request) {
void validateRequest(const sp<IPreparedModel>& preparedModel, const Request& request) {
removeInputTest(preparedModel, request);
removeOutputTest(preparedModel, request);
}

69
neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
View file

@ -28,30 +28,32 @@ namespace android::hardware::neuralnetworks::V1_0::vts::functional {
using implementation::PreparedModelCallback;
static void createPreparedModel(const sp<IDevice>& device, const Model& model,
void createPreparedModel(const sp<IDevice>& device, const Model& model,
sp<IPreparedModel>* preparedModel) {
ASSERT_NE(nullptr, preparedModel);
*preparedModel = nullptr;
// see if service can handle model
bool fullySupportsModel = false;
Return<void> supportedOpsLaunchStatus = device->getSupportedOperations(
const Return<void> supportedCall = device->getSupportedOperations(
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());
ASSERT_TRUE(supportedCall.isOk());
// launch prepare model
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
const sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
const Return<ErrorStatus> prepareLaunchStatus =
device->prepareModel(model, preparedModelCallback);
ASSERT_TRUE(prepareLaunchStatus.isOk());
ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
// retrieve prepared model
preparedModelCallback->wait();
ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
const ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
*preparedModel = preparedModelCallback->getPreparedModel();
// The getSupportedOperations call returns a list of operations that are
@ -63,12 +65,12 @@ static void createPreparedModel(const sp<IDevice>& device, const Model& model,
// 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."
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 "
"prepare model that it does not support."
<< std::endl;
return;
GTEST_SKIP();
}
ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel->get());
@ -77,7 +79,7 @@ static void createPreparedModel(const sp<IDevice>& device, const Model& model,
// A class for test environment setup
NeuralnetworksHidlEnvironment* NeuralnetworksHidlEnvironment::getInstance() {
// This has to return a "new" object because it is freed inside
// ::testing::AddGlobalTestEnvironment when the gtest is being torn down
// testing::AddGlobalTestEnvironment when the gtest is being torn down
static NeuralnetworksHidlEnvironment* instance = new NeuralnetworksHidlEnvironment();
return instance;
}
@ -88,28 +90,29 @@ void NeuralnetworksHidlEnvironment::registerTestServices() {
// The main test class for NEURALNETWORK HIDL HAL.
void NeuralnetworksHidlTest::SetUp() {
::testing::VtsHalHidlTargetTestBase::SetUp();
testing::VtsHalHidlTargetTestBase::SetUp();
#ifdef PRESUBMIT_NOT_VTS
const std::string name =
NeuralnetworksHidlEnvironment::getInstance()->getServiceName<IDevice>();
const std::string sampleDriver = "sample-";
if (device == nullptr && name.substr(0, sampleDriver.size()) == sampleDriver) {
if (kDevice == nullptr && name.substr(0, sampleDriver.size()) == sampleDriver) {
GTEST_SKIP();
}
#endif // PRESUBMIT_NOT_VTS
ASSERT_NE(nullptr, device.get());
ASSERT_NE(nullptr, kDevice.get());
}
void NeuralnetworksHidlTest::TearDown() {
::testing::VtsHalHidlTargetTestBase::TearDown();
}
// Forward declaration from ValidateModel.cpp
void validateModel(const sp<IDevice>& device, const Model& model);
// Forward declaration from ValidateRequest.cpp
void validateRequest(const sp<IPreparedModel>& preparedModel, const Request& request);
void ValidationTest::validateEverything(const Model& model, const Request& request) {
validateModel(model);
void validateEverything(const sp<IDevice>& device, const Model& model, const Request& request) {
validateModel(device, model);
// create IPreparedModel
// Create IPreparedModel.
sp<IPreparedModel> preparedModel;
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
@ -118,33 +121,21 @@ void ValidationTest::validateEverything(const Model& model, const Request& reque
}
TEST_P(ValidationTest, Test) {
const Model model = createModel(*mTestModel);
const Request request = createRequest(*mTestModel);
ASSERT_FALSE(mTestModel->expectFailure);
validateEverything(model, request);
const Model model = createModel(kTestModel);
const Request request = createRequest(kTestModel);
ASSERT_FALSE(kTestModel.expectFailure);
validateEverything(kDevice, model, request);
}
INSTANTIATE_GENERATED_TEST(ValidationTest, [](const test_helper::TestModel&) { return true; });
} // namespace android::hardware::neuralnetworks::V1_0::vts::functional
namespace android::hardware::neuralnetworks::V1_0 {
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus) {
return os << toString(errorStatus);
}
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus) {
return os << toString(deviceStatus);
}
} // namespace android::hardware::neuralnetworks::V1_0
using android::hardware::neuralnetworks::V1_0::vts::functional::NeuralnetworksHidlEnvironment;
int main(int argc, char** argv) {
::testing::AddGlobalTestEnvironment(NeuralnetworksHidlEnvironment::getInstance());
::testing::InitGoogleTest(&argc, argv);
testing::AddGlobalTestEnvironment(NeuralnetworksHidlEnvironment::getInstance());
testing::InitGoogleTest(&argc, argv);
NeuralnetworksHidlEnvironment::getInstance()->init(&argc, argv);
int status = RUN_ALL_TESTS();

24
neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
View file

@ -25,15 +25,11 @@
#include <android-base/macros.h>
#include <gtest/gtest.h>
#include <iostream>
#include <vector>
#include "TestHarness.h"
namespace android::hardware::neuralnetworks::V1_0::vts::functional {
// A class for test environment setup
class NeuralnetworksHidlEnvironment : public ::testing::VtsHalHidlTargetTestEnvBase {
class NeuralnetworksHidlEnvironment : public testing::VtsHalHidlTargetTestEnvBase {
DISALLOW_COPY_AND_ASSIGN(NeuralnetworksHidlEnvironment);
NeuralnetworksHidlEnvironment() = default;
@ -43,27 +39,23 @@ class NeuralnetworksHidlEnvironment : public ::testing::VtsHalHidlTargetTestEnvB
};
// The main test class for NEURALNETWORKS HIDL HAL.
class NeuralnetworksHidlTest : public ::testing::VtsHalHidlTargetTestBase {
class NeuralnetworksHidlTest : public testing::VtsHalHidlTargetTestBase {
DISALLOW_COPY_AND_ASSIGN(NeuralnetworksHidlTest);
public:
NeuralnetworksHidlTest() = default;
void SetUp() override;
void TearDown() override;
protected:
const sp<IDevice> device = ::testing::VtsHalHidlTargetTestBase::getService<IDevice>(
const sp<IDevice> kDevice = testing::VtsHalHidlTargetTestBase::getService<IDevice>(
NeuralnetworksHidlEnvironment::getInstance());
};
// Create an IPreparedModel object. If the model cannot be prepared,
// "preparedModel" will be nullptr instead.
void createPreparedModel(const sp<IDevice>& device, const Model& model,
sp<IPreparedModel>* preparedModel);
} // namespace android::hardware::neuralnetworks::V1_0::vts::functional
namespace android::hardware::neuralnetworks::V1_0 {
// pretty-print values for error messages
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus);
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus);
} // namespace android::hardware::neuralnetworks::V1_0
#endif // ANDROID_HARDWARE_NEURALNETWORKS_V1_0_VTS_HAL_NEURALNETWORKS_H

