neuralnetworks/aidl/vts/functional/CompilationCachingTests.cpp

/*
 * 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.
 */

#define LOG_TAG "neuralnetworks_aidl_hal_test"

#include <android-base/logging.h>
#include <android/binder_auto_utils.h>
#include <android/binder_interface_utils.h>
#include <android/binder_status.h>
#include <fcntl.h>
#include <ftw.h>
#include <gtest/gtest.h>
#include <unistd.h>

#include <cstdio>
#include <cstdlib>
#include <iterator>
#include <random>
#include <thread>

#include "Callbacks.h"
#include "GeneratedTestHarness.h"
#include "TestHarness.h"
#include "Utils.h"
#include "VtsHalNeuralnetworks.h"

// Forward declaration of the mobilenet generated test models in
// frameworks/ml/nn/runtime/test/generated/.
namespace generated_tests::mobilenet_224_gender_basic_fixed {
const test_helper::TestModel& get_test_model();
}  // namespace generated_tests::mobilenet_224_gender_basic_fixed

namespace generated_tests::mobilenet_quantized {
const test_helper::TestModel& get_test_model();
}  // namespace generated_tests::mobilenet_quantized

namespace aidl::android::hardware::neuralnetworks::vts::functional {

using namespace test_helper;
using implementation::PreparedModelCallback;

namespace float32_model {

constexpr auto get_test_model = generated_tests::mobilenet_224_gender_basic_fixed::get_test_model;

}  // namespace float32_model

namespace quant8_model {

constexpr auto get_test_model = generated_tests::mobilenet_quantized::get_test_model;

}  // namespace quant8_model

namespace {

enum class AccessMode { READ_WRITE, READ_ONLY, WRITE_ONLY };

// Creates cache handles based on provided file groups.
// The outer vector corresponds to handles and the inner vector is for fds held by each handle.
void createCacheFds(const std::vector<std::string>& files, const std::vector<AccessMode>& mode,
                    std::vector<ndk::ScopedFileDescriptor>* fds) {
    fds->clear();
    fds->reserve(files.size());
    for (uint32_t i = 0; i < files.size(); i++) {
        const auto& file = files[i];
        int fd;
        if (mode[i] == AccessMode::READ_ONLY) {
            fd = open(file.c_str(), O_RDONLY);
        } else if (mode[i] == AccessMode::WRITE_ONLY) {
            fd = open(file.c_str(), O_WRONLY | O_CREAT, S_IRUSR | S_IWUSR);
        } else if (mode[i] == AccessMode::READ_WRITE) {
            fd = open(file.c_str(), O_RDWR | O_CREAT, S_IRUSR | S_IWUSR);
        } else {
            FAIL();
        }
        ASSERT_GE(fd, 0);
        fds->emplace_back(fd);
    }
}

void createCacheFds(const std::vector<std::string>& files, AccessMode mode,
                    std::vector<ndk::ScopedFileDescriptor>* fds) {
    createCacheFds(files, std::vector<AccessMode>(files.size(), mode), fds);
}

// Create a chain of broadcast operations. The second operand is always constant tensor [1].
// For simplicity, activation scalar is shared. The second operand is not shared
// in the model to let driver maintain a non-trivial size of constant data and the corresponding
// data locations in cache.
//
//                --------- activation --------
//                ↓      ↓      ↓             ↓
// E.g. input -> ADD -> ADD -> ADD -> ... -> ADD -> output
//                ↑      ↑      ↑             ↑
//               [1]    [1]    [1]           [1]
//
// This function assumes the operation is either ADD or MUL.
template <typename CppType, TestOperandType operandType>
TestModel createLargeTestModelImpl(TestOperationType op, uint32_t len) {
    EXPECT_TRUE(op == TestOperationType::ADD || op == TestOperationType::MUL);

    // Model operations and operands.
    std::vector<TestOperation> operations(len);
    std::vector<TestOperand> operands(len * 2 + 2);

    // The activation scalar, value = 0.
    operands[0] = {
            .type = TestOperandType::INT32,
            .dimensions = {},
            .numberOfConsumers = len,
            .scale = 0.0f,
            .zeroPoint = 0,
            .lifetime = TestOperandLifeTime::CONSTANT_COPY,
            .data = TestBuffer::createFromVector<int32_t>({0}),
    };

    // The buffer value of the constant second operand. The logical value is always 1.0f.
    CppType bufferValue;
    // The scale of the first and second operand.
    float scale1, scale2;
    if (operandType == TestOperandType::TENSOR_FLOAT32) {
        bufferValue = 1.0f;
        scale1 = 0.0f;
        scale2 = 0.0f;
    } else if (op == TestOperationType::ADD) {
        bufferValue = 1;
        scale1 = 1.0f;
        scale2 = 1.0f;
    } else {
        // To satisfy the constraint on quant8 MUL: input0.scale * input1.scale < output.scale,
        // set input1 to have scale = 0.5f and bufferValue = 2, i.e. 1.0f in floating point.
        bufferValue = 2;
        scale1 = 1.0f;
        scale2 = 0.5f;
    }

    for (uint32_t i = 0; i < len; i++) {
        const uint32_t firstInputIndex = i * 2 + 1;
        const uint32_t secondInputIndex = firstInputIndex + 1;
        const uint32_t outputIndex = secondInputIndex + 1;

