| /* |
| * Copyright (C) 2021 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 <aidl/android/hardware/neuralnetworks/ErrorStatus.h> |
| #include <aidl/android/hardware/neuralnetworks/RequestMemoryPool.h> |
| #include <android-base/logging.h> |
| #include <android/binder_auto_utils.h> |
| #include <android/sync.h> |
| #include <gtest/gtest.h> |
| |
| #include <algorithm> |
| #include <chrono> |
| #include <iostream> |
| #include <iterator> |
| #include <numeric> |
| #include <vector> |
| |
| #include <MemoryUtils.h> |
| #include <android/binder_status.h> |
| #include <nnapi/Result.h> |
| #include <nnapi/SharedMemory.h> |
| #include <nnapi/Types.h> |
| #include <nnapi/hal/aidl/Conversions.h> |
| #include <nnapi/hal/aidl/Utils.h> |
| |
| #include "Callbacks.h" |
| #include "TestHarness.h" |
| #include "Utils.h" |
| #include "VtsHalNeuralnetworks.h" |
| |
| namespace aidl::android::hardware::neuralnetworks::vts::functional { |
| |
| namespace nn = ::android::nn; |
| using namespace test_helper; |
| using implementation::PreparedModelCallback; |
| |
| namespace { |
| |
| enum class OutputType { FULLY_SPECIFIED, UNSPECIFIED, INSUFFICIENT, MISSED_DEADLINE }; |
| |
| struct TestConfig { |
| Executor executor; |
| bool measureTiming; |
| OutputType outputType; |
| MemoryType memoryType; |
| // `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, bool measureTiming, OutputType outputType, MemoryType memoryType) |
| : executor(executor), |
| measureTiming(measureTiming), |
| outputType(outputType), |
| memoryType(memoryType), |
| reportSkipping(true) {} |
| TestConfig(Executor executor, bool measureTiming, OutputType outputType, MemoryType memoryType, |
| bool reportSkipping) |
| : executor(executor), |
| measureTiming(measureTiming), |
| outputType(outputType), |
| memoryType(memoryType), |
| reportSkipping(reportSkipping) {} |
| }; |
| |
| enum class IOType { INPUT, OUTPUT }; |
| |
| class DeviceMemoryAllocator { |
| public: |
| DeviceMemoryAllocator(const std::shared_ptr<IDevice>& device, |
| const std::shared_ptr<IPreparedModel>& preparedModel, |
| const TestModel& testModel) |
| : kDevice(device), kPreparedModel(preparedModel), kTestModel(testModel) {} |
| |
| // Allocate device memory for a target input/output operand. |
| // Return {IBuffer object, token} if successful. |
| // Return {nullptr, 0} if device memory is not supported. |
| template <IOType ioType> |
| std::pair<std::shared_ptr<IBuffer>, int32_t> allocate(uint32_t index) { |
| std::pair<std::shared_ptr<IBuffer>, int32_t> buffer; |
| allocateInternal<ioType>(index, &buffer); |
| return buffer; |
| } |
| |
| private: |
| template <IOType ioType> |
| void allocateInternal(int32_t index, std::pair<std::shared_ptr<IBuffer>, int32_t>* result) { |
| ASSERT_NE(result, nullptr); |
| |
| // Prepare arguments. |
| BufferRole role = {.modelIndex = 0, .ioIndex = index, .probability = 1.0f}; |
| std::vector<BufferRole> inputRoles, outputRoles; |
| if constexpr (ioType == IOType::INPUT) { |
| inputRoles = {role}; |
| } else { |
| outputRoles = {role}; |
| } |
| |
| // Allocate device memory. |
| DeviceBuffer buffer; |
| IPreparedModelParcel parcel; |
| parcel.preparedModel = kPreparedModel; |
| const auto ret = kDevice->allocate({}, {parcel}, inputRoles, outputRoles, &buffer); |
| |
| // Check allocation results. |
| if (ret.isOk()) { |
| ASSERT_NE(buffer.buffer, nullptr); |
| ASSERT_GT(buffer.token, 0); |
| } else { |
| ASSERT_EQ(ret.getExceptionCode(), EX_SERVICE_SPECIFIC); |
| ASSERT_EQ(static_cast<ErrorStatus>(ret.getServiceSpecificError()), |
| ErrorStatus::GENERAL_FAILURE); |
| buffer.buffer = nullptr; |
| buffer.token = 0; |
| } |
| |
| // Initialize input data from TestBuffer. |
| if constexpr (ioType == IOType::INPUT) { |
| if (buffer.buffer != nullptr) { |
| // TestBuffer -> Shared memory. |
| const auto& testBuffer = |
| kTestModel.main.operands[kTestModel.main.inputIndexes[index]].data; |
| ASSERT_GT(testBuffer.size(), 0); |
| const auto sharedMemory = nn::createSharedMemory(testBuffer.size()).value(); |
| const auto memory = utils::convert(sharedMemory).value(); |
| const auto mapping = nn::map(sharedMemory).value(); |
| uint8_t* inputPtr = static_cast<uint8_t*>(std::get<void*>(mapping.pointer)); |
| ASSERT_NE(inputPtr, nullptr); |