9
neuralnetworks/1.0/vts/functional/include/1.0/Utils.h
View file

@ -20,6 +20,7 @@
#include <android-base/logging.h>
#include <android/hardware/neuralnetworks/1.0/types.h>
#include <algorithm>
#include <iosfwd>
#include <vector>
#include "TestHarness.h"
@ -52,4 +53,12 @@ inline uint32_t hidl_vec_push_back(hidl_vec<Type>* vec, const Type& value) {
} // namespace android::hardware::neuralnetworks
namespace android::hardware::neuralnetworks::V1_0 {
// pretty-print values for error messages
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus);
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus);
} // namespace android::hardware::neuralnetworks::V1_0
#endif // ANDROID_HARDWARE_NEURALNETWORKS_V1_0_UTILS_H

4
neuralnetworks/1.1/vts/functional/BasicTests.cpp
View file

@ -28,7 +28,7 @@ TEST_F(NeuralnetworksHidlTest, CreateDevice) {}
// status test
TEST_F(NeuralnetworksHidlTest, StatusTest) {
Return<DeviceStatus> status = device->getStatus();
Return<DeviceStatus> status = kDevice->getStatus();
ASSERT_TRUE(status.isOk());
EXPECT_EQ(DeviceStatus::AVAILABLE, static_cast<DeviceStatus>(status));
}
@ -36,7 +36,7 @@ TEST_F(NeuralnetworksHidlTest, StatusTest) {
// initialization
TEST_F(NeuralnetworksHidlTest, GetCapabilitiesTest) {
Return<void> ret =
device->getCapabilities_1_1([](ErrorStatus status, const Capabilities& capabilities) {
kDevice->getCapabilities_1_1([](ErrorStatus status, const Capabilities& capabilities) {
EXPECT_EQ(ErrorStatus::NONE, status);
EXPECT_LT(0.0f, capabilities.float32Performance.execTime);
EXPECT_LT(0.0f, capabilities.float32Performance.powerUsage);

55
neuralnetworks/1.1/vts/functional/GeneratedTestHarness.cpp
View file

@ -130,9 +130,15 @@ Model createModel(const TestModel& testModel) {
// Top level driver for models and examples generated by test_generator.py
// Test driver for those generated from ml/nn/runtime/test/spec
void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel) {
void Execute(const sp<IDevice>& device, const TestModel& testModel) {
const Model model = createModel(testModel);
const Request request = createRequest(testModel);
// Create IPreparedModel.
sp<IPreparedModel> preparedModel;
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
// Launch execution.
sp<ExecutionCallback> executionCallback = new ExecutionCallback();
Return<ErrorStatus> executionLaunchStatus = preparedModel->execute(request, executionCallback);
@ -151,53 +157,10 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo
}
// Tag for the generated tests
class GeneratedTest : public GeneratedTestBase {
protected:
void Execute(const TestModel& testModel) {
Model model = createModel(testModel);
// see if service can handle model
bool fullySupportsModel = false;
Return<void> supportedCall = device->getSupportedOperations_1_1(
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(supportedCall.isOk());
// launch prepare model
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(
model, ExecutionPreference::FAST_SINGLE_ANSWER, preparedModelCallback);
ASSERT_TRUE(prepareLaunchStatus.isOk());
ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
// retrieve prepared model
preparedModelCallback->wait();
ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
// early termination if vendor service cannot fully prepare model
if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
ASSERT_EQ(nullptr, preparedModel.get());
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 "
"prepare model that it does not support."
<< std::endl;
GTEST_SKIP();
}
EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel.get());
EvaluatePreparedModel(preparedModel, testModel);
}
};
class GeneratedTest : public GeneratedTestBase {};
TEST_P(GeneratedTest, Test) {
Execute(*mTestModel);
Execute(kDevice, kTestModel);
}
INSTANTIATE_GENERATED_TEST(GeneratedTest,

21
neuralnetworks/1.1/vts/functional/GeneratedTestHarness.h
View file

@ -25,33 +25,20 @@ namespace android::hardware::neuralnetworks::V1_1::vts::functional {
class GeneratedTestBase
: public NeuralnetworksHidlTest,
public ::testing::WithParamInterface<test_helper::TestModelManager::TestParam> {
public testing::WithParamInterface<test_helper::TestModelManager::TestParam> {
protected:
void SetUp() override {
NeuralnetworksHidlTest::SetUp();
ASSERT_NE(mTestModel, nullptr);
}
const test_helper::TestModel* mTestModel = GetParam().second;
const test_helper::TestModel& kTestModel = *GetParam().second;
};
#define INSTANTIATE_GENERATED_TEST(TestSuite, filter) \
INSTANTIATE_TEST_SUITE_P( \
TestGenerated, TestSuite, \
::testing::ValuesIn(::test_helper::TestModelManager::get().getTestModels(filter)), \
testing::ValuesIn(::test_helper::TestModelManager::get().getTestModels(filter)), \
[](const auto& info) { return info.param.first; })
// Tag for the validation tests, instantiated in VtsHalNeuralnetworks.cpp.
// TODO: Clean up the hierarchy for ValidationTest.
class ValidationTest : public GeneratedTestBase {
protected:
void validateEverything(const Model& model, const V1_0::Request& request);
private:
void validateModel(const Model& model);
void validateRequest(const sp<V1_0::IPreparedModel>& preparedModel,
const V1_0::Request& request);
};
class ValidationTest : public GeneratedTestBase {};
Model createModel(const ::test_helper::TestModel& testModel);

