Merge SP1A.210222.001

Change-Id: I49bafb9c4e7adcb330e0e4c01111788b6ed84a00

1 files changed, 731 insertions, 0 deletions

diff --git a/neuralnetworks/aidl/utils/src/Conversions.cpp b/neuralnetworks/aidl/utils/src/Conversions.cpp
new file mode 100644
index 0000000000..db3504bb74
--- /dev/null
+++ b/neuralnetworks/aidl/utils/src/Conversions.cpp
@@ -0,0 +1,731 @@
+/*
+ * 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 "Conversions.h"
+
+#include <aidl/android/hardware/common/NativeHandle.h>
+#include <android-base/logging.h>
+#include <android/hardware_buffer.h>
+#include <cutils/native_handle.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/OperationTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/SharedMemory.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/Validation.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <vndk/hardware_buffer.h>
+
+#include <algorithm>
+#include <chrono>
+#include <functional>
+#include <iterator>
+#include <limits>
+#include <type_traits>
+#include <utility>
+
+#define VERIFY_NON_NEGATIVE(value) \
+    while (UNLIKELY(value < 0)) return NN_ERROR()
+
+namespace {
+
+template <typename Type>
+constexpr std::underlying_type_t<Type> underlyingType(Type value) {
+    return static_cast<std::underlying_type_t<Type>>(value);
+}
+
+constexpr auto kVersion = android::nn::Version::ANDROID_S;
+
+}  // namespace
+
+namespace android::nn {
+namespace {
+
+using ::aidl::android::hardware::common::NativeHandle;
+
+constexpr auto validOperandType(nn::OperandType operandType) {
+    switch (operandType) {
+        case nn::OperandType::FLOAT32:
+        case nn::OperandType::INT32:
+        case nn::OperandType::UINT32:
+        case nn::OperandType::TENSOR_FLOAT32:
+        case nn::OperandType::TENSOR_INT32:
+        case nn::OperandType::TENSOR_QUANT8_ASYMM:
+        case nn::OperandType::BOOL:
+        case nn::OperandType::TENSOR_QUANT16_SYMM:
+        case nn::OperandType::TENSOR_FLOAT16:
+        case nn::OperandType::TENSOR_BOOL8:
+        case nn::OperandType::FLOAT16:
+        case nn::OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL:
+        case nn::OperandType::TENSOR_QUANT16_ASYMM:
+        case nn::OperandType::TENSOR_QUANT8_SYMM:
+        case nn::OperandType::TENSOR_QUANT8_ASYMM_SIGNED:
+        case nn::OperandType::SUBGRAPH:
+            return true;
+        case nn::OperandType::OEM:
+        case nn::OperandType::TENSOR_OEM_BYTE:
+            return false;
+    }
+    return nn::isExtension(operandType);
+}
+
+template <typename Input>
+using UnvalidatedConvertOutput =
+        std::decay_t<decltype(unvalidatedConvert(std::declval<Input>()).value())>;
+
+template <typename Type>
+GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvertVec(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> canonical;
+    canonical.reserve(arguments.size());
+    for (const auto& argument : arguments) {
+        canonical.push_back(NN_TRY(nn::unvalidatedConvert(argument)));
+    }
+    return canonical;
+}
+
+template <typename Type>
+GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvert(
+        const std::vector<Type>& arguments) {
+    return unvalidatedConvertVec(arguments);
+}
+
+template <typename Type>
+GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& halObject) {
+    auto canonical = NN_TRY(nn::unvalidatedConvert(halObject));
+    const auto maybeVersion = validate(canonical);
+    if (!maybeVersion.has_value()) {
+        return error() << maybeVersion.error();
+    }
+    const auto version = maybeVersion.value();
+    if (version > kVersion) {
+        return NN_ERROR() << "Insufficient version: " << version << " vs required " << kVersion;
+    }
+    return canonical;
+}
+
+template <typename Type>
+GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> validatedConvert(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> canonical;
+    canonical.reserve(arguments.size());
+    for (const auto& argument : arguments) {
+        canonical.push_back(NN_TRY(validatedConvert(argument)));
+    }
+    return canonical;
+}
+
+GeneralResult<Handle> unvalidatedConvertHelper(const NativeHandle& aidlNativeHandle) {
+    std::vector<base::unique_fd> fds;
+    fds.reserve(aidlNativeHandle.fds.size());
+    for (const auto& fd : aidlNativeHandle.fds) {
+        const int dupFd = dup(fd.get());
+        if (dupFd == -1) {
+            // TODO(b/120417090): is ANEURALNETWORKS_UNEXPECTED_NULL the correct error to return
+            // here?