| const uint8_t* begin = testBuffer.get<uint8_t>(); |
| const uint8_t* end = begin + testBuffer.size(); |
| std::copy(begin, end, inputPtr); |
| |
| // Shared memory -> IBuffer. |
| auto ret = buffer.buffer->copyFrom(memory, {}); |
| ASSERT_TRUE(ret.isOk()); |
| } |
| } |
| *result = {std::move(buffer.buffer), buffer.token}; |
| } |
| |
| const std::shared_ptr<IDevice> kDevice; |
| const std::shared_ptr<IPreparedModel> kPreparedModel; |
| const TestModel& kTestModel; |
| }; |
| |
| Subgraph createSubgraph(const TestSubgraph& testSubgraph, uint32_t* constCopySize, |
| std::vector<const TestBuffer*>* constCopies, uint32_t* constRefSize, |
| std::vector<const TestBuffer*>* constReferences) { |
| CHECK(constCopySize != nullptr); |
| CHECK(constCopies != nullptr); |
| CHECK(constRefSize != nullptr); |
| CHECK(constReferences != nullptr); |
| |
| // Operands. |
| std::vector<Operand> operands(testSubgraph.operands.size()); |
| for (uint32_t i = 0; i < testSubgraph.operands.size(); i++) { |
| const auto& op = testSubgraph.operands[i]; |
| |
| DataLocation loc = {}; |
| if (op.lifetime == TestOperandLifeTime::CONSTANT_COPY) { |
| loc = { |
| .poolIndex = 0, |
| .offset = *constCopySize, |
| .length = static_cast<int64_t>(op.data.size()), |
| }; |
| constCopies->push_back(&op.data); |
| *constCopySize += op.data.alignedSize(); |
| } else if (op.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) { |
| loc = { |
| .poolIndex = 0, |
| .offset = *constRefSize, |
| .length = static_cast<int64_t>(op.data.size()), |
| }; |
| constReferences->push_back(&op.data); |
| *constRefSize += op.data.alignedSize(); |
| } else if (op.lifetime == TestOperandLifeTime::SUBGRAPH) { |
| loc = { |
| .poolIndex = 0, |
| .offset = *op.data.get<uint32_t>(), |
| .length = 0, |
| }; |
| } |
| |
| std::optional<OperandExtraParams> extraParams; |
| if (op.type == TestOperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL) { |
| using Tag = OperandExtraParams::Tag; |
| extraParams = OperandExtraParams::make<Tag::channelQuant>(SymmPerChannelQuantParams{ |
| .scales = op.channelQuant.scales, |
| .channelDim = static_cast<int32_t>(op.channelQuant.channelDim)}); |
| } |
| |
| operands[i] = {.type = static_cast<OperandType>(op.type), |
| .dimensions = utils::toSigned(op.dimensions).value(), |
| .scale = op.scale, |
| .zeroPoint = op.zeroPoint, |
| .lifetime = static_cast<OperandLifeTime>(op.lifetime), |
| .location = loc, |
| .extraParams = std::move(extraParams)}; |
| } |
| |
| // Operations. |
| std::vector<Operation> operations(testSubgraph.operations.size()); |
| std::transform(testSubgraph.operations.begin(), testSubgraph.operations.end(), |
| operations.begin(), [](const TestOperation& op) -> Operation { |
| return {.type = static_cast<OperationType>(op.type), |
| .inputs = utils::toSigned(op.inputs).value(), |
| .outputs = utils::toSigned(op.outputs).value()}; |
| }); |
| |
| return {.operands = std::move(operands), |
| .operations = std::move(operations), |
| .inputIndexes = utils::toSigned(testSubgraph.inputIndexes).value(), |
| .outputIndexes = utils::toSigned(testSubgraph.outputIndexes).value()}; |
| } |
| |
| void copyTestBuffers(const std::vector<const TestBuffer*>& buffers, uint8_t* output) { |
| uint32_t offset = 0; |
| for (const TestBuffer* buffer : buffers) { |
| const uint8_t* begin = buffer->get<uint8_t>(); |
| const uint8_t* end = begin + buffer->size(); |
| std::copy(begin, end, output + offset); |
| offset += buffer->alignedSize(); |
| } |
| } |
| |
| } // namespace |
| |
| void waitForSyncFence(int syncFd) { |
| constexpr int kInfiniteTimeout = -1; |
| ASSERT_GT(syncFd, 0); |
| int r = sync_wait(syncFd, kInfiniteTimeout); |
| ASSERT_GE(r, 0); |
| } |
| |
| Model createModel(const TestModel& testModel) { |
| uint32_t constCopySize = 0; |
| uint32_t constRefSize = 0; |
| std::vector<const TestBuffer*> constCopies; |
| std::vector<const TestBuffer*> constReferences; |
| |
| Subgraph mainSubgraph = createSubgraph(testModel.main, &constCopySize, &constCopies, |
| &constRefSize, &constReferences); |
| std::vector<Subgraph> refSubgraphs(testModel.referenced.size()); |
| std::transform(testModel.referenced.begin(), testModel.referenced.end(), refSubgraphs.begin(), |
| [&constCopySize, &constCopies, &constRefSize, |