46
neuralnetworks/1.1/vts/functional/ValidateModel.cpp
View file

@ -33,7 +33,7 @@ using V1_0::implementation::PreparedModelCallback;
///////////////////////// UTILITY FUNCTIONS /////////////////////////
static void validateGetSupportedOperations(const sp<IDevice>& device, const std::string& message,
const V1_1::Model& model) {
const Model& model) {
SCOPED_TRACE(message + " [getSupportedOperations_1_1]");
Return<void> ret = device->getSupportedOperations_1_1(
@ -44,7 +44,7 @@ static void validateGetSupportedOperations(const sp<IDevice>& device, const std:
}
static void validatePrepareModel(const sp<IDevice>& device, const std::string& message,
const V1_1::Model& model, ExecutionPreference preference) {
const Model& model, ExecutionPreference preference) {
SCOPED_TRACE(message + " [prepareModel_1_1]");
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
@ -70,7 +70,7 @@ static bool validExecutionPreference(ExecutionPreference preference) {
// mutation to it to invalidate the model, then pass it to interface calls that
// use the model. Note that the model here is passed by value, and any mutation
// to the model does not leave this function.
static void validate(const sp<IDevice>& device, const std::string& message, V1_1::Model model,
static void validate(const sp<IDevice>& device, const std::string& message, Model model,
const std::function<void(Model*)>& mutation,
ExecutionPreference preference = ExecutionPreference::FAST_SINGLE_ANSWER) {
mutation(&model);
@ -109,7 +109,7 @@ static const int32_t invalidOperandTypes[] = {
static_cast<int32_t>(OperandType::TENSOR_OEM_BYTE) + 1, // upper bound OEM
};
static void mutateOperandTypeTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void mutateOperandTypeTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
for (int32_t invalidOperandType : invalidOperandTypes) {
const std::string message = "mutateOperandTypeTest: operand " +
@ -139,7 +139,7 @@ static uint32_t getInvalidRank(OperandType type) {
}
}
static void mutateOperandRankTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void mutateOperandRankTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
const uint32_t invalidRank = getInvalidRank(model.operands[operand].type);
const std::string message = "mutateOperandRankTest: operand " + std::to_string(operand) +
@ -168,7 +168,7 @@ static float getInvalidScale(OperandType type) {
}
}
static void mutateOperandScaleTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void mutateOperandScaleTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
const float invalidScale = getInvalidScale(model.operands[operand].type);
const std::string message = "mutateOperandScaleTest: operand " + std::to_string(operand) +
@ -196,7 +196,7 @@ static std::vector<int32_t> getInvalidZeroPoints(OperandType type) {
}
}
static void mutateOperandZeroPointTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void mutateOperandZeroPointTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
const std::vector<int32_t> invalidZeroPoints =
getInvalidZeroPoints(model.operands[operand].type);
@ -253,7 +253,7 @@ static void mutateOperand(Operand* operand, OperandType type) {
*operand = newOperand;
}
static bool mutateOperationOperandTypeSkip(size_t operand, const V1_1::Model& model) {
static bool mutateOperationOperandTypeSkip(size_t operand, const Model& model) {
// LSH_PROJECTION's second argument is allowed to have any type. This is the
// only operation that currently has a type that can be anything independent
// from any other type. Changing the operand type to any other type will
@ -267,7 +267,7 @@ static bool mutateOperationOperandTypeSkip(size_t operand, const V1_1::Model& mo
return false;
}
static void mutateOperationOperandTypeTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void mutateOperationOperandTypeTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
if (mutateOperationOperandTypeSkip(operand, model)) {
continue;
@ -298,7 +298,7 @@ static const int32_t invalidOperationTypes[] = {
static_cast<int32_t>(OperationType::OEM_OPERATION) + 1, // upper bound OEM
};
static void mutateOperationTypeTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void mutateOperationTypeTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
for (int32_t invalidOperationType : invalidOperationTypes) {
const std::string message = "mutateOperationTypeTest: operation " +
@ -314,8 +314,7 @@ static void mutateOperationTypeTest(const sp<IDevice>& device, const V1_1::Model
///////////////////////// VALIDATE MODEL OPERATION INPUT OPERAND INDEX /////////////////////////
static void mutateOperationInputOperandIndexTest(const sp<IDevice>& device,
const V1_1::Model& model) {
static void mutateOperationInputOperandIndexTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const uint32_t invalidOperand = model.operands.size();
for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) {
@ -331,8 +330,7 @@ static void mutateOperationInputOperandIndexTest(const sp<IDevice>& device,
///////////////////////// VALIDATE MODEL OPERATION OUTPUT OPERAND INDEX /////////////////////////
static void mutateOperationOutputOperandIndexTest(const sp<IDevice>& device,
const V1_1::Model& model) {
static void mutateOperationOutputOperandIndexTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const uint32_t invalidOperand = model.operands.size();
for (size_t output = 0; output < model.operations[operation].outputs.size(); ++output) {
@ -370,7 +368,7 @@ static void removeOperand(Model* model, uint32_t index) {
removeValueAndDecrementGreaterValues(&model->outputIndexes, index);
}
static void removeOperandTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void removeOperandTest(const sp<IDevice>& device, const Model& model) {
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
const std::string message = "removeOperandTest: operand " + std::to_string(operand);
validate(device, message, model,
@ -387,7 +385,7 @@ static void removeOperation(Model* model, uint32_t index) {
hidl_vec_removeAt(&model->operations, index);
}
static void removeOperationTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void removeOperationTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const std::string message = "removeOperationTest: operation " + std::to_string(operation);
validate(device, message, model,
@ -397,14 +395,14 @@ static void removeOperationTest(const sp<IDevice>& device, const V1_1::Model& mo
///////////////////////// REMOVE OPERATION INPUT /////////////////////////
static void removeOperationInputTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void removeOperationInputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) {
const V1_1::Operation& op = model.operations[operation];
const Operation& op = model.operations[operation];
// CONCATENATION has at least 2 inputs, with the last element being
// INT32. Skip this test if removing one of CONCATENATION's
// inputs still produces a valid model.
if (op.type == V1_1::OperationType::CONCATENATION && op.inputs.size() > 2 &&
if (op.type == OperationType::CONCATENATION && op.inputs.size() > 2 &&
input != op.inputs.size() - 1) {
continue;
}
@ -422,7 +420,7 @@ static void removeOperationInputTest(const sp<IDevice>& device, const V1_1::Mode
///////////////////////// REMOVE OPERATION OUTPUT /////////////////////////
static void removeOperationOutputTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void removeOperationOutputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
for (size_t output = 0; output < model.operations[operation].outputs.size(); ++output) {
const std::string message = "removeOperationOutputTest: operation " +
@ -443,7 +441,7 @@ static void removeOperationOutputTest(const sp<IDevice>& device, const V1_1::Mod
///////////////////////// ADD OPERATION INPUT /////////////////////////
static void addOperationInputTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void addOperationInputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const std::string message = "addOperationInputTest: operation " + std::to_string(operation);
validate(device, message, model, [operation](Model* model) {
@ -456,7 +454,7 @@ static void addOperationInputTest(const sp<IDevice>& device, const V1_1::Model&
///////////////////////// ADD OPERATION OUTPUT /////////////////////////
static void addOperationOutputTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void addOperationOutputTest(const sp<IDevice>& device, const Model& model) {
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
const std::string message =
"addOperationOutputTest: operation " + std::to_string(operation);
@ -475,7 +473,7 @@ static const int32_t invalidExecutionPreferences[] = {
static_cast<int32_t>(ExecutionPreference::SUSTAINED_SPEED) + 1, // upper bound
};
static void mutateExecutionPreferenceTest(const sp<IDevice>& device, const V1_1::Model& model) {
static void mutateExecutionPreferenceTest(const sp<IDevice>& device, const Model& model) {
for (int32_t preference : invalidExecutionPreferences) {
const std::string message =
"mutateExecutionPreferenceTest: preference " + std::to_string(preference);
@ -487,7 +485,7 @@ static void mutateExecutionPreferenceTest(const sp<IDevice>& device, const V1_1:
////////////////////////// ENTRY POINT //////////////////////////////
void ValidationTest::validateModel(const V1_1::Model& model) {
void validateModel(const sp<IDevice>& device, const Model& model) {
mutateOperandTypeTest(device, model);
mutateOperandRankTest(device, model);
mutateOperandScaleTest(device, model);