+            return NN_ERROR() << "Failed to dup the fd";
+        }
+        fds.emplace_back(dupFd);
+    }
+
+    return Handle{.fds = std::move(fds), .ints = aidlNativeHandle.ints};
+}
+
+struct NativeHandleDeleter {
+    void operator()(native_handle_t* handle) const {
+        if (handle) {
+            native_handle_close(handle);
+            native_handle_delete(handle);
+        }
+    }
+};
+
+using UniqueNativeHandle = std::unique_ptr<native_handle_t, NativeHandleDeleter>;
+
+static nn::GeneralResult<UniqueNativeHandle> nativeHandleFromAidlHandle(
+        const NativeHandle& handle) {
+    std::vector<base::unique_fd> fds;
+    fds.reserve(handle.fds.size());
+    for (const auto& fd : handle.fds) {
+        const int dupFd = dup(fd.get());
+        if (dupFd == -1) {
+            return NN_ERROR() << "Failed to dup the fd";
+        }
+        fds.emplace_back(dupFd);
+    }
+
+    constexpr size_t kIntMax = std::numeric_limits<int>::max();
+    CHECK_LE(handle.fds.size(), kIntMax);
+    CHECK_LE(handle.ints.size(), kIntMax);
+    native_handle_t* nativeHandle = native_handle_create(static_cast<int>(handle.fds.size()),
+                                                         static_cast<int>(handle.ints.size()));
+    if (nativeHandle == nullptr) {
+        return NN_ERROR() << "Failed to create native_handle";
+    }
+    for (size_t i = 0; i < fds.size(); ++i) {
+        nativeHandle->data[i] = fds[i].release();
+    }
+    std::copy(handle.ints.begin(), handle.ints.end(), &nativeHandle->data[nativeHandle->numFds]);
+
+    return UniqueNativeHandle(nativeHandle);
+}
+
+}  // anonymous namespace
+
+GeneralResult<OperandType> unvalidatedConvert(const aidl_hal::OperandType& operandType) {
+    VERIFY_NON_NEGATIVE(underlyingType(operandType)) << "Negative operand types are not allowed.";
+    return static_cast<OperandType>(operandType);
+}
+
+GeneralResult<OperationType> unvalidatedConvert(const aidl_hal::OperationType& operationType) {
+    VERIFY_NON_NEGATIVE(underlyingType(operationType))
+            << "Negative operation types are not allowed.";
+    return static_cast<OperationType>(operationType);
+}
+
+GeneralResult<DeviceType> unvalidatedConvert(const aidl_hal::DeviceType& deviceType) {
+    return static_cast<DeviceType>(deviceType);
+}
+
+GeneralResult<Priority> unvalidatedConvert(const aidl_hal::Priority& priority) {
+    return static_cast<Priority>(priority);
+}
+
+GeneralResult<Capabilities> unvalidatedConvert(const aidl_hal::Capabilities& capabilities) {
+    const bool validOperandTypes = std::all_of(
+            capabilities.operandPerformance.begin(), capabilities.operandPerformance.end(),
+            [](const aidl_hal::OperandPerformance& operandPerformance) {
+                const auto maybeType = unvalidatedConvert(operandPerformance.type);
+                return !maybeType.has_value() ? false : validOperandType(maybeType.value());
+            });
+    if (!validOperandTypes) {
+        return NN_ERROR() << "Invalid OperandType when unvalidatedConverting OperandPerformance in "
+                             "Capabilities";
+    }
+
+    auto operandPerformance = NN_TRY(unvalidatedConvert(capabilities.operandPerformance));
+    auto table = NN_TRY(hal::utils::makeGeneralFailure(
+            Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)),
+            nn::ErrorStatus::GENERAL_FAILURE));
+
+    return Capabilities{
+            .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
+                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
+            .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
+                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
+            .operandPerformance = std::move(table),
+            .ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance)),
+            .whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance)),
+    };
+}
+
+GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
+        const aidl_hal::OperandPerformance& operandPerformance) {
+    return Capabilities::OperandPerformance{
+            .type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
+            .info = NN_TRY(unvalidatedConvert(operandPerformance.info)),
+    };
+}
+
+GeneralResult<Capabilities::PerformanceInfo> unvalidatedConvert(
+        const aidl_hal::PerformanceInfo& performanceInfo) {
+    return Capabilities::PerformanceInfo{
+            .execTime = performanceInfo.execTime,
