/* * Copyright (C) 2018 The Android Open Source Project * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #undef NDEBUG #include "Callbacks.h" #include "CompilationBuilder.h" #include "Manager.h" #include "ModelBuilder.h" #include "NeuralNetworks.h" #include "SampleDriver.h" #include "TestNeuralNetworksWrapper.h" #include "ValidateHal.h" #include #include #include #include namespace android { using CompilationBuilder = nn::CompilationBuilder; using Device = nn::Device; using DeviceManager = nn::DeviceManager; using HidlModel = hardware::neuralnetworks::V1_2::Model; using HidlToken = hardware::hidl_array; using PreparedModelCallback = hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback; using Result = nn::test_wrapper::Result; using SampleDriver = nn::sample_driver::SampleDriver; using WrapperCompilation = nn::test_wrapper::Compilation; using WrapperEvent = nn::test_wrapper::Event; using WrapperExecution = nn::test_wrapper::Execution; using WrapperModel = nn::test_wrapper::Model; using WrapperOperandType = nn::test_wrapper::OperandType; using WrapperType = nn::test_wrapper::Type; template using MQDescriptorSync = ::android::hardware::MQDescriptorSync; namespace { const Timing kBadTiming = {.timeOnDevice = UINT64_MAX, .timeInDriver = UINT64_MAX}; // Wraps an V1_2::IPreparedModel to allow dummying up the execution status. class TestPreparedModel12 : public V1_2::IPreparedModel { public: // If errorStatus is NONE, then execute behaves normally (and sends back // the actual execution status). Otherwise, don't bother to execute, and // just send back errorStatus (as the execution status, not the launch // status). TestPreparedModel12(sp preparedModel, ErrorStatus errorStatus) : mPreparedModelV1_0(preparedModel), mPreparedModelV1_2(V1_2::IPreparedModel::castFrom(preparedModel).withDefault(nullptr)), mErrorStatus(errorStatus) {} Return execute(const Request& request, const sp& callback) override { CHECK(mPreparedModelV1_0 != nullptr) << "V1_0 prepared model is nullptr."; if (mErrorStatus == ErrorStatus::NONE) { return mPreparedModelV1_0->execute(request, callback); } else { callback->notify(mErrorStatus); return ErrorStatus::NONE; } } Return execute_1_2(const Request& request, MeasureTiming measure, const sp& callback) override { CHECK(mPreparedModelV1_2 != nullptr) << "V1_2 prepared model is nullptr."; if (mErrorStatus == ErrorStatus::NONE) { return mPreparedModelV1_2->execute_1_2(request, measure, callback); } else if (mErrorStatus == ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) { OutputShape shape = {.dimensions = {1}, .isSufficient = false}; callback->notify_1_2(mErrorStatus, {shape}, kBadTiming); return ErrorStatus::NONE; } else { callback->notify_1_2(mErrorStatus, {}, kBadTiming); return ErrorStatus::NONE; } } Return executeSynchronously(const Request& request, MeasureTiming measure, executeSynchronously_cb cb) override { CHECK(mPreparedModelV1_2 != nullptr) << "V1_2 prepared model is nullptr."; if (mErrorStatus == ErrorStatus::NONE) { return mPreparedModelV1_2->executeSynchronously( request, measure, [&cb](ErrorStatus error, const hidl_vec& outputShapes, const Timing& timing) { cb(error, outputShapes, timing); }); } else if (mErrorStatus == ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) { OutputShape shape = {.dimensions = {1}, .isSufficient = false}; cb(mErrorStatus, {shape}, kBadTiming); return Void(); } else { cb(mErrorStatus, {}, kBadTiming); return Void(); } } Return configureExecutionBurst( const sp& callback, const MQDescriptorSync& requestChannel, const MQDescriptorSync& resultChannel, configureExecutionBurst_cb cb) override { if (mErrorStatus == ErrorStatus::NONE) { return