| /* |
| * Copyright (C) 2019 The Android Open Source Project |
| * |
| * Licensed under the Apache License, Version 2.0 (the "License"); |
| * you may not use this file except in compliance with the License. |
| * You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| |
| #include "GeneratedTestHarness.h" |
| |
| #include <android-base/logging.h> |
| #include <android/hardware/neuralnetworks/1.0/IDevice.h> |
| #include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h> |
| #include <android/hardware/neuralnetworks/1.0/IPreparedModel.h> |
| #include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h> |
| #include <android/hardware/neuralnetworks/1.0/types.h> |
| #include <android/hardware/neuralnetworks/1.1/IDevice.h> |
| #include <android/hardware/neuralnetworks/1.2/IDevice.h> |
| #include <android/hardware/neuralnetworks/1.2/IExecutionCallback.h> |
| #include <android/hardware/neuralnetworks/1.2/IPreparedModel.h> |
| #include <android/hardware/neuralnetworks/1.2/IPreparedModelCallback.h> |
| #include <android/hardware/neuralnetworks/1.2/types.h> |
| #include <android/hardware/neuralnetworks/1.3/IDevice.h> |
| #include <android/hardware/neuralnetworks/1.3/IPreparedModel.h> |
| #include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h> |
| #include <android/hardware/neuralnetworks/1.3/types.h> |
| #include <android/hidl/allocator/1.0/IAllocator.h> |
| #include <android/hidl/memory/1.0/IMemory.h> |
| #include <gtest/gtest.h> |
| #include <hidlmemory/mapping.h> |
| |
| #include <algorithm> |
| #include <chrono> |
| #include <iostream> |
| #include <numeric> |
| #include <vector> |
| |
| #include "1.0/Utils.h" |
| #include "1.2/Callbacks.h" |
| #include "1.3/Callbacks.h" |
| #include "ExecutionBurstController.h" |
| #include "MemoryUtils.h" |
| #include "TestHarness.h" |
| #include "Utils.h" |
| #include "VtsHalNeuralnetworks.h" |
| |
| namespace android::hardware::neuralnetworks::V1_3::vts::functional { |
| |
| using namespace test_helper; |
| using hidl::memory::V1_0::IMemory; |
| using implementation::PreparedModelCallback; |
| using V1_0::DataLocation; |
| using V1_0::ErrorStatus; |
| using V1_0::OperandLifeTime; |
| using V1_1::ExecutionPreference; |
| using V1_2::Constant; |
| using V1_2::MeasureTiming; |
| using V1_2::OutputShape; |
| using V1_2::SymmPerChannelQuantParams; |
| using V1_2::Timing; |
| using V1_2::implementation::ExecutionCallback; |
| using HidlToken = hidl_array<uint8_t, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN)>; |
| |
| namespace { |
| |
| enum class Executor { ASYNC, SYNC, BURST }; |
| |
| enum class OutputType { FULLY_SPECIFIED, UNSPECIFIED, INSUFFICIENT }; |
| |
| struct TestConfig { |
| Executor executor; |
| MeasureTiming measureTiming; |
| OutputType outputType; |
| // `reportSkipping` indicates if a test should print an info message in case |
| // it is skipped. The field is set to true by default and is set to false in |
| // quantization coupling tests to suppress skipping a test |
| bool reportSkipping; |
| TestConfig(Executor executor, MeasureTiming measureTiming, OutputType outputType) |
| : executor(executor), |
| measureTiming(measureTiming), |
| outputType(outputType), |
| reportSkipping(true) {} |
| TestConfig(Executor executor, MeasureTiming measureTiming, OutputType outputType, |
| bool reportSkipping) |
| : executor(executor), |
| measureTiming(measureTiming), |
| outputType(outputType), |
| reportSkipping(reportSkipping) {} |
| }; |
| |
| } // namespace |
| |
| Model createModel(const TestModel& testModel) { |
| // Model operands. |
| hidl_vec<Operand> operands(testModel.operands.size()); |
| size_t constCopySize = 0, constRefSize = 0; |
| for (uint32_t i = 0; i < testModel.operands.size(); i++) { |
| const auto& op = testModel.operands[i]; |
| |
| DataLocation loc = {}; |
| if (op.lifetime == TestOperandLifeTime::CONSTANT_COPY) { |
| loc = {.poolIndex = 0, |