| &constReferences](const TestSubgraph& testSubgraph) { |
| return createSubgraph(testSubgraph, &constCopySize, &constCopies, |
| &constRefSize, &constReferences); |
| }); |
| |
| // Constant copies. |
| std::vector<uint8_t> operandValues(constCopySize); |
| copyTestBuffers(constCopies, operandValues.data()); |
| |
| // Shared memory. |
| std::vector<nn::SharedMemory> pools = {}; |
| if (constRefSize > 0) { |
| const auto pool = nn::createSharedMemory(constRefSize).value(); |
| pools.push_back(pool); |
| |
| // load data |
| const auto mappedMemory = nn::map(pool).value(); |
| uint8_t* mappedPtr = static_cast<uint8_t*>(std::get<void*>(mappedMemory.pointer)); |
| CHECK(mappedPtr != nullptr); |
| |
| copyTestBuffers(constReferences, mappedPtr); |
| } |
| |
| std::vector<Memory> aidlPools; |
| aidlPools.reserve(pools.size()); |
| for (auto& pool : pools) { |
| auto aidlPool = utils::convert(pool).value(); |
| aidlPools.push_back(std::move(aidlPool)); |
| } |
| |
| return {.main = std::move(mainSubgraph), |
| .referenced = std::move(refSubgraphs), |
| .operandValues = std::move(operandValues), |
| .pools = std::move(aidlPools), |
| .relaxComputationFloat32toFloat16 = testModel.isRelaxed}; |
| } |
| |
| static bool isOutputSizeGreaterThanOne(const TestModel& testModel, uint32_t index) { |
| const auto byteSize = testModel.main.operands[testModel.main.outputIndexes[index]].data.size(); |
| return byteSize > 1u; |
| } |
| |
| static void makeOutputInsufficientSize(uint32_t outputIndex, Request* request) { |
| auto& loc = request->outputs[outputIndex].location; |
| ASSERT_GT(loc.length, 1u); |
| loc.length -= 1u; |
| // Test that the padding is not used for output data. |
| loc.padding += 1u; |
| } |
| |
| static void makeOutputDimensionsUnspecified(Model* model) { |
| for (auto i : model->main.outputIndexes) { |
| auto& dims = model->main.operands[i].dimensions; |
| std::fill(dims.begin(), dims.end(), 0); |
| } |
| } |
| |
| // Manages the lifetime of memory resources used in an execution. |
| class ExecutionContext { |
| public: |
| ExecutionContext(std::shared_ptr<IDevice> device, std::shared_ptr<IPreparedModel> preparedModel) |
| : kDevice(std::move(device)), kPreparedModel(std::move(preparedModel)) {} |
| |
| std::optional<Request> createRequest(const TestModel& testModel, MemoryType memoryType); |
| std::vector<TestBuffer> getOutputBuffers(const TestModel& testModel, |
| const Request& request) const; |
| |
| private: |
| // Get a TestBuffer with data copied from an IBuffer object. |
| void getBuffer(const std::shared_ptr<IBuffer>& buffer, size_t size, |
| TestBuffer* testBuffer) const; |
| |
| static constexpr uint32_t kInputPoolIndex = 0; |
| static constexpr uint32_t kOutputPoolIndex = 1; |
| static constexpr uint32_t kDeviceMemoryBeginIndex = 2; |
| |
| const std::shared_ptr<IDevice> kDevice; |
| const std::shared_ptr<IPreparedModel> kPreparedModel; |
| std::unique_ptr<TestMemoryBase> mInputMemory, mOutputMemory; |
| std::vector<std::shared_ptr<IBuffer>> mBuffers; |
| }; |
| |
| // Returns the number of bytes needed to round up "size" to the nearest multiple of "multiple". |
| static uint32_t roundUpBytesNeeded(uint32_t size, uint32_t multiple) { |
| CHECK(multiple != 0); |
| return ((size + multiple - 1) / multiple) * multiple - size; |
| } |
| |
| std::optional<Request> ExecutionContext::createRequest(const TestModel& testModel, |
| MemoryType memoryType) { |
| // Memory pools are organized as: |
| // - 0: Input shared memory pool |
| // - 1: Output shared memory pool |
| // - [2, 2+i): Input device memories |
| // - [2+i, 2+i+o): Output device memories |
| DeviceMemoryAllocator allocator(kDevice, kPreparedModel, testModel); |
| std::vector<int32_t> tokens; |
| mBuffers.clear(); |
| |
| // Model inputs. |
| std::vector<RequestArgument> inputs(testModel.main.inputIndexes.size()); |
| size_t inputSize = 0; |
| for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) { |
| const auto& op = testModel.main.operands[testModel.main.inputIndexes[i]]; |
| if (op.data.size() == 0) { |
| // Omitted input. |
| inputs[i] = {.hasNoValue = true}; |
| continue; |
| } else if (memoryType == MemoryType::DEVICE) { |
| SCOPED_TRACE("Input index = " + std::to_string(i)); |
| auto [buffer, token] = allocator.allocate<IOType::INPUT>(i); |