mPreparedModelV1_2->configureExecutionBurst(callback, requestChannel, resultChannel, cb); } else { cb(mErrorStatus, nullptr); return Void(); } } private: const sp mPreparedModelV1_0; const sp mPreparedModelV1_2; ErrorStatus mErrorStatus; }; // Like TestPreparedModel12, but implementing 1.0 class TestPreparedModel10 : public V1_0::IPreparedModel { public: TestPreparedModel10(sp preparedModel, ErrorStatus errorStatus) : m12PreparedModel(new TestPreparedModel12(preparedModel, errorStatus)) {} Return execute(const Request& request, const sp& callback) override { return m12PreparedModel->execute(request, callback); } private: const sp m12PreparedModel; }; // Behaves like SampleDriver, except that it produces wrapped IPreparedModel. class TestDriver12 : public SampleDriver { public: // Allow dummying up the error status for execution of all models // prepared from this driver. If errorStatus is NONE, then // execute behaves normally (and sends back the actual execution // status). Otherwise, don't bother to execute, and just send // back errorStatus (as the execution status, not the launch // status). TestDriver12(const std::string& name, ErrorStatus errorStatus) : SampleDriver(name.c_str()), mErrorStatus(errorStatus) {} Return getCapabilities_1_2(getCapabilities_1_2_cb _hidl_cb) override { android::nn::initVLogMask(); const PerformanceInfo kPerf = {.execTime = 0.75f, .powerUsage = 0.75f}; Capabilities capabilities = { .relaxedFloat32toFloat16PerformanceScalar = kPerf, .relaxedFloat32toFloat16PerformanceTensor = kPerf, .operandPerformance = nn::nonExtensionOperandPerformance(kPerf)}; _hidl_cb(ErrorStatus::NONE, capabilities); return Void(); } Return getSupportedOperations_1_2(const HidlModel& model, getSupportedOperations_1_2_cb cb) override { if (nn::validateModel(model)) { std::vector supported(model.operations.size(), true); cb(ErrorStatus::NONE, supported); } else { std::vector supported; cb(ErrorStatus::INVALID_ARGUMENT, supported); } return Void(); } Return prepareModel_1_2( const HidlModel& model, ExecutionPreference preference, const hidl_vec& modelCache, const hidl_vec& dataCache, const HidlToken& token, const sp& actualCallback) override { sp localCallback = new PreparedModelCallback; Return prepareModelReturn = SampleDriver::prepareModel_1_2( model, preference, modelCache, dataCache, token, localCallback); if (!prepareModelReturn.isOkUnchecked()) { return prepareModelReturn; } if (prepareModelReturn != ErrorStatus::NONE) { actualCallback->notify_1_2( localCallback->getStatus(), V1_2::IPreparedModel::castFrom(localCallback->getPreparedModel())); return prepareModelReturn; } localCallback->wait(); if (localCallback->getStatus() != ErrorStatus::NONE) { actualCallback->notify_1_2( localCallback->getStatus(), V1_2::IPreparedModel::castFrom(localCallback->getPreparedModel())); } else { actualCallback->notify_1_2( ErrorStatus::NONE, new TestPreparedModel12(localCallback->getPreparedModel(), mErrorStatus)); } return prepareModelReturn; } Return prepareModel_1_1( const V1_1::Model& model, ExecutionPreference preference, const sp& actualCallback) override { sp localCallback = new PreparedModelCallback; Return prepareModelReturn = SampleDriver::prepareModel_1_1(model, preference, localCallback); if (!prepareModelReturn.isOkUnchecked()) { return prepareModelReturn; } if (prepareModelReturn != ErrorStatus::NONE) { actualCallback->notify(localCallback->getStatus(), localCallback->getPreparedModel()); return prepareModelReturn; } localCallback->wait(); if (localCallback->getStatus() != ErrorStatus::NONE) { actualCallback->notify(localCallback->getStatus(), localCallback->getPreparedModel()); } else { actualCallback->notify( ErrorStatus::NONE, new