| .offset = static_cast<uint32_t>(constCopySize), |
| .length = static_cast<uint32_t>(op.data.size())}; |
| constCopySize += op.data.alignedSize(); |
| } else if (op.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) { |
| loc = {.poolIndex = 0, |
| .offset = static_cast<uint32_t>(constRefSize), |
| .length = static_cast<uint32_t>(op.data.size())}; |
| constRefSize += op.data.alignedSize(); |
| } |
| |
| Operand::ExtraParams extraParams; |
| if (op.type == TestOperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL) { |
| extraParams.channelQuant(SymmPerChannelQuantParams{ |
| .scales = op.channelQuant.scales, .channelDim = op.channelQuant.channelDim}); |
| } |
| |
| operands[i] = {.type = static_cast<OperandType>(op.type), |
| .dimensions = op.dimensions, |
| .numberOfConsumers = op.numberOfConsumers, |
| .scale = op.scale, |
| .zeroPoint = op.zeroPoint, |
| .lifetime = static_cast<OperandLifeTime>(op.lifetime), |
| .location = loc, |
| .extraParams = std::move(extraParams)}; |
| } |
| |
| // Model operations. |
| hidl_vec<Operation> operations(testModel.operations.size()); |
| std::transform(testModel.operations.begin(), testModel.operations.end(), operations.begin(), |
| [](const TestOperation& op) -> Operation { |
| return {.type = static_cast<OperationType>(op.type), |
| .inputs = op.inputs, |
| .outputs = op.outputs}; |
| }); |
| |
| // Constant copies. |
| hidl_vec<uint8_t> operandValues(constCopySize); |
| for (uint32_t i = 0; i < testModel.operands.size(); i++) { |
| const auto& op = testModel.operands[i]; |
| if (op.lifetime == TestOperandLifeTime::CONSTANT_COPY) { |
| const uint8_t* begin = op.data.get<uint8_t>(); |
| const uint8_t* end = begin + op.data.size(); |
| std::copy(begin, end, operandValues.data() + operands[i].location.offset); |
| } |
| } |
| |
| // Shared memory. |
| hidl_vec<hidl_memory> pools = {}; |
| if (constRefSize > 0) { |
| hidl_vec_push_back(&pools, nn::allocateSharedMemory(constRefSize)); |
| CHECK_NE(pools[0].size(), 0u); |
| |
| // load data |
| sp<IMemory> mappedMemory = mapMemory(pools[0]); |
| CHECK(mappedMemory.get() != nullptr); |
| uint8_t* mappedPtr = |
| reinterpret_cast<uint8_t*>(static_cast<void*>(mappedMemory->getPointer())); |
| CHECK(mappedPtr != nullptr); |
| |
| for (uint32_t i = 0; i < testModel.operands.size(); i++) { |
| const auto& op = testModel.operands[i]; |
| if (op.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) { |
| const uint8_t* begin = op.data.get<uint8_t>(); |
| const uint8_t* end = begin + op.data.size(); |
| std::copy(begin, end, mappedPtr + operands[i].location.offset); |
| } |
| } |
| } |
| |
| return {.operands = std::move(operands), |
| .operations = std::move(operations), |
| .inputIndexes = testModel.inputIndexes, |
| .outputIndexes = testModel.outputIndexes, |
| .operandValues = std::move(operandValues), |
| .pools = std::move(pools), |
| .relaxComputationFloat32toFloat16 = testModel.isRelaxed}; |
| } |
| |
| static bool isOutputSizeGreaterThanOne(const TestModel& testModel, uint32_t index) { |
| const auto byteSize = testModel.operands[testModel.outputIndexes[index]].data.size(); |
| return byteSize > 1u; |
| } |
| |
| static void makeOutputInsufficientSize(uint32_t outputIndex, V1_0::Request* request) { |
| auto& length = request->outputs[outputIndex].location.length; |
| ASSERT_GT(length, 1u); |
| length -= 1u; |
| } |
| |
| static void makeOutputDimensionsUnspecified(Model* model) { |
| for (auto i : model->outputIndexes) { |
| auto& dims = model->operands[i].dimensions; |
| std::fill(dims.begin(), dims.end(), 0); |
| } |
| } |
| |
| static Return<ErrorStatus> ExecutePreparedModel(const sp<IPreparedModel>& preparedModel, |
| const Request& request, MeasureTiming measure, |
| sp<ExecutionCallback>& callback) { |
| return preparedModel->execute_1_3(request, measure, callback); |
| } |
| static Return<ErrorStatus> ExecutePreparedModel(const sp<IPreparedModel>& preparedModel, |