        // The first operation input.
        operands[firstInputIndex] = {
                .type = operandType,
                .dimensions = {1},
                .numberOfConsumers = 1,
                .scale = scale1,
                .zeroPoint = 0,
                .lifetime = (i == 0 ? TestOperandLifeTime::MODEL_INPUT
                                    : TestOperandLifeTime::TEMPORARY_VARIABLE),
                .data = (i == 0 ? TestBuffer::createFromVector<CppType>({1}) : TestBuffer()),
        };

        // The second operation input, value = 1.
        operands[secondInputIndex] = {
                .type = operandType,
                .dimensions = {1},
                .numberOfConsumers = 1,
                .scale = scale2,
                .zeroPoint = 0,
                .lifetime = TestOperandLifeTime::CONSTANT_COPY,
                .data = TestBuffer::createFromVector<CppType>({bufferValue}),
        };

        // The operation. All operations share the same activation scalar.
        // The output operand is created as an input in the next iteration of the loop, in the case
        // of all but the last member of the chain; and after the loop as a model output, in the
        // case of the last member of the chain.
        operations[i] = {
                .type = op,
                .inputs = {firstInputIndex, secondInputIndex, /*activation scalar*/ 0},
                .outputs = {outputIndex},
        };
    }

    // For TestOperationType::ADD, output = 1 + 1 * len = len + 1
    // For TestOperationType::MUL, output = 1 * 1 ^ len = 1
    CppType outputResult = static_cast<CppType>(op == TestOperationType::ADD ? len + 1u : 1u);

    // The model output.
    operands.back() = {
            .type = operandType,
            .dimensions = {1},
            .numberOfConsumers = 0,
            .scale = scale1,
            .zeroPoint = 0,
            .lifetime = TestOperandLifeTime::MODEL_OUTPUT,
            .data = TestBuffer::createFromVector<CppType>({outputResult}),
    };

    return {
            .main = {.operands = std::move(operands),
                     .operations = std::move(operations),
                     .inputIndexes = {1},
                     .outputIndexes = {len * 2 + 1}},
            .isRelaxed = false,
    };
}

}  // namespace

// Tag for the compilation caching tests.
class CompilationCachingTestBase : public testing::Test {
  protected:
    CompilationCachingTestBase(std::shared_ptr<IDevice> device, OperandType type)
        : kDevice(std::move(device)), kOperandType(type) {}

    void SetUp() override {
        testing::Test::SetUp();
        ASSERT_NE(kDevice.get(), nullptr);
        const bool deviceIsResponsive =
                ndk::ScopedAStatus::fromStatus(AIBinder_ping(kDevice->asBinder().get())).isOk();
        ASSERT_TRUE(deviceIsResponsive);

        // Create cache directory. The cache directory and a temporary cache file is always created
        // to test the behavior of prepareModelFromCache, even when caching is not supported.
#ifdef __ANDROID__
        char cacheDirTemp[] = "/data/local/tmp/TestCompilationCachingXXXXXX";
#else   // __ANDROID__
        char cacheDirTemp[] = "/tmp/TestCompilationCachingXXXXXX";
#endif  // __ANDROID__
        char* cacheDir = mkdtemp(cacheDirTemp);
        ASSERT_NE(cacheDir, nullptr);
        mCacheDir = cacheDir;
        mCacheDir.push_back('/');

        NumberOfCacheFiles numCacheFiles;
        const auto ret = kDevice->getNumberOfCacheFilesNeeded(&numCacheFiles);
        ASSERT_TRUE(ret.isOk());

        mNumModelCache = numCacheFiles.numModelCache;
        mNumDataCache = numCacheFiles.numDataCache;
        ASSERT_GE(mNumModelCache, 0) << "Invalid numModelCache: " << mNumModelCache;
        ASSERT_GE(mNumDataCache, 0) << "Invalid numDataCache: " << mNumDataCache;
        mIsCachingSupported = mNumModelCache > 0 || mNumDataCache > 0;

        // Create empty cache files.
        mTmpCache = mCacheDir + "tmp";
        for (uint32_t i = 0; i < mNumModelCache; i++) {
            mModelCache.push_back({mCacheDir + "model" + std::to_string(i)});
        }
        for (uint32_t i = 0; i < mNumDataCache; i++) {
            mDataCache.push_back({mCacheDir + "data" + std::to_string(i)});
        }
        // Placeholder handles, use AccessMode::WRITE_ONLY for createCacheFds to create files.
        std::vector<ndk::ScopedFileDescriptor> modelHandle, dataHandle, tmpHandle;
        createCacheFds(mModelCache, AccessMode::WRITE_ONLY, &modelHandle);
        createCacheFds(mDataCache, AccessMode::WRITE_ONLY, &dataHandle);
        createCacheFds({mTmpCache}, AccessMode::WRITE_ONLY, &tmpHandle);

        if (!mIsCachingSupported) {
            LOG(INFO) << "NN VTS: Early termination of test because vendor service does not "
                         "support compilation caching.";
            std::cout << "[          ]   Early termination of test because vendor service does not "
                         "support compilation caching."
                      << std::endl;
        }
    }

    void TearDown() override {
        // If the test passes, remove the tmp directory.  Otherwise, keep it for debugging purposes.
        if (!testing::Test::HasFailure()) {
            // Recursively remove the cache directory specified by mCacheDir.
            auto callback = [](const char* entry, const struct stat*, int, struct FTW*) {
                return remove(entry);
            };
            nftw(mCacheDir.c_str(), callback, 128, FTW_DEPTH | FTW_MOUNT | FTW_PHYS);
        }
        testing::Test::TearDown();
    }