TestPreparedModel10(localCallback->getPreparedModel(), mErrorStatus)); } return prepareModelReturn; } Return prepareModel( const V1_0::Model& model, const sp& actualCallback) override { return prepareModel_1_1(nn::convertToV1_1(model), ExecutionPreference::FAST_SINGLE_ANSWER, actualCallback); } private: ErrorStatus mErrorStatus; }; // Like TestDriver, but implementing 1.1 class TestDriver11 : public V1_1::IDevice { public: TestDriver11(const std::string& name, ErrorStatus errorStatus) : m12Driver(new TestDriver12(name, errorStatus)) {} Return getCapabilities_1_1(getCapabilities_1_1_cb _hidl_cb) override { return m12Driver->getCapabilities_1_1(_hidl_cb); } Return getSupportedOperations_1_1(const V1_1::Model& model, getSupportedOperations_1_1_cb _hidl_cb) override { return m12Driver->getSupportedOperations_1_1(model, _hidl_cb); } Return prepareModel_1_1( const V1_1::Model& model, ExecutionPreference preference, const sp& actualCallback) override { return m12Driver->prepareModel_1_1(model, preference, actualCallback); } Return getStatus() override { return m12Driver->getStatus(); } Return getCapabilities(getCapabilities_cb _hidl_cb) override { return m12Driver->getCapabilities(_hidl_cb); } Return getSupportedOperations(const V1_0::Model& model, getSupportedOperations_cb _hidl_cb) override { return m12Driver->getSupportedOperations(model, _hidl_cb); } Return prepareModel( const V1_0::Model& model, const sp& actualCallback) override { return m12Driver->prepareModel(model, actualCallback); } private: const sp m12Driver; }; // Like TestDriver, but implementing 1.0 class TestDriver10 : public V1_0::IDevice { public: TestDriver10(const std::string& name, ErrorStatus errorStatus) : m12Driver(new TestDriver12(name, errorStatus)) {} Return getCapabilities(getCapabilities_cb _hidl_cb) override { return m12Driver->getCapabilities(_hidl_cb); } Return getSupportedOperations(const V1_0::Model& model, getSupportedOperations_cb _hidl_cb) override { return m12Driver->getSupportedOperations(model, _hidl_cb); } Return prepareModel( const V1_0::Model& model, const sp& actualCallback) override { return m12Driver->prepareModel(model, actualCallback); } Return getStatus() override { return m12Driver->getStatus(); } private: const sp m12Driver; }; // This class adds some simple utilities on top of WrapperCompilation in order // to provide access to certain features from CompilationBuilder that are not // exposed by the base class. template class TestCompilation : public WrapperCompilation { public: // Allow dummying up the error status for all executions from this // compilation. If errorStatus is NONE, then execute behaves // normally (and sends back the actual execution status). // Otherwise, don't bother to execute, and just send back // errorStatus (as the execution status, not the launch status). TestCompilation(const WrapperModel* model, const std::string& deviceName, ErrorStatus errorStatus) { std::vector> devices; auto device = DeviceManager::forTest_makeDriverDevice( deviceName, new DriverClass(deviceName, errorStatus)); devices.push_back(device); nn::ModelBuilder* m = reinterpret_cast(model->getHandle()); CompilationBuilder* c = nullptr; int result = m->createCompilation(&c, devices); EXPECT_EQ(result, 0); // We need to ensure that we use our TestDriver and do not // fall back to CPU. (If we allow CPU fallback, then when our // TestDriver reports an execution failure, we'll re-execute // on CPU, and will not see the failure.) c->setPartitioning(DeviceManager::kPartitioningWithoutFallback); mCompilation = reinterpret_cast(c); } }; // This class has roughly the same functionality as TestCompilation class. // The major