3
neuralnetworks/1.1/vts/functional/ValidateRequest.cpp
View file

@ -71,8 +71,7 @@ static void removeOutputTest(const sp<IPreparedModel>& preparedModel, const Requ
///////////////////////////// ENTRY POINT //////////////////////////////////
void ValidationTest::validateRequest(const sp<IPreparedModel>& preparedModel,
const Request& request) {
void validateRequest(const sp<IPreparedModel>& preparedModel, const Request& request) {
removeInputTest(preparedModel, request);
removeOutputTest(preparedModel, request);
}

74
neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
View file

@ -31,31 +31,32 @@ using V1_0::IPreparedModel;
using V1_0::Request;
using V1_0::implementation::PreparedModelCallback;
static void createPreparedModel(const sp<IDevice>& device, const Model& model,
void createPreparedModel(const sp<IDevice>& device, const Model& model,
sp<IPreparedModel>* preparedModel) {
ASSERT_NE(nullptr, preparedModel);
*preparedModel = nullptr;
// see if service can handle model
bool fullySupportsModel = false;
Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_1(
const Return<void> supportedCall = device->getSupportedOperations_1_1(
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());
ASSERT_TRUE(supportedCall.isOk());
// launch prepare model
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(
const sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
const Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(
model, ExecutionPreference::FAST_SINGLE_ANSWER, preparedModelCallback);
ASSERT_TRUE(prepareLaunchStatus.isOk());
ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
// retrieve prepared model
preparedModelCallback->wait();
ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
const ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
*preparedModel = preparedModelCallback->getPreparedModel();
// The getSupportedOperations_1_1 call returns a list of operations that are
@ -67,12 +68,12 @@ static void createPreparedModel(const sp<IDevice>& device, const Model& model,
// 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."
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 "
"prepare model that it does not support."
<< std::endl;
return;
GTEST_SKIP();
}
ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel->get());
@ -81,7 +82,7 @@ static void createPreparedModel(const sp<IDevice>& device, const Model& model,
// A class for test environment setup
NeuralnetworksHidlEnvironment* NeuralnetworksHidlEnvironment::getInstance() {
// This has to return a "new" object because it is freed inside
// ::testing::AddGlobalTestEnvironment when the gtest is being torn down
// testing::AddGlobalTestEnvironment when the gtest is being torn down
static NeuralnetworksHidlEnvironment* instance = new NeuralnetworksHidlEnvironment();
return instance;
}
@ -92,65 +93,52 @@ void NeuralnetworksHidlEnvironment::registerTestServices() {
// The main test class for NEURALNETWORK HIDL HAL.
void NeuralnetworksHidlTest::SetUp() {
::testing::VtsHalHidlTargetTestBase::SetUp();
testing::VtsHalHidlTargetTestBase::SetUp();
#ifdef PRESUBMIT_NOT_VTS
const std::string name =
NeuralnetworksHidlEnvironment::getInstance()->getServiceName<IDevice>();
const std::string sampleDriver = "sample-";
if (device == nullptr && name.substr(0, sampleDriver.size()) == sampleDriver) {
if (kDevice == nullptr && name.substr(0, sampleDriver.size()) == sampleDriver) {
GTEST_SKIP();
}
#endif // PRESUBMIT_NOT_VTS
ASSERT_NE(nullptr, device.get());
ASSERT_NE(nullptr, kDevice.get());
}
void NeuralnetworksHidlTest::TearDown() {
::testing::VtsHalHidlTargetTestBase::TearDown();
}
// Forward declaration from ValidateModel.cpp
void validateModel(const sp<IDevice>& device, const Model& model);
// Forward declaration from ValidateRequest.cpp
void validateRequest(const sp<V1_0::IPreparedModel>& preparedModel, const V1_0::Request& request);
void ValidationTest::validateEverything(const Model& model, const Request& request) {
validateModel(model);
void validateEverything(const sp<IDevice>& device, const Model& model, const Request& request) {
validateModel(device, model);
// create IPreparedModel
// Create IPreparedModel.
sp<IPreparedModel> preparedModel;
ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
if (preparedModel == nullptr) {
return;
}
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
validateRequest(preparedModel, request);
}
TEST_P(ValidationTest, Test) {
const Model model = createModel(*mTestModel);
const Request request = createRequest(*mTestModel);
ASSERT_FALSE(mTestModel->expectFailure);
validateEverything(model, request);
const Model model = createModel(kTestModel);
const Request request = createRequest(kTestModel);
ASSERT_FALSE(kTestModel.expectFailure);
validateEverything(kDevice, model, request);
}
INSTANTIATE_GENERATED_TEST(ValidationTest, [](const test_helper::TestModel&) { return true; });
} // namespace android::hardware::neuralnetworks::V1_1::vts::functional
namespace android::hardware::neuralnetworks::V1_0 {
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus) {
return os << toString(errorStatus);
}
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus) {
return os << toString(deviceStatus);
}
} // namespace android::hardware::neuralnetworks::V1_0
using android::hardware::neuralnetworks::V1_1::vts::functional::NeuralnetworksHidlEnvironment;
int main(int argc, char** argv) {
::testing::AddGlobalTestEnvironment(NeuralnetworksHidlEnvironment::getInstance());
::testing::InitGoogleTest(&argc, argv);
testing::AddGlobalTestEnvironment(NeuralnetworksHidlEnvironment::getInstance());
testing::InitGoogleTest(&argc, argv);
NeuralnetworksHidlEnvironment::getInstance()->init(&argc, argv);
int status = RUN_ALL_TESTS();