    // Model and examples creators. According to kOperandType, the following methods will return
    // either float32 model/examples or the quant8 variant.
    TestModel createTestModel() {
        if (kOperandType == OperandType::TENSOR_FLOAT32) {
            return float32_model::get_test_model();
        } else {
            return quant8_model::get_test_model();
        }
    }

    TestModel createLargeTestModel(OperationType op, uint32_t len) {
        if (kOperandType == OperandType::TENSOR_FLOAT32) {
            return createLargeTestModelImpl<float, TestOperandType::TENSOR_FLOAT32>(
                    static_cast<TestOperationType>(op), len);
        } else {
            return createLargeTestModelImpl<uint8_t, TestOperandType::TENSOR_QUANT8_ASYMM>(
                    static_cast<TestOperationType>(op), len);
        }
    }

    // See if the service can handle the model.
    bool isModelFullySupported(const Model& model) {
        std::vector<bool> supportedOps;
        const auto supportedCall = kDevice->getSupportedOperations(model, &supportedOps);
        EXPECT_TRUE(supportedCall.isOk());
        EXPECT_EQ(supportedOps.size(), model.main.operations.size());
        if (!supportedCall.isOk() || supportedOps.size() != model.main.operations.size()) {
            return false;
        }
        return std::all_of(supportedOps.begin(), supportedOps.end(),
                           [](bool valid) { return valid; });
    }

    void saveModelToCache(const Model& model,
                          const std::vector<ndk::ScopedFileDescriptor>& modelCache,
                          const std::vector<ndk::ScopedFileDescriptor>& dataCache,
                          std::shared_ptr<IPreparedModel>* preparedModel = nullptr) {
        if (preparedModel != nullptr) *preparedModel = nullptr;

        // Launch prepare model.
        std::shared_ptr<PreparedModelCallback> preparedModelCallback =
                ndk::SharedRefBase::make<PreparedModelCallback>();
        std::vector<uint8_t> cacheToken(std::begin(mToken), std::end(mToken));
        const auto prepareLaunchStatus = kDevice->prepareModel(
                model, ExecutionPreference::FAST_SINGLE_ANSWER, kDefaultPriority, kNoDeadline,
                modelCache, dataCache, cacheToken, preparedModelCallback);
        ASSERT_TRUE(prepareLaunchStatus.isOk());

        // Retrieve prepared model.
        preparedModelCallback->wait();
        ASSERT_EQ(preparedModelCallback->getStatus(), ErrorStatus::NONE);
        if (preparedModel != nullptr) {
            *preparedModel = preparedModelCallback->getPreparedModel();
        }
    }

    bool checkEarlyTermination(ErrorStatus status) {
        if (status == ErrorStatus::GENERAL_FAILURE) {
            LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
                         "save the prepared model that it does not support.";
            std::cout << "[          ]   Early termination of test because vendor service cannot "
                         "save the prepared model that it does not support."
                      << std::endl;
            return true;
        }
        return false;
    }

    bool checkEarlyTermination(const Model& model) {
        if (!isModelFullySupported(model)) {
            LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
                         "prepare model that it does not support.";
            std::cout << "[          ]   Early termination of test because vendor service cannot "
                         "prepare model that it does not support."
                      << std::endl;
            return true;
        }
        return false;
    }

    // If fallbackModel is not provided, call prepareModelFromCache.
    // If fallbackModel is provided, and prepareModelFromCache returns GENERAL_FAILURE,
    // then prepareModel(fallbackModel) will be called.
    // This replicates the behaviour of the runtime when loading a model from cache.
    // NNAPI Shim depends on this behaviour and may try to load the model from cache in
    // prepareModel (shim needs model information when loading from cache).
    void prepareModelFromCache(const std::vector<ndk::ScopedFileDescriptor>& modelCache,
                               const std::vector<ndk::ScopedFileDescriptor>& dataCache,
                               std::shared_ptr<IPreparedModel>* preparedModel, ErrorStatus* status,
                               const Model* fallbackModel = nullptr) {
        // Launch prepare model from cache.
        std::shared_ptr<PreparedModelCallback> preparedModelCallback =
                ndk::SharedRefBase::make<PreparedModelCallback>();
        std::vector<uint8_t> cacheToken(std::begin(mToken), std::end(mToken));
        auto prepareLaunchStatus = kDevice->prepareModelFromCache(
                kNoDeadline, modelCache, dataCache, cacheToken, preparedModelCallback);

        // The shim does not support prepareModelFromCache() properly, but it
        // will still attempt to create a model from cache when modelCache or
        // dataCache is provided in prepareModel(). Instead of failing straight
        // away, we try to utilize that other code path when fallbackModel is
        // set. Note that we cannot verify whether the returned model was
        // actually prepared from cache in that case.
        if (!prepareLaunchStatus.isOk() &&
            prepareLaunchStatus.getExceptionCode() == EX_SERVICE_SPECIFIC &&
            static_cast<ErrorStatus>(prepareLaunchStatus.getServiceSpecificError()) ==
                    ErrorStatus::GENERAL_FAILURE &&
            mIsCachingSupported && fallbackModel != nullptr) {
            preparedModelCallback = ndk::SharedRefBase::make<PreparedModelCallback>();
            prepareLaunchStatus = kDevice->prepareModel(
                    *fallbackModel, ExecutionPreference::FAST_SINGLE_ANSWER, kDefaultPriority,
                    kNoDeadline, modelCache, dataCache, cacheToken, preparedModelCallback);
        }