difference is that Introspection API is used to select the device. class TestIntrospectionCompilation : public WrapperCompilation { public: TestIntrospectionCompilation(const WrapperModel* model, const std::string& deviceName) { std::vector mDevices; uint32_t numDevices = 0; EXPECT_EQ(ANeuralNetworks_getDeviceCount(&numDevices), ANEURALNETWORKS_NO_ERROR); EXPECT_GE(numDevices, (uint32_t)1); for (uint32_t i = 0; i < numDevices; i++) { ANeuralNetworksDevice* device = nullptr; EXPECT_EQ(ANeuralNetworks_getDevice(i, &device), ANEURALNETWORKS_NO_ERROR); const char* buffer = nullptr; int result = ANeuralNetworksDevice_getName(device, &buffer); if (result == ANEURALNETWORKS_NO_ERROR && deviceName.compare(buffer) == 0) { mDevices.push_back(device); } } // In CPU only mode, DeviceManager::getDrivers() will not be able to // provide the actual device list. We will not be able to find the test // driver with specified deviceName. if (!DeviceManager::get()->getUseCpuOnly()) { EXPECT_EQ(mDevices.size(), (uint32_t)1); int result = ANeuralNetworksCompilation_createForDevices( model->getHandle(), mDevices.data(), mDevices.size(), &mCompilation); EXPECT_EQ(result, ANEURALNETWORKS_NO_ERROR); } } }; template class ExecutionTestTemplate : public ::testing::TestWithParam> { public: ExecutionTestTemplate() : kName(toString(std::get<0>(GetParam()))), kForceErrorStatus(std::get<0>(GetParam())), kExpectResult(std::get<1>(GetParam())), kUseIntrospectionAPI(std::get<2>(GetParam())), mModel(makeModel()) { if (kUseIntrospectionAPI) { DeviceManager::get()->forTest_registerDevice(kName.c_str(), new DriverClass(kName, kForceErrorStatus)); mCompilation = TestIntrospectionCompilation(&mModel, kName); } else { mCompilation = TestCompilation(&mModel, kName, kForceErrorStatus); } } protected: // Unit test method void TestWait(); virtual void TearDown() { // Reinitialize the device list since Introspection API path altered it. if (kUseIntrospectionAPI) { DeviceManager::get()->forTest_reInitializeDeviceList(); } } const std::string kName; // Allow dummying up the error status for execution. If // kForceErrorStatus is NONE, then execution behaves normally (and // sends back the actual execution status). Otherwise, don't // bother to execute, and just send back kForceErrorStatus (as the // execution status, not the launch status). const ErrorStatus kForceErrorStatus; // What result do we expect from the execution? (The Result // equivalent of kForceErrorStatus.) const Result kExpectResult; // Whether mCompilation is created via Introspection API or not. const bool kUseIntrospectionAPI; WrapperModel mModel; WrapperCompilation mCompilation; void setInputOutput(WrapperExecution* execution) { mInputBuffer = kInputBuffer; mOutputBuffer = kOutputBufferInitial; ASSERT_EQ(execution->setInput(0, &mInputBuffer, sizeof(mInputBuffer)), Result::NO_ERROR); ASSERT_EQ(execution->setOutput(0, &mOutputBuffer, sizeof(mOutputBuffer)), Result::NO_ERROR); } const float kInputBuffer = 3.14; const float kOutputBufferInitial = 0; float mInputBuffer; float mOutputBuffer; const float kOutputBufferExpected = 3; const std::vector kOutputDimensionsExpected = {1}; private: static WrapperModel makeModel() { static const WrapperOperandType tensorType(WrapperType::TENSOR_FLOAT32, { 1 }); WrapperModel model; uint32_t input = model.addOperand(&tensorType); uint32_t output = model.addOperand(&tensorType); model.addOperation(ANEURALNETWORKS_FLOOR, { input }, { output }); model.identifyInputsAndOutputs({ input }, { output } ); assert(model.finish() == Result::NO_ERROR); return model; } }; template void ExecutionTestTemplate::TestWait() { SCOPED_TRACE(kName); // Skip Introspection API tests