+            .powerUsage = performanceInfo.powerUsage,
+    };
+}
+
+GeneralResult<DataLocation> unvalidatedConvert(const aidl_hal::DataLocation& location) {
+    VERIFY_NON_NEGATIVE(location.poolIndex) << "DataLocation: pool index must not be negative";
+    VERIFY_NON_NEGATIVE(location.offset) << "DataLocation: offset must not be negative";
+    VERIFY_NON_NEGATIVE(location.length) << "DataLocation: length must not be negative";
+    if (location.offset > std::numeric_limits<uint32_t>::max()) {
+        return NN_ERROR() << "DataLocation: offset must be <= std::numeric_limits<uint32_t>::max()";
+    }
+    if (location.length > std::numeric_limits<uint32_t>::max()) {
+        return NN_ERROR() << "DataLocation: length must be <= std::numeric_limits<uint32_t>::max()";
+    }
+    return DataLocation{
+            .poolIndex = static_cast<uint32_t>(location.poolIndex),
+            .offset = static_cast<uint32_t>(location.offset),
+            .length = static_cast<uint32_t>(location.length),
+    };
+}
+
+GeneralResult<Operation> unvalidatedConvert(const aidl_hal::Operation& operation) {
+    return Operation{
+            .type = NN_TRY(unvalidatedConvert(operation.type)),
+            .inputs = NN_TRY(toUnsigned(operation.inputs)),
+            .outputs = NN_TRY(toUnsigned(operation.outputs)),
+    };
+}
+
+GeneralResult<Operand::LifeTime> unvalidatedConvert(
+        const aidl_hal::OperandLifeTime& operandLifeTime) {
+    return static_cast<Operand::LifeTime>(operandLifeTime);
+}
+
+GeneralResult<Operand> unvalidatedConvert(const aidl_hal::Operand& operand) {
+    return Operand{
+            .type = NN_TRY(unvalidatedConvert(operand.type)),
+            .dimensions = NN_TRY(toUnsigned(operand.dimensions)),
+            .scale = operand.scale,
+            .zeroPoint = operand.zeroPoint,
+            .lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),
+            .location = NN_TRY(unvalidatedConvert(operand.location)),
+            .extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),
+    };
+}
+
+GeneralResult<Operand::ExtraParams> unvalidatedConvert(
+        const std::optional<aidl_hal::OperandExtraParams>& optionalExtraParams) {
+    if (!optionalExtraParams.has_value()) {
+        return Operand::NoParams{};
+    }
+    const auto& extraParams = optionalExtraParams.value();
+    using Tag = aidl_hal::OperandExtraParams::Tag;
+    switch (extraParams.getTag()) {
+        case Tag::channelQuant:
+            return unvalidatedConvert(extraParams.get<Tag::channelQuant>());
+        case Tag::extension:
+            return extraParams.get<Tag::extension>();
+    }
+    return NN_ERROR() << "Unrecognized Operand::ExtraParams tag: "
+                      << underlyingType(extraParams.getTag());
+}
+
+GeneralResult<Operand::SymmPerChannelQuantParams> unvalidatedConvert(
+        const aidl_hal::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
+    VERIFY_NON_NEGATIVE(symmPerChannelQuantParams.channelDim)
+            << "Per-channel quantization channel dimension must not be negative.";
+    return Operand::SymmPerChannelQuantParams{
+            .scales = symmPerChannelQuantParams.scales,
+            .channelDim = static_cast<uint32_t>(symmPerChannelQuantParams.channelDim),
+    };
+}
+
+GeneralResult<Model> unvalidatedConvert(const aidl_hal::Model& model) {
+    return Model{
+            .main = NN_TRY(unvalidatedConvert(model.main)),
+            .referenced = NN_TRY(unvalidatedConvert(model.referenced)),
+            .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
+            .pools = NN_TRY(unvalidatedConvert(model.pools)),
+            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
+            .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
+    };
+}
+
+GeneralResult<Model::Subgraph> unvalidatedConvert(const aidl_hal::Subgraph& subgraph) {
+    return Model::Subgraph{
+            .operands = NN_TRY(unvalidatedConvert(subgraph.operands)),
+            .operations = NN_TRY(unvalidatedConvert(subgraph.operations)),
+            .inputIndexes = NN_TRY(toUnsigned(subgraph.inputIndexes)),
+            .outputIndexes = NN_TRY(toUnsigned(subgraph.outputIndexes)),
+    };
+}
+
+GeneralResult<Model::ExtensionNameAndPrefix> unvalidatedConvert(
+        const aidl_hal::ExtensionNameAndPrefix& extensionNameAndPrefix) {
+    return Model::ExtensionNameAndPrefix{
+            .name = extensionNameAndPrefix.name,