| const Request& request, MeasureTiming measure, |
| hidl_vec<OutputShape>* outputShapes, |
| Timing* timing) { |
| ErrorStatus result; |
| Return<void> ret = preparedModel->executeSynchronously_1_3( |
| request, measure, |
| [&result, outputShapes, timing](ErrorStatus error, const hidl_vec<OutputShape>& shapes, |
| const Timing& time) { |
| result = error; |
| *outputShapes = shapes; |
| *timing = time; |
| }); |
| if (!ret.isOk()) { |
| return ErrorStatus::GENERAL_FAILURE; |
| } |
| return result; |
| } |
| static std::shared_ptr<::android::nn::ExecutionBurstController> CreateBurst( |
| const sp<IPreparedModel>& preparedModel) { |
| return android::nn::ExecutionBurstController::create(preparedModel, |
| std::chrono::microseconds{0}); |
| } |
| |
| void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel, |
| const TestConfig& testConfig, bool* skipped = nullptr) { |
| if (skipped != nullptr) { |
| *skipped = false; |
| } |
| // If output0 does not have size larger than one byte, we can not test with insufficient buffer. |
| if (testConfig.outputType == OutputType::INSUFFICIENT && |
| !isOutputSizeGreaterThanOne(testModel, 0)) { |
| return; |
| } |
| |
| V1_0::Request request10 = createRequest(testModel); |
| if (testConfig.outputType == OutputType::INSUFFICIENT) { |
| makeOutputInsufficientSize(/*outputIndex=*/0, &request10); |
| } |
| Request request = nn::convertToV1_3(request10); |
| |
| ErrorStatus executionStatus; |
| hidl_vec<OutputShape> outputShapes; |
| Timing timing; |
| switch (testConfig.executor) { |
| case Executor::ASYNC: { |
| SCOPED_TRACE("asynchronous"); |
| |
| // launch execution |
| sp<ExecutionCallback> executionCallback = new ExecutionCallback(); |
| Return<ErrorStatus> executionLaunchStatus = ExecutePreparedModel( |
| preparedModel, request, testConfig.measureTiming, executionCallback); |
| ASSERT_TRUE(executionLaunchStatus.isOk()); |
| EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus)); |
| |
| // retrieve execution status |
| executionCallback->wait(); |
| executionStatus = executionCallback->getStatus(); |
| outputShapes = executionCallback->getOutputShapes(); |
| timing = executionCallback->getTiming(); |
| |
| break; |
| } |
| case Executor::SYNC: { |
| SCOPED_TRACE("synchronous"); |
| |
| // execute |
| Return<ErrorStatus> executionReturnStatus = ExecutePreparedModel( |
| preparedModel, request, testConfig.measureTiming, &outputShapes, &timing); |
| ASSERT_TRUE(executionReturnStatus.isOk()); |
| executionStatus = static_cast<ErrorStatus>(executionReturnStatus); |
| |
| break; |
| } |
| case Executor::BURST: { |
| // TODO(butlermichael): Check if we need to test burst in V1_3 if the interface remains |
| // V1_2. |
| SCOPED_TRACE("burst"); |
| |
| // create burst |
| const std::shared_ptr<::android::nn::ExecutionBurstController> controller = |
| CreateBurst(preparedModel); |
| ASSERT_NE(nullptr, controller.get()); |
| |
| // create memory keys |
| std::vector<intptr_t> keys(request10.pools.size()); |
| for (size_t i = 0; i < keys.size(); ++i) { |
| keys[i] = reinterpret_cast<intptr_t>(&request10.pools[i]); |
| } |
| |
| // execute burst |
| int n; |
| std::tie(n, outputShapes, timing, std::ignore) = |
| controller->compute(request10, testConfig.measureTiming, keys); |
| executionStatus = nn::convertResultCodeToErrorStatus(n); |
| |
| break; |
| } |
| } |
| |
| if (testConfig.outputType != OutputType::FULLY_SPECIFIED && |
| executionStatus == ErrorStatus::GENERAL_FAILURE) { |
| if (skipped != nullptr) { |
| *skipped = true; |
| } |
| if (!testConfig.reportSkipping) { |
| return; |
| } |
| LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot " |
| "execute model that it does not support."; |
| std::cout << "[ ] Early termination of test because vendor service cannot " |
| "execute model that it does not support." |
| << std::endl; |
| GTEST_SKIP(); |
| } |
| if (testConfig.measureTiming == MeasureTiming::NO) { |