        ASSERT_TRUE(prepareLaunchStatus.isOk() ||
                    prepareLaunchStatus.getExceptionCode() == EX_SERVICE_SPECIFIC)
                << "prepareLaunchStatus: " << prepareLaunchStatus.getDescription();
        if (!prepareLaunchStatus.isOk()) {
            *preparedModel = nullptr;
            *status = static_cast<ErrorStatus>(prepareLaunchStatus.getServiceSpecificError());
            return;
        }

        // Retrieve prepared model.
        preparedModelCallback->wait();
        *status = preparedModelCallback->getStatus();
        *preparedModel = preparedModelCallback->getPreparedModel();
    }

    // Replicate behaviour of runtime when loading model from cache.
    // Test if prepareModelFromCache behaves correctly when faced with bad
    // arguments. If prepareModelFromCache is not supported (GENERAL_FAILURE),
    // it attempts to call prepareModel with same arguments, which is expected either
    // to not support the model (GENERAL_FAILURE) or return a valid model.
    void verifyModelPreparationBehaviour(const std::vector<ndk::ScopedFileDescriptor>& modelCache,
                                         const std::vector<ndk::ScopedFileDescriptor>& dataCache,
                                         const Model* model, const TestModel& testModel) {
        std::shared_ptr<IPreparedModel> preparedModel;
        ErrorStatus status;

        // Verify that prepareModelFromCache fails either due to bad
        // arguments (INVALID_ARGUMENT) or GENERAL_FAILURE if not supported.
        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status,
                              /*fallbackModel=*/nullptr);
        if (status != ErrorStatus::INVALID_ARGUMENT) {
            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
        }
        ASSERT_EQ(preparedModel, nullptr);

        // If caching is not supported, attempt calling prepareModel.
        if (status == ErrorStatus::GENERAL_FAILURE) {
            // Fallback with prepareModel should succeed regardless of cache files
            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status,
                                  /*fallbackModel=*/model);
            // Unless caching is not supported?
            if (status != ErrorStatus::GENERAL_FAILURE) {
                // But if it is, we should see a valid model.
                ASSERT_EQ(status, ErrorStatus::NONE);
                ASSERT_NE(preparedModel, nullptr);
                EvaluatePreparedModel(kDevice, preparedModel, testModel,
                                      /*testKind=*/TestKind::GENERAL);
            }
        }
    }

    // Absolute path to the temporary cache directory.
    std::string mCacheDir;

    // Groups of file paths for model and data cache in the tmp cache directory, initialized with
    // size = mNum{Model|Data}Cache. The outer vector corresponds to handles and the inner vector is
    // for fds held by each handle.
    std::vector<std::string> mModelCache;
    std::vector<std::string> mDataCache;

    // A separate temporary file path in the tmp cache directory.
    std::string mTmpCache;

    uint8_t mToken[static_cast<uint32_t>(IDevice::BYTE_SIZE_OF_CACHE_TOKEN)] = {};
    uint32_t mNumModelCache;
    uint32_t mNumDataCache;
    bool mIsCachingSupported;

    const std::shared_ptr<IDevice> kDevice;
    // The primary data type of the testModel.
    const OperandType kOperandType;
};

using CompilationCachingTestParam = std::tuple<NamedDevice, OperandType>;

// A parameterized fixture of CompilationCachingTestBase. Every test will run twice, with the first
// pass running with float32 models and the second pass running with quant8 models.
class CompilationCachingTest : public CompilationCachingTestBase,
                               public testing::WithParamInterface<CompilationCachingTestParam> {
  protected:
    CompilationCachingTest()
        : CompilationCachingTestBase(getData(std::get<NamedDevice>(GetParam())),
                                     std::get<OperandType>(GetParam())) {}
};

TEST_P(CompilationCachingTest, CacheSavingAndRetrieval) {
    // Create test HIDL model and compile.
    const TestModel& testModel = createTestModel();
    const Model model = createModel(testModel);
    if (checkEarlyTermination(model)) return;
    std::shared_ptr<IPreparedModel> preparedModel = nullptr;

    // Save the compilation to cache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        saveModelToCache(model, modelCache, dataCache);
    }

    // Retrieve preparedModel from cache.
    {
        preparedModel = nullptr;
        ErrorStatus status;
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status,
                              /*fallbackModel=*/&model);
        if (!mIsCachingSupported) {
            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
            ASSERT_EQ(preparedModel, nullptr);
            return;
        } else if (checkEarlyTermination(status)) {
            ASSERT_EQ(preparedModel, nullptr);
            return;
        } else {
            ASSERT_EQ(status, ErrorStatus::NONE);
            ASSERT_NE(preparedModel, nullptr);
        }
    }

    // Execute and verify results.
    EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
}

TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
    // Create test HIDL model and compile.
    const TestModel& testModel = createTestModel();
    const Model model = createModel(testModel);
    if (checkEarlyTermination(model)) return;
    std::shared_ptr<IPreparedModel> preparedModel = nullptr;