| if (buffer != nullptr) { |
| DataLocation loc = {.poolIndex = static_cast<int32_t>(mBuffers.size() + |
| kDeviceMemoryBeginIndex)}; |
| mBuffers.push_back(std::move(buffer)); |
| tokens.push_back(token); |
| inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; |
| continue; |
| } |
| } |
| |
| // Reserve shared memory for input. |
| inputSize += roundUpBytesNeeded(inputSize, nn::kDefaultRequestMemoryAlignment); |
| const auto padding = roundUpBytesNeeded(op.data.size(), nn::kDefaultRequestMemoryPadding); |
| DataLocation loc = {.poolIndex = kInputPoolIndex, |
| .offset = static_cast<int64_t>(inputSize), |
| .length = static_cast<int64_t>(op.data.size()), |
| .padding = static_cast<int64_t>(padding)}; |
| inputSize += (op.data.size() + padding); |
| inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; |
| } |
| |
| // Model outputs. |
| std::vector<RequestArgument> outputs(testModel.main.outputIndexes.size()); |
| size_t outputSize = 0; |
| for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) { |
| const auto& op = testModel.main.operands[testModel.main.outputIndexes[i]]; |
| if (memoryType == MemoryType::DEVICE) { |
| SCOPED_TRACE("Output index = " + std::to_string(i)); |
| auto [buffer, token] = allocator.allocate<IOType::OUTPUT>(i); |
| if (buffer != nullptr) { |
| DataLocation loc = {.poolIndex = static_cast<int32_t>(mBuffers.size() + |
| kDeviceMemoryBeginIndex)}; |
| mBuffers.push_back(std::move(buffer)); |
| tokens.push_back(token); |
| outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; |
| continue; |
| } |
| } |
| |
| // In the case of zero-sized output, we should at least provide a one-byte buffer. |
| // This is because zero-sized tensors are only supported internally to the driver, or |
| // reported in output shapes. It is illegal for the client to pre-specify a zero-sized |
| // tensor as model output. Otherwise, we will have two semantic conflicts: |
| // - "Zero dimension" conflicts with "unspecified dimension". |
| // - "Omitted operand buffer" conflicts with "zero-sized operand buffer". |
| size_t bufferSize = std::max<size_t>(op.data.size(), 1); |
| |
| // Reserve shared memory for output. |
| outputSize += roundUpBytesNeeded(outputSize, nn::kDefaultRequestMemoryAlignment); |
| const auto padding = roundUpBytesNeeded(bufferSize, nn::kDefaultRequestMemoryPadding); |
| DataLocation loc = {.poolIndex = kOutputPoolIndex, |
| .offset = static_cast<int64_t>(outputSize), |
| .length = static_cast<int64_t>(bufferSize), |
| .padding = static_cast<int64_t>(padding)}; |
| outputSize += (bufferSize + padding); |
| outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}}; |
| } |
| |
| if (memoryType == MemoryType::DEVICE && mBuffers.empty()) { |
| return std::nullopt; |
| } |
| |
| // Memory pools. |
| if (memoryType == MemoryType::BLOB_AHWB) { |
| mInputMemory = TestBlobAHWB::create(std::max<size_t>(inputSize, 1)); |
| mOutputMemory = TestBlobAHWB::create(std::max<size_t>(outputSize, 1)); |
| } else { |
| mInputMemory = TestAshmem::create(std::max<size_t>(inputSize, 1)); |
| mOutputMemory = TestAshmem::create(std::max<size_t>(outputSize, 1)); |
| } |
| CHECK_NE(mInputMemory, nullptr); |
| CHECK_NE(mOutputMemory, nullptr); |
| std::vector<RequestMemoryPool> pools; |
| pools.reserve(kDeviceMemoryBeginIndex + mBuffers.size()); |
| |
| auto copiedInputMemory = utils::clone(*mInputMemory->getAidlMemory()); |
| CHECK(copiedInputMemory.has_value()) << copiedInputMemory.error().message; |
| auto copiedOutputMemory = utils::clone(*mOutputMemory->getAidlMemory()); |
| CHECK(copiedOutputMemory.has_value()) << copiedOutputMemory.error().message; |
| |
| pools.push_back(RequestMemoryPool::make<RequestMemoryPool::Tag::pool>( |
| std::move(copiedInputMemory).value())); |
| pools.push_back(RequestMemoryPool::make<RequestMemoryPool::Tag::pool>( |
| std::move(copiedOutputMemory).value())); |
| for (const auto& token : tokens) { |
| pools.push_back(RequestMemoryPool::make<RequestMemoryPool::Tag::token>(token)); |
| } |
| |
| // Copy input data to the input shared memory pool. |
| uint8_t* inputPtr = mInputMemory->getPointer(); |
| for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) { |
| if (!inputs[i].hasNoValue && inputs[i].location.poolIndex == kInputPoolIndex) { |