24
neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
View file

@ -26,15 +26,11 @@
#include <android-base/macros.h>
#include <gtest/gtest.h>
#include <iostream>
#include <vector>
#include "TestHarness.h"
namespace android::hardware::neuralnetworks::V1_1::vts::functional {
// A class for test environment setup
class NeuralnetworksHidlEnvironment : public ::testing::VtsHalHidlTargetTestEnvBase {
class NeuralnetworksHidlEnvironment : public testing::VtsHalHidlTargetTestEnvBase {
DISALLOW_COPY_AND_ASSIGN(NeuralnetworksHidlEnvironment);
NeuralnetworksHidlEnvironment() = default;
@ -44,27 +40,23 @@ class NeuralnetworksHidlEnvironment : public ::testing::VtsHalHidlTargetTestEnvB
};
// The main test class for NEURALNETWORKS HIDL HAL.
class NeuralnetworksHidlTest : public ::testing::VtsHalHidlTargetTestBase {
class NeuralnetworksHidlTest : public testing::VtsHalHidlTargetTestBase {
DISALLOW_COPY_AND_ASSIGN(NeuralnetworksHidlTest);
public:
NeuralnetworksHidlTest() = default;
void SetUp() override;
void TearDown() override;
protected:
const sp<IDevice> device = ::testing::VtsHalHidlTargetTestBase::getService<IDevice>(
const sp<IDevice> kDevice = testing::VtsHalHidlTargetTestBase::getService<IDevice>(
NeuralnetworksHidlEnvironment::getInstance());
};
// Create an IPreparedModel object. If the model cannot be prepared,
// "preparedModel" will be nullptr instead.
void createPreparedModel(const sp<IDevice>& device, const Model& model,
sp<V1_0::IPreparedModel>* preparedModel);
} // namespace android::hardware::neuralnetworks::V1_1::vts::functional
namespace android::hardware::neuralnetworks::V1_0 {
// pretty-print values for error messages
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus);
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus);
} // namespace android::hardware::neuralnetworks::V1_0
#endif // ANDROID_HARDWARE_NEURALNETWORKS_V1_1_VTS_HAL_NEURALNETWORKS_H

13
neuralnetworks/1.2/vts/functional/BasicTests.cpp
View file

@ -29,7 +29,7 @@ TEST_F(NeuralnetworksHidlTest, CreateDevice) {}
// status test
TEST_F(NeuralnetworksHidlTest, StatusTest) {
Return<DeviceStatus> status = device->getStatus();
Return<DeviceStatus> status = kDevice->getStatus();
ASSERT_TRUE(status.isOk());
EXPECT_EQ(DeviceStatus::AVAILABLE, static_cast<DeviceStatus>(status));
}
@ -37,7 +37,7 @@ TEST_F(NeuralnetworksHidlTest, StatusTest) {
// initialization
TEST_F(NeuralnetworksHidlTest, GetCapabilitiesTest) {
using OperandPerformance = Capabilities::OperandPerformance;
Return<void> ret = device->getCapabilities_1_2([](ErrorStatus status,
Return<void> ret = kDevice->getCapabilities_1_2([](ErrorStatus status,
const Capabilities& capabilities) {
EXPECT_EQ(ErrorStatus::NONE, status);
@ -61,7 +61,8 @@ TEST_F(NeuralnetworksHidlTest, GetCapabilitiesTest) {
// device version test
TEST_F(NeuralnetworksHidlTest, GetDeviceVersionStringTest) {
Return<void> ret = device->getVersionString([](ErrorStatus status, const hidl_string& version) {
Return<void> ret =
kDevice->getVersionString([](ErrorStatus status, const hidl_string& version) {
EXPECT_EQ(ErrorStatus::NONE, status);
EXPECT_LT(0, version.size());
});
@ -70,7 +71,7 @@ TEST_F(NeuralnetworksHidlTest, GetDeviceVersionStringTest) {
// device type test
TEST_F(NeuralnetworksHidlTest, GetDeviceTypeTest) {
Return<void> ret = device->getType([](ErrorStatus status, DeviceType type) {
Return<void> ret = kDevice->getType([](ErrorStatus status, DeviceType type) {
EXPECT_EQ(ErrorStatus::NONE, status);
EXPECT_TRUE(type == DeviceType::OTHER || type == DeviceType::CPU ||
type == DeviceType::GPU || type == DeviceType::ACCELERATOR);
@ -80,7 +81,7 @@ TEST_F(NeuralnetworksHidlTest, GetDeviceTypeTest) {
// device supported extensions test
TEST_F(NeuralnetworksHidlTest, GetDeviceSupportedExtensionsTest) {
Return<void> ret = device->getSupportedExtensions(
Return<void> ret = kDevice->getSupportedExtensions(
[](ErrorStatus status, const hidl_vec<Extension>& extensions) {
EXPECT_EQ(ErrorStatus::NONE, status);
for (auto& extension : extensions) {
@ -101,7 +102,7 @@ TEST_F(NeuralnetworksHidlTest, GetDeviceSupportedExtensionsTest) {
// getNumberOfCacheFilesNeeded test
TEST_F(NeuralnetworksHidlTest, getNumberOfCacheFilesNeeded) {
Return<void> ret = device->getNumberOfCacheFilesNeeded(
Return<void> ret = kDevice->getNumberOfCacheFilesNeeded(
[](ErrorStatus status, uint32_t numModelCache, uint32_t numDataCache) {
EXPECT_EQ(ErrorStatus::NONE, status);
EXPECT_LE(numModelCache,