    // Save the compilation to cache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        uint8_t placeholderBytes[] = {0, 0};
        // Write a placeholder integer to the cache.
        // The driver should be able to handle non-empty cache and non-zero fd offset.
        for (uint32_t i = 0; i < modelCache.size(); i++) {
            ASSERT_EQ(write(modelCache[i].get(), &placeholderBytes, sizeof(placeholderBytes)),
                      sizeof(placeholderBytes));
        }
        for (uint32_t i = 0; i < dataCache.size(); i++) {
            ASSERT_EQ(write(dataCache[i].get(), &placeholderBytes, sizeof(placeholderBytes)),
                      sizeof(placeholderBytes));
        }
        saveModelToCache(model, modelCache, dataCache);
    }

    // Retrieve preparedModel from cache.
    {
        preparedModel = nullptr;
        ErrorStatus status;
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        uint8_t placeholderByte = 0;
        // Advance the offset of each handle by one byte.
        // The driver should be able to handle non-zero fd offset.
        for (uint32_t i = 0; i < modelCache.size(); i++) {
            ASSERT_GE(read(modelCache[i].get(), &placeholderByte, 1), 0);
        }
        for (uint32_t i = 0; i < dataCache.size(); i++) {
            ASSERT_GE(read(dataCache[i].get(), &placeholderByte, 1), 0);
        }
        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status,
                              /*fallbackModel=*/&model);
        if (!mIsCachingSupported) {
            ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
            ASSERT_EQ(preparedModel, nullptr);
            return;
        } else if (checkEarlyTermination(status)) {
            ASSERT_EQ(preparedModel, nullptr);
            return;
        } else {
            ASSERT_EQ(status, ErrorStatus::NONE);
            ASSERT_NE(preparedModel, nullptr);
        }
    }

    // Execute and verify results.
    EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
}

TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
    // Create test HIDL model and compile.
    const TestModel& testModel = createTestModel();
    const Model model = createModel(testModel);
    if (checkEarlyTermination(model)) return;

    // Test with number of model cache files greater than mNumModelCache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        // Pass an additional cache file for model cache.
        mModelCache.push_back({mTmpCache});
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        mModelCache.pop_back();
        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
        saveModelToCache(model, modelCache, dataCache, &preparedModel);
        ASSERT_NE(preparedModel, nullptr);
        // Execute and verify results.
        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
        // Check if prepareModelFromCache fails.
        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }

    // Test with number of model cache files smaller than mNumModelCache.
    if (mModelCache.size() > 0) {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        // Pop out the last cache file.
        auto tmp = mModelCache.back();
        mModelCache.pop_back();
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        mModelCache.push_back(tmp);
        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
        saveModelToCache(model, modelCache, dataCache, &preparedModel);
        ASSERT_NE(preparedModel, nullptr);
        // Execute and verify results.
        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
        // Check if prepareModelFromCache fails.
        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }

    // Test with number of data cache files greater than mNumDataCache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        // Pass an additional cache file for data cache.
        mDataCache.push_back({mTmpCache});
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        mDataCache.pop_back();
        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
        saveModelToCache(model, modelCache, dataCache, &preparedModel);
        ASSERT_NE(preparedModel, nullptr);
        // Execute and verify results.
        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
        // Check if prepareModelFromCache fails.
        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }

    // Test with number of data cache files smaller than mNumDataCache.
    if (mDataCache.size() > 0) {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        // Pop out the last cache file.
        auto tmp = mDataCache.back();
        mDataCache.pop_back();
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        mDataCache.push_back(tmp);
        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
        saveModelToCache(model, modelCache, dataCache, &preparedModel);
        ASSERT_NE(preparedModel, nullptr);
        // Execute and verify results.
        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
        // Check if prepareModelFromCache fails.
        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }
}

TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
    // Create test HIDL model and compile.
    const TestModel& testModel = createTestModel();
    const Model model = createModel(testModel);
    if (checkEarlyTermination(model)) return;

    // Save the compilation to cache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        saveModelToCache(model, modelCache, dataCache);
    }

    // Test with number of model cache files greater than mNumModelCache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        mModelCache.push_back({mTmpCache});
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        mModelCache.pop_back();

        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }

    // Test with number of model cache files smaller than mNumModelCache.
    if (mModelCache.size() > 0) {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        auto tmp = mModelCache.back();
        mModelCache.pop_back();
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        mModelCache.push_back(tmp);

        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }

    // Test with number of data cache files greater than mNumDataCache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        mDataCache.push_back({mTmpCache});
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        mDataCache.pop_back();

        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }

    // Test with number of data cache files smaller than mNumDataCache.
    if (mDataCache.size() > 0) {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        auto tmp = mDataCache.back();
        mDataCache.pop_back();
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        mDataCache.push_back(tmp);

        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }
}

TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
    // Create test HIDL model and compile.
    const TestModel& testModel = createTestModel();
    const Model model = createModel(testModel);
    if (checkEarlyTermination(model)) return;
    std::vector<AccessMode> modelCacheMode(mNumModelCache, AccessMode::READ_WRITE);
    std::vector<AccessMode> dataCacheMode(mNumDataCache, AccessMode::READ_WRITE);

    // Go through each handle in model cache, test with invalid access mode.
    for (uint32_t i = 0; i < mNumModelCache; i++) {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        modelCacheMode[i] = AccessMode::READ_ONLY;
        createCacheFds(mModelCache, modelCacheMode, &modelCache);
        createCacheFds(mDataCache, dataCacheMode, &dataCache);
        modelCacheMode[i] = AccessMode::READ_WRITE;
        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
        saveModelToCache(model, modelCache, dataCache, &preparedModel);
        ASSERT_NE(preparedModel, nullptr);
        // Execute and verify results.
        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
        // Check if prepareModelFromCache fails.
        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }

    // Go through each handle in data cache, test with invalid access mode.
    for (uint32_t i = 0; i < mNumDataCache; i++) {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        dataCacheMode[i] = AccessMode::READ_ONLY;
        createCacheFds(mModelCache, modelCacheMode, &modelCache);
        createCacheFds(mDataCache, dataCacheMode, &dataCache);
        dataCacheMode[i] = AccessMode::READ_WRITE;
        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
        saveModelToCache(model, modelCache, dataCache, &preparedModel);
        ASSERT_NE(preparedModel, nullptr);
        // Execute and verify results.
        EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
        // Check if prepareModelFromCache fails.
        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }
}

TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
    // Create test HIDL model and compile.
    const TestModel& testModel = createTestModel();
    const Model model = createModel(testModel);
    if (checkEarlyTermination(model)) return;
    std::vector<AccessMode> modelCacheMode(mNumModelCache, AccessMode::READ_WRITE);
    std::vector<AccessMode> dataCacheMode(mNumDataCache, AccessMode::READ_WRITE);

    // Save the compilation to cache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        saveModelToCache(model, modelCache, dataCache);
    }

    // Go through each handle in model cache, test with invalid access mode.
    for (uint32_t i = 0; i < mNumModelCache; i++) {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        modelCacheMode[i] = AccessMode::WRITE_ONLY;
        createCacheFds(mModelCache, modelCacheMode, &modelCache);
        createCacheFds(mDataCache, dataCacheMode, &dataCache);
        modelCacheMode[i] = AccessMode::READ_WRITE;

        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }

    // Go through each handle in data cache, test with invalid access mode.
    for (uint32_t i = 0; i < mNumDataCache; i++) {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        dataCacheMode[i] = AccessMode::WRITE_ONLY;
        createCacheFds(mModelCache, modelCacheMode, &modelCache);
        createCacheFds(mDataCache, dataCacheMode, &dataCache);
        dataCacheMode[i] = AccessMode::READ_WRITE;
        verifyModelPreparationBehaviour(modelCache, dataCache, &model, testModel);
    }
}

// Copy file contents between files.
// The vector sizes must match.
static void copyCacheFiles(const std::vector<std::string>& from,
                           const std::vector<std::string>& to) {
    constexpr size_t kBufferSize = 1000000;
    uint8_t buffer[kBufferSize];

    ASSERT_EQ(from.size(), to.size());
    for (uint32_t i = 0; i < from.size(); i++) {
        int fromFd = open(from[i].c_str(), O_RDONLY);
        int toFd = open(to[i].c_str(), O_WRONLY | O_CREAT, S_IRUSR | S_IWUSR);
        ASSERT_GE(fromFd, 0);
        ASSERT_GE(toFd, 0);

        ssize_t readBytes;
        while ((readBytes = read(fromFd, &buffer, kBufferSize)) > 0) {
            ASSERT_EQ(write(toFd, &buffer, readBytes), readBytes);
        }
        ASSERT_GE(readBytes, 0);

        close(fromFd);
        close(toFd);
    }
}

// Number of operations in the large test model.
constexpr uint32_t kLargeModelSize = 100;
constexpr uint32_t kNumIterationsTOCTOU = 100;

TEST_P(CompilationCachingTest, SaveToCache_TOCTOU) {
    if (!mIsCachingSupported) return;

    // Create test models and check if fully supported by the service.
    const TestModel testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
    const Model modelMul = createModel(testModelMul);
    if (checkEarlyTermination(modelMul)) return;
    const TestModel testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
    const Model modelAdd = createModel(testModelAdd);
    if (checkEarlyTermination(modelAdd)) return;

    // Save the modelMul compilation to cache.
    auto modelCacheMul = mModelCache;
    for (auto& cache : modelCacheMul) {
        cache.append("_mul");
    }
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        saveModelToCache(modelMul, modelCache, dataCache);
    }

    // Use a different token for modelAdd.
    mToken[0]++;

    // This test is probabilistic, so we run it multiple times.
    for (uint32_t i = 0; i < kNumIterationsTOCTOU; i++) {
        // Save the modelAdd compilation to cache.
        {
            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);

            // Spawn a thread to copy the cache content concurrently while saving to cache.
            std::thread thread(copyCacheFiles, std::cref(modelCacheMul), std::cref(mModelCache));
            saveModelToCache(modelAdd, modelCache, dataCache);
            thread.join();
        }

        // Retrieve preparedModel from cache.
        {
            std::shared_ptr<IPreparedModel> preparedModel = nullptr;
            ErrorStatus status;
            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status,
                                  /*fallbackModel=*/nullptr);

            // The preparation may fail or succeed, but must not crash. If the preparation succeeds,
            // the prepared model must be executed with the correct result and not crash.
            if (status != ErrorStatus::NONE) {
                ASSERT_EQ(preparedModel, nullptr);
            } else {
                ASSERT_NE(preparedModel, nullptr);
                EvaluatePreparedModel(kDevice, preparedModel, testModelAdd,
                                      /*testKind=*/TestKind::GENERAL);
            }
        }
    }
}

TEST_P(CompilationCachingTest, PrepareFromCache_TOCTOU) {
    if (!mIsCachingSupported) return;

