/* * Copyright (C) 2017 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 #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include "AndroidVersionUtil.h" #include "GeneratedTestUtils.h" #include "TestHarness.h" #include "TestNeuralNetworksWrapper.h" #include "TestUtils.h" // Systrace is not available from CTS tests due to platform layering // constraints. We reuse the NNTEST_ONLY_PUBLIC_API flag, as that should also be // the case for CTS (public APIs only). #ifndef NNTEST_ONLY_PUBLIC_API #include #else #define NNTRACE_FULL_RAW(...) #define NNTRACE_APP(...) #define NNTRACE_APP_SWITCH(...) #endif #ifdef NNTEST_CTS #define NNTEST_COMPUTE_MODE #endif namespace android::nn::generated_tests { using namespace test_wrapper; using namespace test_helper; class GeneratedTests : public GeneratedTestBase { protected: void SetUp() override; void TearDown() override; bool shouldSkipTest(); std::optional compileModel(const Model& model); void executeInternal(const Compilation& compilation, const TestModel& testModel, bool testReusableExecution); void executeWithCompilation(const Compilation& compilation, const TestModel& testModel); void executeOnce(const Model& model, const TestModel& testModel); void executeMultithreadedOwnCompilation(const Model& model, const TestModel& testModel); void executeMultithreadedSharedCompilation(const Model& model, const TestModel& testModel); // Test driver for those generated from ml/nn/runtime/test/spec void execute(const TestModel& testModel); // VNDK version of the device under test. static int mVndkVersion; std::string mCacheDir; std::vector mToken; bool mTestCompilationCaching = false; bool mTestDynamicOutputShape = false; bool mExpectFailure = false; bool mTestQuantizationCoupling = false; bool mTestDeviceMemory = false; bool mTestReusableExecution = true; Execution::ComputeMode mComputeMode = Execution::getComputeMode(); }; int GeneratedTests::mVndkVersion = __ANDROID_API_FUTURE__; // Tag for the dynamic output shape tests class DynamicOutputShapeTest : public GeneratedTests { protected: DynamicOutputShapeTest() { mTestDynamicOutputShape = true; } }; // Tag for the fenced execute tests class FencedComputeTest : public GeneratedTests {}; // Tag for the generated validation tests class GeneratedValidationTests : public GeneratedTests { protected: GeneratedValidationTests() { mExpectFailure = true; } }; class QuantizationCouplingTest : public GeneratedTests { protected: QuantizationCouplingTest() { mTestQuantizationCoupling = true; // QuantizationCouplingTest is intended for verifying if a driver supports ASYMM quant8, it // must support SYMM quant8. All the models in QuantizationCouplingTest will also be // executed in other test suites, so there is no need to test reusable execution again. mTestReusableExecution = false; } }; class DeviceMemoryTest : public GeneratedTests { protected: DeviceMemoryTest() { mTestDeviceMemory = true; } }; std::optional GeneratedTests::compileModel(const Model& model) { NNTRACE_APP(NNTRACE_PHASE_COMPILATION, "compileModel"); if (mTestCompilationCaching) { // Compile the model twice with the same token, so that compilation caching will be // exercised if supported by the driver. // No invalid model will be passed to this branch. EXPECT_FALSE(mExpectFailure); Compilation compilation1(&model); EXPECT_EQ(compilation1.setCaching(mCacheDir, mToken), Result::NO_ERROR); EXPECT_EQ(compilation1.finish(), Result::NO_ERROR); Compilation compilation2(&model); EXPECT_EQ(compilation2.setCaching(mCacheDir, mToken), Result::NO_ERROR); EXPECT_EQ(compilation2.finish(), Result::NO_ERROR); return compilation2; } else { Compilation compilation(&model); Result result = compilation.finish(); // For valid model, we check the compilation result == NO_ERROR. // For invalid model, the driver may fail at compilation or execution, so any result code is // permitted at this point. if (mExpectFailure && result != Result::NO_ERROR) return std::nullopt; EXPECT_EQ(result, Result::NO_ERROR); return compilation; } } static ANeuralNetworksMemory* createDeviceMemoryForInput(const Compilation& compilation, uint32_t index) { ANeuralNetworksMemoryDesc* desc = nullptr; EXPECT_EQ(ANeuralNetworksMemoryDesc_create(&desc), ANEURALNETWORKS_NO_ERROR); EXPECT_EQ(ANeuralNetworksMemoryDesc_addInputRole(desc, compilation.getHandle(), index, 1.0f), ANEURALNETWORKS_NO_ERROR); EXPECT_EQ(ANeuralNetworksMemoryDesc_finish(desc), ANEURALNETWORKS_NO_ERROR); ANeuralNetworksMemory* memory = nullptr; EXPECT_EQ(ANeuralNetworksMemory_createFromDesc(desc, &memory), ANEURALNETWORKS_NO_ERROR); ANeuralNetworksMemoryDesc_free(desc); return memory; } static ANeuralNetworksMemory* createDeviceMemoryForOutput(const Compilation& compilation, uint32_t index) { ANeuralNetworksMemoryDesc* desc = nullptr; EXPECT_EQ(ANeuralNetworksMemoryDesc_create(&desc), ANEURALNETWORKS_NO_ERROR); EXPECT_EQ(ANeuralNetworksMemoryDesc_addOutputRole(desc, compilation.getHandle(), index, 1.0f), ANEURALNETWORKS_NO_ERROR); EXPECT_EQ(ANeuralNetworksMemoryDesc_finish(desc), ANEURALNETWORKS_NO_ERROR); ANeuralNetworksMemory* memory = nullptr; EXPECT_EQ(ANeuralNetworksMemory_createFromDesc(desc, &memory), ANEURALNETWORKS_NO_ERROR); ANeuralNetworksMemoryDesc_free(desc); return memory; } static void createRequestWithDeviceMemories(const Compilation& compilation, const TestModel& testModel, Execution* execution, std::vector* inputMemories, std::vector* outputMemories) { ASSERT_NE(execution, nullptr); ASSERT_NE(inputMemories, nullptr); ASSERT_NE(outputMemories, nullptr); // Model inputs. for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) { SCOPED_TRACE("Input index: " + std::to_string(i)); const auto& operand = testModel.main.operands[testModel.main.inputIndexes[i]]; // Omitted input. if (operand.data.size() == 0) { ASSERT_EQ(Result::NO_ERROR, execution->setInput(i, nullptr, 0)); continue; } // Create device memory. ANeuralNetworksMemory* memory = createDeviceMemoryForInput(compilation, i); ASSERT_NE(memory, nullptr); auto& wrapperMemory = inputMemories->emplace_back(memory); // Copy data from TestBuffer to device memory. auto ashmem = TestAshmem::createFrom(operand.data); ASSERT_NE(ashmem, nullptr); ASSERT_EQ(ANeuralNetworksMemory_copy(ashmem->get()->get(), memory), ANEURALNETWORKS_NO_ERROR); ASSERT_EQ(Result::NO_ERROR, execution->setInputFromMemory(i, &wrapperMemory, 0, 0)); } // Model outputs. for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) { SCOPED_TRACE("Output index: " + std::to_string(i)); ANeuralNetworksMemory* memory = createDeviceMemoryForOutput(compilation, i); ASSERT_NE(memory, nullptr); auto& wrapperMemory = outputMemories->emplace_back(memory); ASSERT_EQ(Result::NO_ERROR, execution->setOutputFromMemory(i, &wrapperMemory, 0, 0)); } } static void copyResultsFromDeviceMemories(const TestModel& testModel, const std::vector& outputMemories, std::vector* outputs) { ASSERT_NE(outputs, nullptr); ASSERT_EQ(testModel.main.outputIndexes.size(), outputMemories.size()); outputs->clear(); // Copy out output results. for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) { SCOPED_TRACE("Output index: " + std::to_string(i)); const auto& operand = testModel.main.operands[testModel.main.outputIndexes[i]]; const size_t bufferSize = operand.data.size(); auto& output = outputs->emplace_back(bufferSize); auto ashmem = TestAshmem::createFrom(output); ASSERT_NE(ashmem, nullptr); ASSERT_EQ(ANeuralNetworksMemory_copy(outputMemories[i].get(), ashmem->get()->get()), ANEURALNETWORKS_NO_ERROR); std::copy(ashmem->dataAs(), ashmem->dataAs() + bufferSize, output.getMutable()); } } void GeneratedTests::executeInternal(const Compilation& compilation, const TestModel& testModel, bool testReusableExecution) { NNTRACE_APP(NNTRACE_PHASE_EXECUTION, "executeInternal example"); Execution execution(&compilation); if (__builtin_available(android __NNAPI_FL5_MIN_ANDROID_API__, *)) { execution.setReusable(testReusableExecution); } std::vector outputs; std::vector inputMemories, outputMemories; if (mTestDeviceMemory) { createRequestWithDeviceMemories(compilation, testModel, &execution, &inputMemories, &outputMemories); } else { createRequest(testModel, &execution, &outputs); } const auto computeAndCheckResults = [this, &testModel, &execution, &outputs, &outputMemories] { Result result = execution.compute(mComputeMode); if (mTestDeviceMemory) { copyResultsFromDeviceMemories(testModel, outputMemories, &outputs); } if (result == Result::NO_ERROR && outputs.empty()) { return; } { NNTRACE_APP(NNTRACE_PHASE_RESULTS, "executeInternal example"); if (mExpectFailure) { ASSERT_NE(result, Result::NO_ERROR); return; } else { ASSERT_EQ(result, Result::NO_ERROR); } // Check output dimensions. for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) { SCOPED_TRACE("Output index: " + std::to_string(i)); const auto& output = testModel.main.operands[testModel.main.outputIndexes[i]]; if (output.isIgnored) continue; std::vector actualDimensions; ASSERT_EQ(Result::NO_ERROR, execution.getOutputOperandDimensions(i, &actualDimensions)); ASSERT_EQ(output.dimensions, actualDimensions); } checkResults(testModel, outputs); } }; computeAndCheckResults(); if (testReusableExecution) { computeAndCheckResults(); } } void GeneratedTests::executeWithCompilation(const Compilation& compilation, const TestModel& testModel) { // Single-time and reusable executions have different code paths, so test both. executeInternal(compilation, testModel, /*testReusableExecution=*/false); if (__builtin_available(android __NNAPI_FL5_MIN_ANDROID_API__, *)) { if (mTestReusableExecution) { executeInternal(compilation, testModel, /*testReusableExecution=*/true); } } } static bool isPowerOfTwo(uint32_t x) { return x > 0 && ((x & (x - 1)) == 0); } static void validateCompilationMemoryPreferences(const Compilation& compilation, const TestModel& testModel) { if (__builtin_available(android __NNAPI_FL5_MIN_ANDROID_API__, *)) { for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) { SCOPED_TRACE("Input index: " + std::to_string(i)); uint32_t alignment = 0, padding = 0; ASSERT_EQ(compilation.getPreferredMemoryAlignmentForInput(i, &alignment), Result::NO_ERROR); ASSERT_EQ(compilation.getPreferredMemoryPaddingForInput(i, &padding), Result::NO_ERROR); EXPECT_TRUE(isPowerOfTwo(alignment)) << "alignment: " << alignment; EXPECT_TRUE(isPowerOfTwo(padding)) << "padding: " << padding; } for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) { SCOPED_TRACE("Output index: " + std::to_string(i)); uint32_t alignment = 0, padding = 0; ASSERT_EQ(compilation.getPreferredMemoryAlignmentForOutput(i, &alignment), Result::NO_ERROR); ASSERT_EQ(compilation.getPreferredMemoryPaddingForOutput(i, &padding), Result::NO_ERROR); EXPECT_TRUE(isPowerOfTwo(alignment)) << "alignment: " << alignment; EXPECT_TRUE(isPowerOfTwo(padding)) << "padding: " << padding; } } } void GeneratedTests::executeOnce(const Model& model, const TestModel& testModel) { NNTRACE_APP(NNTRACE_PHASE_OVERALL, "executeOnce"); std::optional compilation = compileModel(model); // Early return if compilation fails. The compilation result code is checked in compileModel. if (!compilation) return; validateCompilationMemoryPreferences(compilation.value(), testModel); executeWithCompilation(compilation.value(), testModel); } void GeneratedTests::executeMultithreadedOwnCompilation(const Model& model, const TestModel& testModel) { NNTRACE_APP(NNTRACE_PHASE_OVERALL, "executeMultithreadedOwnCompilation"); SCOPED_TRACE("MultithreadedOwnCompilation"); std::vector threads; for (int i = 0; i < 10; i++) { threads.push_back(std::thread([&]() { executeOnce(model, testModel); })); } std::for_each(threads.begin(), threads.end(), [](std::thread& t) { t.join(); }); } void GeneratedTests::executeMultithreadedSharedCompilation(const Model& model, const TestModel& testModel) { NNTRACE_APP(NNTRACE_PHASE_OVERALL, "executeMultithreadedSharedCompilation"); SCOPED_TRACE("MultithreadedSharedCompilation"); std::optional compilation = compileModel(model); // Early return if compilation fails. The ompilation result code is checked in compileModel. if (!compilation) return; std::vector threads; for (int i = 0; i < 10; i++) { threads.push_back( std::thread([&]() { executeWithCompilation(compilation.value(), testModel); })); } std::for_each(threads.begin(), threads.end(), [](std::thread& t) { t.join(); }); } // Test driver for those generated from ml/nn/runtime/test/spec void GeneratedTests::execute(const TestModel& testModel) { NNTRACE_APP(NNTRACE_PHASE_OVERALL, "execute"); GeneratedModel model; createModel(testModel, mTestDynamicOutputShape, &model); if (testModel.expectFailure && !model.isValid()) { return; } ASSERT_EQ(model.finish(), Result::NO_ERROR); ASSERT_TRUE(model.isValid()); auto executeInternal = [&testModel, &model, this]() { SCOPED_TRACE("TestCompilationCaching = " + std::to_string(mTestCompilationCaching)); #ifndef NNTEST_MULTITHREADED executeOnce(model, testModel); #else // defined(NNTEST_MULTITHREADED) executeMultithreadedOwnCompilation(model, testModel); executeMultithreadedSharedCompilation(model, testModel); #endif // !defined(NNTEST_MULTITHREADED) }; mTestCompilationCaching = false; executeInternal(); if (!mExpectFailure) { mTestCompilationCaching = true; executeInternal(); } } bool GeneratedTests::shouldSkipTest() { // A map of {min VNDK version -> tests that should be skipped with earlier VNDK versions}. // The listed tests are added in a later release, but exercising old APIs. They should be // skipped if the device has a mixed build of system and vendor partitions. static const std::map> kMapOfMinVndkVersionToTests = { { __ANDROID_API_R__, { "add_broadcast_quant8_all_inputs_as_internal", }, }, }; for (const auto& [minVersion, names] : kMapOfMinVndkVersionToTests) { if (mVndkVersion < minVersion && names.count(kTestName) > 0) { return true; } } return false; } void GeneratedTests::SetUp() { GeneratedTestBase::SetUp(); mVndkVersion = ::android::base::GetIntProperty("ro.vndk.version", __ANDROID_API_FUTURE__); if (shouldSkipTest()) { GTEST_SKIP(); return; } char cacheDirTemp[] = "/data/local/tmp/TestCompilationCachingXXXXXX"; char* cacheDir = mkdtemp(cacheDirTemp); ASSERT_NE(cacheDir, nullptr); mCacheDir = cacheDir; mToken = std::vector(ANEURALNETWORKS_BYTE_SIZE_OF_CACHE_TOKEN, 0); } void GeneratedTests::TearDown() { if (!::testing::Test::HasFailure()) { // TODO: Switch to std::filesystem::remove_all once libc++fs is made available in CTS. // Remove the cache directory specified by path recursively. auto callback = [](const char* child, const struct stat*, int, struct FTW*) { return remove(child); }; nftw(mCacheDir.c_str(), callback, 128, FTW_DEPTH | FTW_MOUNT | FTW_PHYS); } GeneratedTestBase::TearDown(); } #ifdef NNTEST_COMPUTE_MODE TEST_P(GeneratedTests, Sync) { mComputeMode = Execution::ComputeMode::SYNC; execute(testModel); } TEST_P(GeneratedTests, Async) { mComputeMode = Execution::ComputeMode::ASYNC; execute(testModel); } TEST_P(GeneratedTests, Burst) { mComputeMode = Execution::ComputeMode::BURST; execute(testModel); } #else TEST_P(GeneratedTests, Test) { execute(testModel); } #endif TEST_P(DynamicOutputShapeTest, Test) { execute(testModel); } TEST_P(GeneratedValidationTests, Test) { execute(testModel); } TEST_P(QuantizationCouplingTest, Test) { execute(convertQuant8AsymmOperandsToSigned(testModel)); } TEST_P(DeviceMemoryTest, Test) { execute(testModel); } TEST_P(FencedComputeTest, Test) { mComputeMode = Execution::ComputeMode::FENCED; execute(testModel); } INSTANTIATE_GENERATED_TEST(GeneratedTests, [](const TestModel& testModel) { return !testModel.expectFailure; }); INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest, [](const TestModel& testModel) { return !testModel.expectFailure && !testModel.hasScalarOutputs(); }); INSTANTIATE_GENERATED_TEST(GeneratedValidationTests, [](const TestModel& testModel) { return testModel.expectFailure && !testModel.isInfiniteLoopTimeoutTest(); }); INSTANTIATE_GENERATED_TEST(QuantizationCouplingTest, [](const TestModel& testModel) { return !testModel.expectFailure && testModel.main.operations.size() == 1 && testModel.referenced.size() == 0 && testModel.hasQuant8CoupledOperands(); }); INSTANTIATE_GENERATED_TEST(DeviceMemoryTest, [](const TestModel& testModel) { return !testModel.expectFailure && std::all_of(testModel.main.outputIndexes.begin(), testModel.main.outputIndexes.end(), [&testModel](uint32_t index) { return testModel.main.operands[index].data.size() > 0; }); }); INSTANTIATE_GENERATED_TEST(FencedComputeTest, [](const TestModel& testModel) { return !testModel.expectFailure && std::all_of(testModel.main.outputIndexes.begin(), testModel.main.outputIndexes.end(), [&testModel](uint32_t index) { return testModel.main.operands[index].data.size() > 0; }); }); } // namespace android::nn::generated_tests