22
neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
View file

@ -223,7 +223,7 @@ class CompilationCachingTestBase : public NeuralnetworksHidlTest {
void SetUp() override {
NeuralnetworksHidlTest::SetUp();
ASSERT_NE(device.get(), nullptr);
ASSERT_NE(kDevice.get(), nullptr);
// Create cache directory. The cache directory and a temporary cache file is always created
// to test the behavior of prepareModelFromCache, even when caching is not supported.
@ -233,7 +233,7 @@ class CompilationCachingTestBase : public NeuralnetworksHidlTest {
mCacheDir = cacheDir;
mCacheDir.push_back('/');
Return<void> ret = device->getNumberOfCacheFilesNeeded(
Return<void> ret = kDevice->getNumberOfCacheFilesNeeded(
[this](ErrorStatus status, uint32_t numModelCache, uint32_t numDataCache) {
EXPECT_EQ(ErrorStatus::NONE, status);
mNumModelCache = numModelCache;
@ -267,7 +267,7 @@ class CompilationCachingTestBase : public NeuralnetworksHidlTest {
void TearDown() override {
// If the test passes, remove the tmp directory. Otherwise, keep it for debugging purposes.
if (!::testing::Test::HasFailure()) {
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);
@ -300,7 +300,7 @@ class CompilationCachingTestBase : public NeuralnetworksHidlTest {
// See if the service can handle the model.
bool isModelFullySupported(const Model& model) {
bool fullySupportsModel = false;
Return<void> supportedCall = device->getSupportedOperations_1_2(
Return<void> supportedCall = kDevice->getSupportedOperations_1_2(
model,
[&fullySupportsModel, &model](ErrorStatus status, const hidl_vec<bool>& supported) {
ASSERT_EQ(ErrorStatus::NONE, status);
@ -321,8 +321,8 @@ class CompilationCachingTestBase : public NeuralnetworksHidlTest {
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
hidl_array<uint8_t, sizeof(mToken)> cacheToken(mToken);
Return<ErrorStatus> prepareLaunchStatus =
device->prepareModel_1_2(model, ExecutionPreference::FAST_SINGLE_ANSWER, modelCache,
dataCache, cacheToken, preparedModelCallback);
kDevice->prepareModel_1_2(model, ExecutionPreference::FAST_SINGLE_ANSWER,
modelCache, dataCache, cacheToken, preparedModelCallback);
ASSERT_TRUE(prepareLaunchStatus.isOk());
ASSERT_EQ(static_cast<ErrorStatus>(prepareLaunchStatus), ErrorStatus::NONE);
@ -365,7 +365,7 @@ class CompilationCachingTestBase : public NeuralnetworksHidlTest {
// Launch prepare model from cache.
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
hidl_array<uint8_t, sizeof(mToken)> cacheToken(mToken);
Return<ErrorStatus> prepareLaunchStatus = device->prepareModelFromCache(
Return<ErrorStatus> prepareLaunchStatus = kDevice->prepareModelFromCache(
modelCache, dataCache, cacheToken, preparedModelCallback);
ASSERT_TRUE(prepareLaunchStatus.isOk());
if (static_cast<ErrorStatus>(prepareLaunchStatus) != ErrorStatus::NONE) {
@ -405,7 +405,7 @@ class CompilationCachingTestBase : public NeuralnetworksHidlTest {
// 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> {
public testing::WithParamInterface<OperandType> {
protected:
CompilationCachingTest() : CompilationCachingTestBase(GetParam()) {}
};
@ -1193,13 +1193,13 @@ TEST_P(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
}
static const auto kOperandTypeChoices =
::testing::Values(OperandType::TENSOR_FLOAT32, OperandType::TENSOR_QUANT8_ASYMM);
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>> {
public testing::WithParamInterface<std::tuple<OperandType, uint32_t>> {
protected:
CompilationCachingSecurityTest() : CompilationCachingTestBase(std::get<0>(GetParam())) {}
@ -1339,6 +1339,6 @@ TEST_P(CompilationCachingSecurityTest, WrongToken) {
}
INSTANTIATE_TEST_CASE_P(TestCompilationCaching, CompilationCachingSecurityTest,
::testing::Combine(kOperandTypeChoices, ::testing::Range(0U, 10U)));
testing::Combine(kOperandTypeChoices, testing::Range(0U, 10U)));
} // namespace android::hardware::neuralnetworks::V1_2::vts::functional

65
neuralnetworks/1.2/vts/functional/GeneratedTestHarness.cpp
View file

@ -358,74 +358,31 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo
}
}
void PrepareModel(const sp<IDevice>& device, const Model& model,
sp<IPreparedModel>* preparedModel) {
// see if service can handle model
bool fullySupportsModel = false;
Return<void> supportedCall = 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(supportedCall.isOk());
// launch prepare model
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
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();
sp<V1_0::IPreparedModel> preparedModelV1_0 = preparedModelCallback->getPreparedModel();
*preparedModel = IPreparedModel::castFrom(preparedModelV1_0).withDefault(nullptr);
// early termination if vendor service cannot fully prepare model
if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
ASSERT_EQ(nullptr, preparedModel->get());
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 "
"prepare model that it does not support."
<< std::endl;
return;
}
EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel->get());
}
// Tag for the generated tests
class GeneratedTest : public GeneratedTestBase {
protected:
void Execute(const TestModel& testModel, bool testDynamicOutputShape) {
void Execute(const sp<IDevice>& device, const TestModel& testModel, bool testDynamicOutputShape) {
Model model = createModel(testModel);
if (testDynamicOutputShape) {
makeOutputDimensionsUnspecified(&model);
}
sp<IPreparedModel> preparedModel = nullptr;
PrepareModel(device, model, &preparedModel);
if (preparedModel == nullptr) {
GTEST_SKIP();
}
sp<IPreparedModel> preparedModel;
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
EvaluatePreparedModel(preparedModel, testModel, testDynamicOutputShape);
}
};
}
// Tag for the generated tests
class GeneratedTest : public GeneratedTestBase {};
// Tag for the dynamic output shape tests
class DynamicOutputShapeTest : public GeneratedTest {};
TEST_P(GeneratedTest, Test) {
Execute(*mTestModel, /*testDynamicOutputShape=*/false);
Execute(kDevice, kTestModel, /*testDynamicOutputShape=*/false);
}
TEST_P(DynamicOutputShapeTest, Test) {
Execute(*mTestModel, /*testDynamicOutputShape=*/true);
Execute(kDevice, kTestModel, /*testDynamicOutputShape=*/true);
}
INSTANTIATE_GENERATED_TEST(GeneratedTest,