| EXPECT_EQ(UINT64_MAX, timing.timeOnDevice); |
| EXPECT_EQ(UINT64_MAX, timing.timeInDriver); |
| } else { |
| if (timing.timeOnDevice != UINT64_MAX && timing.timeInDriver != UINT64_MAX) { |
| EXPECT_LE(timing.timeOnDevice, timing.timeInDriver); |
| } |
| } |
| |
| switch (testConfig.outputType) { |
| case OutputType::FULLY_SPECIFIED: |
| // If the model output operands are fully specified, outputShapes must be either |
| // either empty, or have the same number of elements as the number of outputs. |
| ASSERT_EQ(ErrorStatus::NONE, executionStatus); |
| ASSERT_TRUE(outputShapes.size() == 0 || |
| outputShapes.size() == testModel.outputIndexes.size()); |
| break; |
| case OutputType::UNSPECIFIED: |
| // If the model output operands are not fully specified, outputShapes must have |
| // the same number of elements as the number of outputs. |
| ASSERT_EQ(ErrorStatus::NONE, executionStatus); |
| ASSERT_EQ(outputShapes.size(), testModel.outputIndexes.size()); |
| break; |
| case OutputType::INSUFFICIENT: |
| ASSERT_EQ(ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, executionStatus); |
| ASSERT_EQ(outputShapes.size(), testModel.outputIndexes.size()); |
| ASSERT_FALSE(outputShapes[0].isSufficient); |
| return; |
| } |
| |
| // Go through all outputs, check returned output shapes. |
| for (uint32_t i = 0; i < outputShapes.size(); i++) { |
| EXPECT_TRUE(outputShapes[i].isSufficient); |
| const auto& expect = testModel.operands[testModel.outputIndexes[i]].dimensions; |
| const std::vector<uint32_t> actual = outputShapes[i].dimensions; |
| EXPECT_EQ(expect, actual); |
| } |
| |
| // Retrieve execution results. |
| const std::vector<TestBuffer> outputs = getOutputBuffers(request10); |
| |
| // We want "close-enough" results. |
| checkResults(testModel, outputs); |
| } |
| |
| void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel, |
| TestKind testKind) { |
| std::vector<OutputType> outputTypesList; |
| std::vector<MeasureTiming> measureTimingList; |
| std::vector<Executor> executorList; |
| |
| switch (testKind) { |
| case TestKind::GENERAL: { |
| outputTypesList = {OutputType::FULLY_SPECIFIED}; |
| measureTimingList = {MeasureTiming::NO, MeasureTiming::YES}; |
| executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST}; |
| } break; |
| case TestKind::DYNAMIC_SHAPE: { |
| outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT}; |
| measureTimingList = {MeasureTiming::NO, MeasureTiming::YES}; |
| executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST}; |
| } break; |
| case TestKind::QUANTIZATION_COUPLING: { |
| LOG(FATAL) << "Wrong TestKind for EvaluatePreparedModel"; |
| return; |
| } break; |
| } |
| |
| for (const OutputType outputType : outputTypesList) { |
| for (const MeasureTiming measureTiming : measureTimingList) { |
| for (const Executor executor : executorList) { |
| const TestConfig testConfig(executor, measureTiming, outputType); |
| EvaluatePreparedModel(preparedModel, testModel, testConfig); |
| } |
| } |
| } |
| } |
| |
| void EvaluatePreparedCoupledModels(const sp<IPreparedModel>& preparedModel, |
| const TestModel& testModel, |
| const sp<IPreparedModel>& preparedCoupledModel, |
| const TestModel& coupledModel) { |
| const std::vector<OutputType> outputTypesList = {OutputType::FULLY_SPECIFIED}; |
| const std::vector<MeasureTiming> measureTimingList = {MeasureTiming::NO, MeasureTiming::YES}; |
| const std::vector<Executor> executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST}; |
| |
| for (const OutputType outputType : outputTypesList) { |
| for (const MeasureTiming measureTiming : measureTimingList) { |
| for (const Executor executor : executorList) { |
| const TestConfig testConfig(executor, measureTiming, outputType, |
| /*reportSkipping=*/false); |
| bool baseSkipped = false; |
| EvaluatePreparedModel(preparedModel, testModel, testConfig, &baseSkipped); |
| bool coupledSkipped = false; |