| const auto& op = testModel.main.operands[testModel.main.inputIndexes[i]]; |
| const uint8_t* begin = op.data.get<uint8_t>(); |
| const uint8_t* end = begin + op.data.size(); |
| std::copy(begin, end, inputPtr + inputs[i].location.offset); |
| } |
| } |
| return Request{ |
| .inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)}; |
| } |
| |
| std::vector<TestBuffer> ExecutionContext::getOutputBuffers(const TestModel& testModel, |
| const Request& request) const { |
| // Copy out output results. |
| uint8_t* outputPtr = mOutputMemory->getPointer(); |
| std::vector<TestBuffer> outputBuffers; |
| for (uint32_t i = 0; i < request.outputs.size(); i++) { |
| const auto& outputLoc = request.outputs[i].location; |
| if (outputLoc.poolIndex == kOutputPoolIndex) { |
| outputBuffers.emplace_back(outputLoc.length, outputPtr + outputLoc.offset); |
| } else { |
| const auto& op = testModel.main.operands[testModel.main.outputIndexes[i]]; |
| if (op.data.size() == 0) { |
| outputBuffers.emplace_back(0, nullptr); |
| } else { |
| SCOPED_TRACE("Output index = " + std::to_string(i)); |
| const uint32_t bufferIndex = outputLoc.poolIndex - kDeviceMemoryBeginIndex; |
| TestBuffer buffer; |
| getBuffer(mBuffers[bufferIndex], op.data.size(), &buffer); |
| outputBuffers.push_back(std::move(buffer)); |
| } |
| } |
| } |
| return outputBuffers; |
| } |
| |
| // Get a TestBuffer with data copied from an IBuffer object. |
| void ExecutionContext::getBuffer(const std::shared_ptr<IBuffer>& buffer, size_t size, |
| TestBuffer* testBuffer) const { |
| // IBuffer -> Shared memory. |
| auto sharedMemory = nn::createSharedMemory(size).value(); |
| auto aidlMemory = utils::convert(sharedMemory).value(); |
| const auto ret = buffer->copyTo(aidlMemory); |
| ASSERT_TRUE(ret.isOk()); |
| |
| // Shared memory -> TestBuffer. |
| const auto outputMemory = nn::map(sharedMemory).value(); |
| const uint8_t* outputPtr = std::visit( |
| [](auto* ptr) { return static_cast<const uint8_t*>(ptr); }, outputMemory.pointer); |
| ASSERT_NE(outputPtr, nullptr); |
| ASSERT_NE(testBuffer, nullptr); |
| *testBuffer = TestBuffer(size, outputPtr); |
| } |
| |
| static bool hasZeroSizedOutput(const TestModel& testModel) { |
| return std::any_of(testModel.main.outputIndexes.begin(), testModel.main.outputIndexes.end(), |
| [&testModel](uint32_t index) { |
| return testModel.main.operands[index].data.size() == 0; |
| }); |
| } |
| |
| void EvaluatePreparedModel(const std::shared_ptr<IDevice>& device, |
| const std::shared_ptr<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; |
| } |
| |
| ExecutionContext context(device, preparedModel); |
| auto maybeRequest = context.createRequest(testModel, testConfig.memoryType); |
| // Skip if testing memory domain but no device memory has been allocated. |
| if (!maybeRequest.has_value()) { |
| return; |
| } |
| |
| Request request = std::move(maybeRequest).value(); |
| |
| constexpr uint32_t kInsufficientOutputIndex = 0; |
| if (testConfig.outputType == OutputType::INSUFFICIENT) { |
| makeOutputInsufficientSize(kInsufficientOutputIndex, &request); |
| } |
| |
| int64_t loopTimeoutDuration = kOmittedTimeoutDuration; |
| // OutputType::MISSED_DEADLINE is only used by |
| // TestKind::INTINITE_LOOP_TIMEOUT tests to verify that an infinite loop is |
| // aborted after a timeout. |
| if (testConfig.outputType == OutputType::MISSED_DEADLINE) { |
| // Override the default loop timeout duration with a small value to |
| // speed up test execution. |
| constexpr int64_t kMillisecond = 1'000'000; |
| loopTimeoutDuration = 1 * kMillisecond; |
| } |
| |
| ErrorStatus executionStatus; |
| std::vector<OutputShape> outputShapes; |
| Timing timing = kNoTiming; |
| switch (testConfig.executor) { |
| case Executor::SYNC: { |
| SCOPED_TRACE("synchronous"); |
| |
| ExecutionResult executionResult; |
| // execute |
| const auto ret = preparedModel->executeSynchronously(request, testConfig.measureTiming, |
| kNoDeadline, loopTimeoutDuration, |
| &executionResult); |
| ASSERT_TRUE(ret.isOk() || ret.getExceptionCode() == EX_SERVICE_SPECIFIC) |
| << ret.getDescription(); |
| if (ret.isOk()) { |
| executionStatus = executionResult.outputSufficientSize |
| ? ErrorStatus::NONE |
| : ErrorStatus::OUTPUT_INSUFFICIENT_SIZE; |