24
neuralnetworks/1.2/vts/functional/GeneratedTestHarness.h
View file

@ -29,36 +29,20 @@ namespace android::hardware::neuralnetworks::V1_2::vts::functional {
class GeneratedTestBase
: public NeuralnetworksHidlTest,
public ::testing::WithParamInterface<test_helper::TestModelManager::TestParam> {
public testing::WithParamInterface<test_helper::TestModelManager::TestParam> {
protected:
void SetUp() override {
NeuralnetworksHidlTest::SetUp();
ASSERT_NE(mTestModel, nullptr);
}
const test_helper::TestModel* mTestModel = GetParam().second;
const test_helper::TestModel& kTestModel = *GetParam().second;
};
#define INSTANTIATE_GENERATED_TEST(TestSuite, filter) \
INSTANTIATE_TEST_SUITE_P( \
TestGenerated, TestSuite, \
::testing::ValuesIn(::test_helper::TestModelManager::get().getTestModels(filter)), \
testing::ValuesIn(::test_helper::TestModelManager::get().getTestModels(filter)), \
[](const auto& info) { return info.param.first; })
// Tag for the validation tests, instantiated in VtsHalNeuralnetworks.cpp.
// TODO: Clean up the hierarchy for ValidationTest.
class ValidationTest : public GeneratedTestBase {
protected:
void validateEverything(const Model& model, const V1_0::Request& request);
void validateFailure(const Model& model, const V1_0::Request& request);
private:
void validateModel(const Model& model);
void validateRequest(const sp<IPreparedModel>& preparedModel, const V1_0::Request& request);
void validateRequestFailure(const sp<IPreparedModel>& preparedModel,
const V1_0::Request& request);
void validateBurst(const sp<IPreparedModel>& preparedModel, const V1_0::Request& request);
};
class ValidationTest : public GeneratedTestBase {};
Model createModel(const ::test_helper::TestModel& testModel);

3
neuralnetworks/1.2/vts/functional/ValidateBurst.cpp
View file

@ -391,8 +391,7 @@ static void validateBurstSanitized(const sp<IPreparedModel>& preparedModel,
///////////////////////////// ENTRY POINT //////////////////////////////////
void ValidationTest::validateBurst(const sp<IPreparedModel>& preparedModel,
const Request& request) {
void validateBurst(const sp<IPreparedModel>& preparedModel, const Request& request) {
ASSERT_NO_FATAL_FAILURE(validateBurstSerialization(preparedModel, request));
ASSERT_NO_FATAL_FAILURE(validateBurstFmqLength(preparedModel, request));
ASSERT_NO_FATAL_FAILURE(validateBurstSanitized(preparedModel, request));

2
neuralnetworks/1.2/vts/functional/ValidateModel.cpp
View file

@ -692,7 +692,7 @@ static void mutateExecutionPreferenceTest(const sp<IDevice>& device, const Model
////////////////////////// ENTRY POINT //////////////////////////////
void ValidationTest::validateModel(const Model& model) {
void validateModel(const sp<IDevice>& device, const Model& model) {
mutateOperandTypeTest(device, model);
mutateOperandRankTest(device, model);
mutateOperandScaleTest(device, model);

6
neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
View file

@ -148,14 +148,12 @@ static void removeOutputTest(const sp<IPreparedModel>& preparedModel, const Requ
///////////////////////////// ENTRY POINT //////////////////////////////////
void ValidationTest::validateRequest(const sp<IPreparedModel>& preparedModel,
const Request& request) {
void validateRequest(const sp<IPreparedModel>& preparedModel, const Request& request) {
removeInputTest(preparedModel, request);
removeOutputTest(preparedModel, request);
}
void ValidationTest::validateRequestFailure(const sp<IPreparedModel>& preparedModel,
const Request& request) {
void validateRequestFailure(const sp<IPreparedModel>& preparedModel, const Request& request) {
SCOPED_TRACE("Expecting request to fail [executeSynchronously]");
Return<void> executeStatus = preparedModel->executeSynchronously(
request, MeasureTiming::NO,