    // Create test models and check if fully supported by the service.
    const TestModel testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
    const Model modelMul = createModel(testModelMul);
    if (checkEarlyTermination(modelMul)) return;
    const TestModel testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
    const Model modelAdd = createModel(testModelAdd);
    if (checkEarlyTermination(modelAdd)) return;

    // Save the modelMul compilation to cache.
    auto modelCacheMul = mModelCache;
    for (auto& cache : modelCacheMul) {
        cache.append("_mul");
    }
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        saveModelToCache(modelMul, modelCache, dataCache);
    }

    // Use a different token for modelAdd.
    mToken[0]++;

    // This test is probabilistic, so we run it multiple times.
    for (uint32_t i = 0; i < kNumIterationsTOCTOU; i++) {
        // Save the modelAdd compilation to cache.
        {
            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
            saveModelToCache(modelAdd, modelCache, dataCache);
        }

        // Retrieve preparedModel from cache.
        {
            std::shared_ptr<IPreparedModel> preparedModel = nullptr;
            ErrorStatus status;
            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);

            // Spawn a thread to copy the cache content concurrently while preparing from cache.
            std::thread thread(copyCacheFiles, std::cref(modelCacheMul), std::cref(mModelCache));
            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status,
                                  /*fallbackModel=*/nullptr);
            thread.join();

            // The preparation may fail or succeed, but must not crash. If the preparation succeeds,
            // the prepared model must be executed with the correct result and not crash.
            if (status != ErrorStatus::NONE) {
                ASSERT_EQ(preparedModel, nullptr);
            } else {
                ASSERT_NE(preparedModel, nullptr);
                EvaluatePreparedModel(kDevice, preparedModel, testModelAdd,
                                      /*testKind=*/TestKind::GENERAL);
            }
        }
    }
}

TEST_P(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
    if (!mIsCachingSupported) return;

    // Create test models and check if fully supported by the service.
    const TestModel testModelMul = createLargeTestModel(OperationType::MUL, kLargeModelSize);
    const Model modelMul = createModel(testModelMul);
    if (checkEarlyTermination(modelMul)) return;
    const TestModel testModelAdd = createLargeTestModel(OperationType::ADD, kLargeModelSize);
    const Model modelAdd = createModel(testModelAdd);
    if (checkEarlyTermination(modelAdd)) return;

    // Save the modelMul compilation to cache.
    auto modelCacheMul = mModelCache;
    for (auto& cache : modelCacheMul) {
        cache.append("_mul");
    }
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(modelCacheMul, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        saveModelToCache(modelMul, modelCache, dataCache);
    }

    // Use a different token for modelAdd.
    mToken[0]++;

    // Save the modelAdd compilation to cache.
    {
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        saveModelToCache(modelAdd, modelCache, dataCache);
    }

    // Replace the model cache of modelAdd with modelMul.
    copyCacheFiles(modelCacheMul, mModelCache);

    // Retrieve the preparedModel from cache, expect failure.
    {
        std::shared_ptr<IPreparedModel> preparedModel = nullptr;
        ErrorStatus status;
        std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
        createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
        createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
        prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);
        ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
        ASSERT_EQ(preparedModel, nullptr);
    }
}

// TODO(b/179270601): restore kNamedDeviceChoices.
static const auto kOperandTypeChoices =
        testing::Values(OperandType::TENSOR_FLOAT32, OperandType::TENSOR_QUANT8_ASYMM);

std::string printCompilationCachingTest(
        const testing::TestParamInfo<CompilationCachingTestParam>& info) {
    const auto& [namedDevice, operandType] = info.param;
    const std::string type = (operandType == OperandType::TENSOR_FLOAT32 ? "float32" : "quant8");
    return gtestCompliantName(getName(namedDevice) + "_" + type);
}

GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(CompilationCachingTest);
INSTANTIATE_TEST_SUITE_P(TestCompilationCaching, CompilationCachingTest,
                         testing::Combine(testing::ValuesIn(getNamedDevices()),
                                          kOperandTypeChoices),
                         printCompilationCachingTest);

using CompilationCachingSecurityTestParam = std::tuple<NamedDevice, OperandType, uint32_t>;

class CompilationCachingSecurityTest
    : public CompilationCachingTestBase,
      public testing::WithParamInterface<CompilationCachingSecurityTestParam> {
  protected:
    CompilationCachingSecurityTest()
        : CompilationCachingTestBase(getData(std::get<NamedDevice>(GetParam())),
                                     std::get<OperandType>(GetParam())) {}

    void SetUp() {
        CompilationCachingTestBase::SetUp();
        generator.seed(kSeed);
    }

    // Get a random integer within a closed range [lower, upper].
    template <typename T>
    T getRandomInt(T lower, T upper) {
        std::uniform_int_distribution<T> dis(lower, upper);
        return dis(generator);
    }

    // Randomly flip one single bit of the cache entry.
    void flipOneBitOfCache(const std::string& filename, bool* skip) {
        FILE* pFile = fopen(filename.c_str(), "r+");
        ASSERT_EQ(fseek(pFile, 0, SEEK_END), 0);
        long int fileSize = ftell(pFile);
        if (fileSize == 0) {
            fclose(pFile);
            *skip = true;
            return;
        }
        ASSERT_EQ(fseek(pFile, getRandomInt(0l, fileSize - 1), SEEK_SET), 0);
        int readByte = fgetc(pFile);
        ASSERT_NE(readByte, EOF);
        ASSERT_EQ(fseek(pFile, -1, SEEK_CUR), 0);
        ASSERT_NE(fputc(static_cast<uint8_t>(readByte) ^ (1U << getRandomInt(0, 7)), pFile), EOF);
        fclose(pFile);
        *skip = false;
    }