| outputShapes = std::move(executionResult.outputShapes); |
| timing = executionResult.timing; |
| } else { |
| executionStatus = static_cast<ErrorStatus>(ret.getServiceSpecificError()); |
| } |
| break; |
| } |
| case Executor::BURST: { |
| SCOPED_TRACE("burst"); |
| |
| // create burst |
| std::shared_ptr<IBurst> burst; |
| auto ret = preparedModel->configureExecutionBurst(&burst); |
| ASSERT_TRUE(ret.isOk()) << ret.getDescription(); |
| ASSERT_NE(nullptr, burst.get()); |
| |
| // associate a unique slot with each memory pool |
| int64_t currentSlot = 0; |
| std::vector<int64_t> slots; |
| slots.reserve(request.pools.size()); |
| for (const auto& pool : request.pools) { |
| if (pool.getTag() == RequestMemoryPool::Tag::pool) { |
| slots.push_back(currentSlot++); |
| } else { |
| EXPECT_EQ(pool.getTag(), RequestMemoryPool::Tag::token); |
| slots.push_back(-1); |
| } |
| } |
| |
| ExecutionResult executionResult; |
| // execute |
| ret = burst->executeSynchronously(request, slots, testConfig.measureTiming, kNoDeadline, |
| loopTimeoutDuration, &executionResult); |
| ASSERT_TRUE(ret.isOk() || ret.getExceptionCode() == EX_SERVICE_SPECIFIC) |
| << ret.getDescription(); |
| if (ret.isOk()) { |
| executionStatus = executionResult.outputSufficientSize |
| ? ErrorStatus::NONE |
| : ErrorStatus::OUTPUT_INSUFFICIENT_SIZE; |
| outputShapes = std::move(executionResult.outputShapes); |
| timing = executionResult.timing; |
| } else { |
| executionStatus = static_cast<ErrorStatus>(ret.getServiceSpecificError()); |
| } |
| |
| // Mark each slot as unused after the execution. This is unnecessary because the burst |
| // is freed after this scope ends, but this is here to test the functionality. |
| for (int64_t slot : slots) { |
| ret = burst->releaseMemoryResource(slot); |
| ASSERT_TRUE(ret.isOk()) << ret.getDescription(); |
| } |
| |
| break; |
| } |
| case Executor::FENCED: { |
| SCOPED_TRACE("fenced"); |
| ErrorStatus result = ErrorStatus::NONE; |
| FencedExecutionResult executionResult; |
| auto ret = preparedModel->executeFenced(request, {}, testConfig.measureTiming, |
| kNoDeadline, loopTimeoutDuration, kNoDuration, |
| &executionResult); |
| ASSERT_TRUE(ret.isOk() || ret.getExceptionCode() == EX_SERVICE_SPECIFIC) |
| << ret.getDescription(); |
| if (!ret.isOk()) { |
| result = static_cast<ErrorStatus>(ret.getServiceSpecificError()); |
| executionStatus = result; |
| } else if (executionResult.syncFence.get() != -1) { |
| std::vector<ndk::ScopedFileDescriptor> waitFor; |
| auto dupFd = dup(executionResult.syncFence.get()); |
| ASSERT_NE(dupFd, -1); |
| waitFor.emplace_back(dupFd); |
| // If a sync fence is returned, try start another run waiting for the sync fence. |
| ret = preparedModel->executeFenced(request, waitFor, testConfig.measureTiming, |
| kNoDeadline, loopTimeoutDuration, kNoDuration, |
| &executionResult); |
| ASSERT_TRUE(ret.isOk()); |
| waitForSyncFence(executionResult.syncFence.get()); |
| } |
| if (result == ErrorStatus::NONE) { |
| ASSERT_NE(executionResult.callback, nullptr); |
| Timing timingFenced; |
| auto ret = executionResult.callback->getExecutionInfo(&timing, &timingFenced, |
| &executionStatus); |
| ASSERT_TRUE(ret.isOk()); |
| } |
| break; |
| } |
| default: { |
| FAIL() << "Unsupported execution mode for AIDL interface."; |
| } |
| } |
| |
| 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) { |
| EXPECT_EQ(timing, kNoTiming); |
| } else { |
| if (timing.timeOnDevice != -1 && timing.timeInDriver != -1) { |
| EXPECT_LE(timing.timeOnDevice, timing.timeInDriver); |
| } |
| } |
| |
| switch (testConfig.outputType) { |
| case OutputType::FULLY_SPECIFIED: |
| if (testConfig.executor == Executor::FENCED && hasZeroSizedOutput(testModel)) { |
| // Executor::FENCED does not support zero-sized output. |
| ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionStatus); |
| return; |
| } |
| // 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.main.outputIndexes.size()); |
| break; |
| case OutputType::UNSPECIFIED: |
| if (testConfig.executor == Executor::FENCED) { |
| // For Executor::FENCED, the output shape must be fully specified. |
| ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionStatus); |
| return; |
| } |
| // 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.main.outputIndexes.size()); |