91
neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
View file

@ -33,24 +33,25 @@ using V1_0::Request;
using V1_1::ExecutionPreference;
// internal helper function
static void createPreparedModel(const sp<IDevice>& device, const Model& model,
void createPreparedModel(const sp<IDevice>& device, const Model& model,
sp<IPreparedModel>* preparedModel) {
ASSERT_NE(nullptr, preparedModel);
*preparedModel = nullptr;
// see if service can handle model
bool fullySupportsModel = false;
Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_2(
const Return<void> supportedCall = 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());
ASSERT_TRUE(supportedCall.isOk());
// launch prepare model
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_2(
const sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
const 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());
@ -58,7 +59,7 @@ static void createPreparedModel(const sp<IDevice>& device, const Model& model,
// retrieve prepared model
preparedModelCallback->wait();
ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
const ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
*preparedModel = getPreparedModel_1_2(preparedModelCallback);
// The getSupportedOperations_1_2 call returns a list of operations that are
@ -70,12 +71,12 @@ static void createPreparedModel(const sp<IDevice>& device, const Model& model,
// 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."
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 "
"prepare model that it does not support."
<< std::endl;
return;
GTEST_SKIP();
}
ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel->get());
@ -84,7 +85,7 @@ static void createPreparedModel(const sp<IDevice>& device, const Model& model,
// A class for test environment setup
NeuralnetworksHidlEnvironment* NeuralnetworksHidlEnvironment::getInstance() {
// This has to return a "new" object because it is freed inside
// ::testing::AddGlobalTestEnvironment when the gtest is being torn down
// testing::AddGlobalTestEnvironment when the gtest is being torn down
static NeuralnetworksHidlEnvironment* instance = new NeuralnetworksHidlEnvironment();
return instance;
}
@ -95,59 +96,61 @@ void NeuralnetworksHidlEnvironment::registerTestServices() {
// The main test class for NEURALNETWORK HIDL HAL.
void NeuralnetworksHidlTest::SetUp() {
::testing::VtsHalHidlTargetTestBase::SetUp();
testing::VtsHalHidlTargetTestBase::SetUp();
#ifdef PRESUBMIT_NOT_VTS
const std::string name =
NeuralnetworksHidlEnvironment::getInstance()->getServiceName<IDevice>();
const std::string sampleDriver = "sample-";
if (device == nullptr && name.substr(0, sampleDriver.size()) == sampleDriver) {
if (kDevice == nullptr && name.substr(0, sampleDriver.size()) == sampleDriver) {
GTEST_SKIP();
}
#endif // PRESUBMIT_NOT_VTS
ASSERT_NE(nullptr, device.get());
ASSERT_NE(nullptr, kDevice.get());
}
void NeuralnetworksHidlTest::TearDown() {
::testing::VtsHalHidlTargetTestBase::TearDown();
}
// Forward declaration from ValidateModel.cpp
void validateModel(const sp<IDevice>& device, const Model& model);
// Forward declaration from ValidateRequest.cpp
void validateRequest(const sp<IPreparedModel>& preparedModel, const V1_0::Request& request);
// Forward declaration from ValidateRequest.cpp
void validateRequestFailure(const sp<IPreparedModel>& preparedModel, const V1_0::Request& request);
// Forward declaration from ValidateBurst.cpp
void validateBurst(const sp<IPreparedModel>& preparedModel, const V1_0::Request& request);
void ValidationTest::validateEverything(const Model& model, const Request& request) {
validateModel(model);
void validateEverything(const sp<IDevice>& device, const Model& model, const Request& request) {
validateModel(device, model);
// create IPreparedModel
// Create IPreparedModel.
sp<IPreparedModel> preparedModel;
ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
if (preparedModel == nullptr) {
return;
}
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
validateRequest(preparedModel, request);
validateBurst(preparedModel, request);
}
void ValidationTest::validateFailure(const Model& model, const Request& request) {
void validateFailure(const sp<IDevice>& device, const Model& model, const Request& request) {
// TODO: Should this always succeed?
// What if the invalid input is part of the model (i.e., a parameter).
validateModel(model);
validateModel(device, model);
// Create IPreparedModel.
sp<IPreparedModel> preparedModel;
ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
if (preparedModel == nullptr) {
return;
}
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
validateRequestFailure(preparedModel, request);
}
TEST_P(ValidationTest, Test) {
const Model model = createModel(*mTestModel);
const Request request = createRequest(*mTestModel);
if (mTestModel->expectFailure) {
validateFailure(model, request);
const Model model = createModel(kTestModel);
const Request request = createRequest(kTestModel);
if (kTestModel.expectFailure) {
validateFailure(kDevice, model, request);
} else {
validateEverything(model, request);
validateEverything(kDevice, model, request);
}
}
@ -160,23 +163,11 @@ sp<IPreparedModel> getPreparedModel_1_2(const sp<implementation::PreparedModelCa
} // namespace android::hardware::neuralnetworks::V1_2::vts::functional
namespace android::hardware::neuralnetworks::V1_0 {
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus) {
return os << toString(errorStatus);
}
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus) {
return os << toString(deviceStatus);
}
} // namespace android::hardware::neuralnetworks::V1_0
using android::hardware::neuralnetworks::V1_2::vts::functional::NeuralnetworksHidlEnvironment;
int main(int argc, char** argv) {
::testing::AddGlobalTestEnvironment(NeuralnetworksHidlEnvironment::getInstance());
::testing::InitGoogleTest(&argc, argv);
testing::AddGlobalTestEnvironment(NeuralnetworksHidlEnvironment::getInstance());
testing::InitGoogleTest(&argc, argv);
NeuralnetworksHidlEnvironment::getInstance()->init(&argc, argv);
int status = RUN_ALL_TESTS();

24
neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
View file

@ -26,16 +26,12 @@
#include <android/hardware/neuralnetworks/1.2/types.h>
#include <gtest/gtest.h>
#include <iostream>
#include <vector>
#include "1.2/Callbacks.h"
#include "TestHarness.h"
namespace android::hardware::neuralnetworks::V1_2::vts::functional {
// A class for test environment setup
class NeuralnetworksHidlEnvironment : public ::testing::VtsHalHidlTargetTestEnvBase {
class NeuralnetworksHidlEnvironment : public testing::VtsHalHidlTargetTestEnvBase {
DISALLOW_COPY_AND_ASSIGN(NeuralnetworksHidlEnvironment);
NeuralnetworksHidlEnvironment() = default;
@ -45,30 +41,26 @@ class NeuralnetworksHidlEnvironment : public ::testing::VtsHalHidlTargetTestEnvB
};
// The main test class for NEURALNETWORKS HIDL HAL.
class NeuralnetworksHidlTest : public ::testing::VtsHalHidlTargetTestBase {
class NeuralnetworksHidlTest : public testing::VtsHalHidlTargetTestBase {
DISALLOW_COPY_AND_ASSIGN(NeuralnetworksHidlTest);
public:
NeuralnetworksHidlTest() = default;
void SetUp() override;
void TearDown() override;
protected:
const sp<IDevice> device = ::testing::VtsHalHidlTargetTestBase::getService<IDevice>(
const sp<IDevice> kDevice = testing::VtsHalHidlTargetTestBase::getService<IDevice>(
NeuralnetworksHidlEnvironment::getInstance());
};
// Create an IPreparedModel object. If the model cannot be prepared,
// "preparedModel" will be nullptr instead.
void createPreparedModel(const sp<IDevice>& device, const Model& model,
sp<IPreparedModel>* preparedModel);
// Utility function to get PreparedModel from callback and downcast to V1_2.
sp<IPreparedModel> getPreparedModel_1_2(const sp<implementation::PreparedModelCallback>& callback);
} // namespace android::hardware::neuralnetworks::V1_2::vts::functional
namespace android::hardware::neuralnetworks::V1_0 {
// pretty-print values for error messages
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus);
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus);
} // namespace android::hardware::neuralnetworks::V1_0
#endif // ANDROID_HARDWARE_NEURALNETWORKS_V1_2_VTS_HAL_NEURALNETWORKS_H