when CPU only flag is forced on. if (kUseIntrospectionAPI && DeviceManager::get()->getUseCpuOnly()) { GTEST_SKIP(); } ASSERT_EQ(mCompilation.finish(), Result::NO_ERROR); { SCOPED_TRACE("startCompute"); WrapperExecution execution(&mCompilation); ASSERT_NO_FATAL_FAILURE(setInputOutput(&execution)); WrapperEvent event; ASSERT_EQ(execution.startCompute(&event), Result::NO_ERROR); ASSERT_EQ(event.wait(), kExpectResult); if (kExpectResult == Result::NO_ERROR) { ASSERT_EQ(mOutputBuffer, kOutputBufferExpected); } std::vector dimensions; if (kExpectResult == Result::OUTPUT_INSUFFICIENT_SIZE) { // Only one output operand, hardcoded as index 0. ASSERT_EQ(execution.getOutputOperandDimensions(0, &dimensions), Result::OUTPUT_INSUFFICIENT_SIZE); } else { ASSERT_EQ(execution.getOutputOperandDimensions(0, &dimensions), Result::NO_ERROR); } if (kExpectResult == Result::NO_ERROR || kExpectResult == Result::OUTPUT_INSUFFICIENT_SIZE) { ASSERT_EQ(dimensions, kOutputDimensionsExpected); } } { SCOPED_TRACE("compute"); WrapperExecution execution(&mCompilation); ASSERT_NO_FATAL_FAILURE(setInputOutput(&execution)); ASSERT_EQ(execution.compute(), kExpectResult); if (kExpectResult == Result::NO_ERROR) { ASSERT_EQ(mOutputBuffer, kOutputBufferExpected); } std::vector dimensions; if (kExpectResult == Result::OUTPUT_INSUFFICIENT_SIZE) { // Only one output operand, hardcoded as index 0. ASSERT_EQ(execution.getOutputOperandDimensions(0, &dimensions), Result::OUTPUT_INSUFFICIENT_SIZE); } else { ASSERT_EQ(execution.getOutputOperandDimensions(0, &dimensions), Result::NO_ERROR); } if (kExpectResult == Result::NO_ERROR || kExpectResult == Result::OUTPUT_INSUFFICIENT_SIZE) { ASSERT_EQ(dimensions, kOutputDimensionsExpected); } } } auto kTestValues = ::testing::Values( std::make_tuple(ErrorStatus::NONE, Result::NO_ERROR, /* kUseIntrospectionAPI */ false), std::make_tuple(ErrorStatus::DEVICE_UNAVAILABLE, Result::UNAVAILABLE_DEVICE, /* kUseIntrospectionAPI */ false), std::make_tuple(ErrorStatus::GENERAL_FAILURE, Result::OP_FAILED, /* kUseIntrospectionAPI */ false), std::make_tuple(ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, Result::OUTPUT_INSUFFICIENT_SIZE, /* kUseIntrospectionAPI */ false), std::make_tuple(ErrorStatus::INVALID_ARGUMENT, Result::BAD_DATA, /* kUseIntrospectionAPI */ false)); class ExecutionTest12 : public ExecutionTestTemplate {}; TEST_P(ExecutionTest12, Wait) { TestWait(); } INSTANTIATE_TEST_CASE_P(Flavor, ExecutionTest12, kTestValues); class ExecutionTest11 : public ExecutionTestTemplate {}; TEST_P(ExecutionTest11, Wait) { if (kForceErrorStatus == ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) return; TestWait(); } INSTANTIATE_TEST_CASE_P(Flavor, ExecutionTest11, kTestValues); class ExecutionTest10 : public ExecutionTestTemplate {}; TEST_P(ExecutionTest10, Wait) { if (kForceErrorStatus == ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) return; TestWait(); } INSTANTIATE_TEST_CASE_P(Flavor, ExecutionTest10, kTestValues); auto kIntrospectionTestValues = ::testing::Values( std::make_tuple(ErrorStatus::NONE, Result::NO_ERROR, /* kUseIntrospectionAPI */ true), std::make_tuple(ErrorStatus::DEVICE_UNAVAILABLE, Result::UNAVAILABLE_DEVICE, /* kUseIntrospectionAPI */ true), std::make_tuple(ErrorStatus::GENERAL_FAILURE, Result::OP_FAILED, /* kUseIntrospectionAPI */ true), std::make_tuple(ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, Result::OUTPUT_INSUFFICIENT_SIZE, /* kUseIntrospectionAPI */ true), std::make_tuple(ErrorStatus::INVALID_ARGUMENT, Result::BAD_DATA, /* kUseIntrospectionAPI */ true)); INSTANTIATE_TEST_CASE_P(IntrospectionFlavor, ExecutionTest12, kIntrospectionTestValues); } // namespace } // namespace android