| break; |
| case OutputType::INSUFFICIENT: |
| if (testConfig.executor == Executor::FENCED) { |
| // For Executor::FENCED, the output shape must be fully specified. |
| ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionStatus); |
| return; |
| } |
| ASSERT_EQ(ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, executionStatus); |
| ASSERT_EQ(outputShapes.size(), testModel.main.outputIndexes.size()); |
| // Check that all returned output dimensions are at least as fully specified as the |
| // union of the information about the corresponding operand in the model and in the |
| // request. In this test, all model outputs have known rank with all dimensions |
| // unspecified, and no dimensional information is provided in the request. |
| for (uint32_t i = 0; i < outputShapes.size(); i++) { |
| ASSERT_EQ(outputShapes[i].isSufficient, i != kInsufficientOutputIndex); |
| const auto& actual = outputShapes[i].dimensions; |
| const auto& golden = |
| testModel.main.operands[testModel.main.outputIndexes[i]].dimensions; |
| ASSERT_EQ(actual.size(), golden.size()); |
| for (uint32_t j = 0; j < actual.size(); j++) { |
| if (actual[j] == 0) continue; |
| EXPECT_EQ(actual[j], golden[j]) << "index: " << j; |
| } |
| } |
| return; |
| case OutputType::MISSED_DEADLINE: |
| ASSERT_TRUE(executionStatus == ErrorStatus::MISSED_DEADLINE_TRANSIENT || |
| executionStatus == ErrorStatus::MISSED_DEADLINE_PERSISTENT) |
| << "executionStatus = " << executionStatus; |
| 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.main.operands[testModel.main.outputIndexes[i]].dimensions; |
| const auto unsignedActual = nn::toUnsigned(outputShapes[i].dimensions); |
| ASSERT_TRUE(unsignedActual.has_value()); |
| const std::vector<uint32_t>& actual = unsignedActual.value(); |
| EXPECT_EQ(expect, actual); |
| } |
| |
| // Retrieve execution results. |
| const std::vector<TestBuffer> outputs = context.getOutputBuffers(testModel, request); |
| |
| // We want "close-enough" results. |
| checkResults(testModel, outputs); |
| } |
| |
| void EvaluatePreparedModel(const std::shared_ptr<IDevice>& device, |
| const std::shared_ptr<IPreparedModel>& preparedModel, |
| const TestModel& testModel, TestKind testKind) { |
| std::vector<OutputType> outputTypesList; |
| std::vector<bool> measureTimingList; |
| std::vector<Executor> executorList; |
| std::vector<MemoryType> memoryTypeList; |
| |
| switch (testKind) { |
| case TestKind::GENERAL: { |
| outputTypesList = {OutputType::FULLY_SPECIFIED}; |
| measureTimingList = {false, true}; |
| executorList = {Executor::SYNC, Executor::BURST}; |
| memoryTypeList = {MemoryType::ASHMEM}; |
| } break; |
| case TestKind::DYNAMIC_SHAPE: { |
| outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT}; |
| measureTimingList = {false, true}; |
| executorList = {Executor::SYNC, Executor::BURST, Executor::FENCED}; |
| memoryTypeList = {MemoryType::ASHMEM}; |
| } break; |
| case TestKind::MEMORY_DOMAIN: { |
| outputTypesList = {OutputType::FULLY_SPECIFIED}; |
| measureTimingList = {false}; |
| executorList = {Executor::SYNC, Executor::BURST, Executor::FENCED}; |
| memoryTypeList = {MemoryType::BLOB_AHWB, MemoryType::DEVICE}; |
| } break; |
| case TestKind::FENCED_COMPUTE: { |
| outputTypesList = {OutputType::FULLY_SPECIFIED}; |
| measureTimingList = {false, true}; |
| executorList = {Executor::FENCED}; |
| memoryTypeList = {MemoryType::ASHMEM}; |
| } break; |
| case TestKind::QUANTIZATION_COUPLING: { |
| LOG(FATAL) << "Wrong TestKind for EvaluatePreparedModel"; |
| return; |
| } break; |
| case TestKind::INTINITE_LOOP_TIMEOUT: { |
| outputTypesList = {OutputType::MISSED_DEADLINE}; |
| measureTimingList = {false, true}; |
| executorList = {Executor::SYNC, Executor::BURST, Executor::FENCED}; |
| memoryTypeList = {MemoryType::ASHMEM}; |
| } break; |
| } |
| |
| for (const OutputType outputType : outputTypesList) { |
| for (const bool measureTiming : measureTimingList) { |
| for (const Executor executor : executorList) { |
| for (const MemoryType memoryType : memoryTypeList) { |
| const TestConfig testConfig(executor, measureTiming, outputType, memoryType); |
| EvaluatePreparedModel(device, preparedModel, testModel, testConfig); |
| } |
| } |
| } |
| } |
| } |
| |