| EvaluatePreparedModel(preparedCoupledModel, coupledModel, testConfig, |
| &coupledSkipped); |
| ASSERT_EQ(baseSkipped, coupledSkipped); |
| if (baseSkipped) { |
| LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot " |
| "execute model that it does not support."; |
| std::cout << "[ ] Early termination of test because vendor service " |
| "cannot " |
| "execute model that it does not support." |
| << std::endl; |
| GTEST_SKIP(); |
| } |
| } |
| } |
| } |
| } |
| |
| void Execute(const sp<IDevice>& device, const TestModel& testModel, TestKind testKind) { |
| Model model = createModel(testModel); |
| if (testKind == TestKind::DYNAMIC_SHAPE) { |
| makeOutputDimensionsUnspecified(&model); |
| } |
| |
| sp<IPreparedModel> preparedModel; |
| switch (testKind) { |
| case TestKind::GENERAL: { |
| createPreparedModel(device, model, &preparedModel); |
| if (preparedModel == nullptr) return; |
| EvaluatePreparedModel(preparedModel, testModel, TestKind::GENERAL); |
| } break; |
| case TestKind::DYNAMIC_SHAPE: { |
| createPreparedModel(device, model, &preparedModel); |
| if (preparedModel == nullptr) return; |
| EvaluatePreparedModel(preparedModel, testModel, TestKind::DYNAMIC_SHAPE); |
| } break; |
| case TestKind::QUANTIZATION_COUPLING: { |
| ASSERT_TRUE(testModel.hasQuant8CoupledOperands()); |
| createPreparedModel(device, model, &preparedModel, /*reportSkipping*/ false); |
| TestModel signedQuantizedModel = convertQuant8AsymmOperandsToSigned(testModel); |
| sp<IPreparedModel> preparedCoupledModel; |
| createPreparedModel(device, createModel(signedQuantizedModel), &preparedCoupledModel, |
| /*reportSkipping*/ false); |
| // If we couldn't prepare a model with unsigned quantization, we must |
| // fail to prepare a model with signed quantization as well. |
| if (preparedModel == nullptr) { |
| ASSERT_EQ(preparedCoupledModel, nullptr); |
| // If we failed to prepare both of the models, we can safely skip |
| // the test. |
| 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(); |
| } |
| ASSERT_NE(preparedCoupledModel, nullptr); |
| EvaluatePreparedCoupledModels(preparedModel, testModel, preparedCoupledModel, |
| signedQuantizedModel); |
| } break; |
| } |
| } |
| |
| void GeneratedTestBase::SetUp() { |
| testing::TestWithParam<GeneratedTestParam>::SetUp(); |
| ASSERT_NE(kDevice, nullptr); |
| } |
| |
| std::vector<NamedModel> getNamedModels(const FilterFn& filter) { |
| return TestModelManager::get().getTestModels(filter); |
| } |
| |
| std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info) { |
| const auto& [namedDevice, namedModel] = info.param; |
| return gtestCompliantName(getName(namedDevice) + "_" + getName(namedModel)); |
| } |
| |
| // Tag for the generated tests |
| class GeneratedTest : public GeneratedTestBase {}; |
| |
| // Tag for the dynamic output shape tests |
| class DynamicOutputShapeTest : public GeneratedTest {}; |
| |
| // Tag for the dynamic output shape tests |
| class QuantizationCouplingTest : public GeneratedTest {}; |
| |
| TEST_P(GeneratedTest, Test) { |
| Execute(kDevice, kTestModel, /*testKind=*/TestKind::GENERAL); |
| } |
| |
| TEST_P(DynamicOutputShapeTest, Test) { |
| Execute(kDevice, kTestModel, /*testKind=*/TestKind::DYNAMIC_SHAPE); |
| } |
| |
| TEST_P(QuantizationCouplingTest, Test) { |
| Execute(kDevice, kTestModel, /*testKind=*/TestKind::QUANTIZATION_COUPLING); |
| } |
| |
| INSTANTIATE_GENERATED_TEST(GeneratedTest, |
| [](const TestModel& testModel) { return !testModel.expectFailure; }); |
| |
| INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest, |
| [](const TestModel& testModel) { return !testModel.expectFailure; }); |
| |
| INSTANTIATE_GENERATED_TEST(QuantizationCouplingTest, [](const TestModel& testModel) { |
| return testModel.hasQuant8CoupledOperands() && testModel.operations.size() == 1; |
| }); |
| |
| } // namespace android::hardware::neuralnetworks::V1_3::vts::functional |