    // Randomly append bytes to the cache entry.
    void appendBytesToCache(const std::string& filename, bool* skip) {
        FILE* pFile = fopen(filename.c_str(), "a");
        uint32_t appendLength = getRandomInt(1, 256);
        for (uint32_t i = 0; i < appendLength; i++) {
            ASSERT_NE(fputc(getRandomInt<uint8_t>(0, 255), pFile), EOF);
        }
        fclose(pFile);
        *skip = false;
    }

    enum class ExpectedResult { GENERAL_FAILURE, NOT_CRASH };

    // Test if the driver behaves as expected when given corrupted cache or token.
    // The modifier will be invoked after save to cache but before prepare from cache.
    // The modifier accepts one pointer argument "skip" as the returning value, indicating
    // whether the test should be skipped or not.
    void testCorruptedCache(ExpectedResult expected, std::function<void(bool*)> modifier) {
        const TestModel& testModel = createTestModel();
        const Model model = createModel(testModel);
        if (checkEarlyTermination(model)) return;

        // Save the compilation to cache.
        {
            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
            saveModelToCache(model, modelCache, dataCache);
        }

        bool skip = false;
        modifier(&skip);
        if (skip) return;

        // Retrieve preparedModel from cache.
        {
            std::shared_ptr<IPreparedModel> preparedModel = nullptr;
            ErrorStatus status;
            std::vector<ndk::ScopedFileDescriptor> modelCache, dataCache;
            createCacheFds(mModelCache, AccessMode::READ_WRITE, &modelCache);
            createCacheFds(mDataCache, AccessMode::READ_WRITE, &dataCache);
            prepareModelFromCache(modelCache, dataCache, &preparedModel, &status);

            switch (expected) {
                case ExpectedResult::GENERAL_FAILURE:
                    ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
                    ASSERT_EQ(preparedModel, nullptr);
                    break;
                case ExpectedResult::NOT_CRASH:
                    ASSERT_EQ(preparedModel == nullptr, status != ErrorStatus::NONE);
                    break;
                default:
                    FAIL();
            }
        }
    }

    const uint32_t kSeed = std::get<uint32_t>(GetParam());
    std::mt19937 generator;
};

TEST_P(CompilationCachingSecurityTest, CorruptedModelCache) {
    if (!mIsCachingSupported) return;
    for (uint32_t i = 0; i < mNumModelCache; i++) {
        testCorruptedCache(ExpectedResult::GENERAL_FAILURE,
                           [this, i](bool* skip) { flipOneBitOfCache(mModelCache[i], skip); });
    }
}

TEST_P(CompilationCachingSecurityTest, WrongLengthModelCache) {
    if (!mIsCachingSupported) return;
    for (uint32_t i = 0; i < mNumModelCache; i++) {
        testCorruptedCache(ExpectedResult::GENERAL_FAILURE,
                           [this, i](bool* skip) { appendBytesToCache(mModelCache[i], skip); });
    }
}

TEST_P(CompilationCachingSecurityTest, CorruptedDataCache) {
    if (!mIsCachingSupported) return;
    for (uint32_t i = 0; i < mNumDataCache; i++) {
        testCorruptedCache(ExpectedResult::NOT_CRASH,
                           [this, i](bool* skip) { flipOneBitOfCache(mDataCache[i], skip); });
    }
}

TEST_P(CompilationCachingSecurityTest, WrongLengthDataCache) {
    if (!mIsCachingSupported) return;
    for (uint32_t i = 0; i < mNumDataCache; i++) {
        testCorruptedCache(ExpectedResult::NOT_CRASH,
                           [this, i](bool* skip) { appendBytesToCache(mDataCache[i], skip); });
    }
}

TEST_P(CompilationCachingSecurityTest, WrongToken) {
    if (!mIsCachingSupported) return;
    testCorruptedCache(ExpectedResult::GENERAL_FAILURE, [this](bool* skip) {
        // Randomly flip one single bit in mToken.
        uint32_t ind =
                getRandomInt(0u, static_cast<uint32_t>(IDevice::BYTE_SIZE_OF_CACHE_TOKEN) - 1);
        mToken[ind] ^= (1U << getRandomInt(0, 7));
        *skip = false;
    });
}

std::string printCompilationCachingSecurityTest(
        const testing::TestParamInfo<CompilationCachingSecurityTestParam>& info) {
    const auto& [namedDevice, operandType, seed] = info.param;
    const std::string type = (operandType == OperandType::TENSOR_FLOAT32 ? "float32" : "quant8");
    return gtestCompliantName(getName(namedDevice) + "_" + type + "_" + std::to_string(seed));
}

GTEST_ALLOW_UNINSTANTIATED_PARAMETERIZED_TEST(CompilationCachingSecurityTest);
INSTANTIATE_TEST_SUITE_P(TestCompilationCaching, CompilationCachingSecurityTest,
                         testing::Combine(testing::ValuesIn(getNamedDevices()), kOperandTypeChoices,
                                          testing::Range(0U, 10U)),
                         printCompilationCachingSecurityTest);

}  // namespace aidl::android::hardware::neuralnetworks::vts::functional