| void EvaluatePreparedCoupledModels(const std::shared_ptr<IDevice>& device, |
| const std::shared_ptr<IPreparedModel>& preparedModel, |
| const TestModel& testModel, |
| const std::shared_ptr<IPreparedModel>& preparedCoupledModel, |
| const TestModel& coupledModel) { |
| const std::vector<OutputType> outputTypesList = {OutputType::FULLY_SPECIFIED}; |
| const std::vector<bool> measureTimingList = {false, true}; |
| const std::vector<Executor> executorList = {Executor::SYNC, Executor::BURST, Executor::FENCED}; |
| |
| for (const OutputType outputType : outputTypesList) { |
| for (const bool measureTiming : measureTimingList) { |
| for (const Executor executor : executorList) { |
| const TestConfig testConfig(executor, measureTiming, outputType, MemoryType::ASHMEM, |
| /*reportSkipping=*/false); |
| bool baseSkipped = false; |
| EvaluatePreparedModel(device, preparedModel, testModel, testConfig, &baseSkipped); |
| bool coupledSkipped = false; |
| EvaluatePreparedModel(device, 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 std::shared_ptr<IDevice>& device, const TestModel& testModel, |
| TestKind testKind) { |
| Model model = createModel(testModel); |
| if (testKind == TestKind::DYNAMIC_SHAPE) { |
| makeOutputDimensionsUnspecified(&model); |
| } |
| |
| std::shared_ptr<IPreparedModel> preparedModel; |
| switch (testKind) { |
| case TestKind::GENERAL: |
| case TestKind::DYNAMIC_SHAPE: |
| case TestKind::MEMORY_DOMAIN: |
| case TestKind::FENCED_COMPUTE: |
| case TestKind::INTINITE_LOOP_TIMEOUT: { |
| createPreparedModel(device, model, &preparedModel); |
| if (preparedModel == nullptr) return; |
| EvaluatePreparedModel(device, preparedModel, testModel, testKind); |
| } break; |
| case TestKind::QUANTIZATION_COUPLING: { |
| ASSERT_TRUE(testModel.hasQuant8CoupledOperands()); |
| createPreparedModel(device, model, &preparedModel, |
| /*reportSkipping*/ false); |
| TestModel signedQuantizedModel = convertQuant8AsymmOperandsToSigned(testModel); |
| std::shared_ptr<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(device, 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::vector<NamedModel> getNamedModels(const FilterNameFn& 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 memory domain tests |
| class MemoryDomainTest : public GeneratedTest {}; |
| |
| // Tag for the fenced compute tests |
| class FencedComputeTest : public GeneratedTest {}; |
| |
| // Tag for the dynamic output shape tests |
| class QuantizationCouplingTest : public GeneratedTest {}; |
| |
| // Tag for the loop timeout tests |
| class InfiniteLoopTimeoutTest : public GeneratedTest {}; |
| |
| TEST_P(GeneratedTest, Test) { |
| Execute(kDevice, kTestModel, TestKind::GENERAL); |
| } |
| |
| TEST_P(DynamicOutputShapeTest, Test) { |
| Execute(kDevice, kTestModel, TestKind::DYNAMIC_SHAPE); |
| } |
| |
| TEST_P(MemoryDomainTest, Test) { |
| Execute(kDevice, kTestModel, TestKind::MEMORY_DOMAIN); |
| } |
| |
| TEST_P(FencedComputeTest, Test) { |
| Execute(kDevice, kTestModel, TestKind::FENCED_COMPUTE); |
| } |
| |
| TEST_P(QuantizationCouplingTest, Test) { |
| Execute(kDevice, kTestModel, TestKind::QUANTIZATION_COUPLING); |
| } |
| |
| TEST_P(InfiniteLoopTimeoutTest, Test) { |
| Execute(kDevice, kTestModel, TestKind::INTINITE_LOOP_TIMEOUT); |
| } |
| |
| INSTANTIATE_GENERATED_TEST(GeneratedTest, |
| [](const TestModel& testModel) { return !testModel.expectFailure; }); |
| |
| INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest, [](const TestModel& testModel) { |
| return !testModel.expectFailure && !testModel.hasScalarOutputs(); |
| }); |
| |
| INSTANTIATE_GENERATED_TEST(MemoryDomainTest, |
| [](const TestModel& testModel) { return !testModel.expectFailure; }); |
| |
| INSTANTIATE_GENERATED_TEST(FencedComputeTest, |
| [](const TestModel& testModel) { return !testModel.expectFailure; }); |
| |
| INSTANTIATE_GENERATED_TEST(QuantizationCouplingTest, [](const TestModel& testModel) { |
| return !testModel.expectFailure && testModel.hasQuant8CoupledOperands() && |
| testModel.main.operations.size() == 1; |
| }); |
| |
| INSTANTIATE_GENERATED_TEST(InfiniteLoopTimeoutTest, [](const TestModel& testModel) { |
| return testModel.isInfiniteLoopTimeoutTest(); |
| }); |
| |
| } // namespace aidl::android::hardware::neuralnetworks::vts::functional |