+            .prefix = extensionNameAndPrefix.prefix,
+    };
+}
+
+GeneralResult<Extension> unvalidatedConvert(const aidl_hal::Extension& extension) {
+    return Extension{
+            .name = extension.name,
+            .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
+    };
+}
+
+GeneralResult<Extension::OperandTypeInformation> unvalidatedConvert(
+        const aidl_hal::ExtensionOperandTypeInformation& operandTypeInformation) {
+    VERIFY_NON_NEGATIVE(operandTypeInformation.byteSize)
+            << "Extension operand type byte size must not be negative";
+    return Extension::OperandTypeInformation{
+            .type = operandTypeInformation.type,
+            .isTensor = operandTypeInformation.isTensor,
+            .byteSize = static_cast<uint32_t>(operandTypeInformation.byteSize),
+    };
+}
+
+GeneralResult<OutputShape> unvalidatedConvert(const aidl_hal::OutputShape& outputShape) {
+    return OutputShape{
+            .dimensions = NN_TRY(toUnsigned(outputShape.dimensions)),
+            .isSufficient = outputShape.isSufficient,
+    };
+}
+
+GeneralResult<MeasureTiming> unvalidatedConvert(bool measureTiming) {
+    return measureTiming ? MeasureTiming::YES : MeasureTiming::NO;
+}
+
+static uint32_t roundUpToMultiple(uint32_t value, uint32_t multiple) {
+    return (value + multiple - 1) / multiple * multiple;
+}
+
+GeneralResult<SharedMemory> unvalidatedConvert(const aidl_hal::Memory& memory) {
+    VERIFY_NON_NEGATIVE(memory.size) << "Memory size must not be negative";
+    if (memory.size > std::numeric_limits<uint32_t>::max()) {
+        return NN_ERROR() << "Memory: size must be <= std::numeric_limits<size_t>::max()";
+    }
+
+    if (memory.name != "hardware_buffer_blob") {
+        return std::make_shared<const Memory>(Memory{
+                .handle = NN_TRY(unvalidatedConvertHelper(memory.handle)),
+                .size = static_cast<uint32_t>(memory.size),
+                .name = memory.name,
+        });
+    }
+
+    const auto size = static_cast<uint32_t>(memory.size);
+    const auto format = AHARDWAREBUFFER_FORMAT_BLOB;
+    const auto usage = AHARDWAREBUFFER_USAGE_CPU_READ_OFTEN | AHARDWAREBUFFER_USAGE_CPU_WRITE_OFTEN;
+    const uint32_t width = size;
+    const uint32_t height = 1;  // height is always 1 for BLOB mode AHardwareBuffer.
+    const uint32_t layers = 1;  // layers is always 1 for BLOB mode AHardwareBuffer.
+
+    const UniqueNativeHandle handle = NN_TRY(nativeHandleFromAidlHandle(memory.handle));
+    const native_handle_t* nativeHandle = handle.get();
+
+    // AHardwareBuffer_createFromHandle() might fail because an allocator
+    // expects a specific stride value. In that case, we try to guess it by
+    // aligning the width to small powers of 2.
+    // TODO(b/174120849): Avoid stride assumptions.
+    AHardwareBuffer* hardwareBuffer = nullptr;
+    status_t status = UNKNOWN_ERROR;
+    for (uint32_t alignment : {1, 4, 32, 64, 128, 2, 8, 16}) {
+        const uint32_t stride = roundUpToMultiple(width, alignment);
+        AHardwareBuffer_Desc desc{
+                .width = width,
+                .height = height,
+                .layers = layers,
+                .format = format,
+                .usage = usage,
+                .stride = stride,
+        };
+        status = AHardwareBuffer_createFromHandle(&desc, nativeHandle,
+                                                  AHARDWAREBUFFER_CREATE_FROM_HANDLE_METHOD_CLONE,
+                                                  &hardwareBuffer);
+        if (status == NO_ERROR) {
+            break;
+        }
+    }
+    if (status != NO_ERROR) {
+        return NN_ERROR(ErrorStatus::GENERAL_FAILURE)
+               << "Can't create AHardwareBuffer from handle. Error: " << status;
+    }
+
+    return std::make_shared<const Memory>(Memory{
+            .handle = HardwareBufferHandle(hardwareBuffer, /*takeOwnership=*/true),
+            .size = static_cast<uint32_t>(memory.size),
+            .name = memory.name,
+    });
+}
+
+GeneralResult<Model::OperandValues> unvalidatedConvert(const std::vector<uint8_t>& operandValues) {
+    return Model::OperandValues(operandValues.data(), operandValues.size());
+}
+
+GeneralResult<BufferDesc> unvalidatedConvert(const aidl_hal::BufferDesc& bufferDesc) {
+    return BufferDesc{.dimensions = NN_TRY(toUnsigned(bufferDesc.dimensions))};
+}
+
+GeneralResult<BufferRole> unvalidatedConvert(const aidl_hal::BufferRole& bufferRole) {
+    VERIFY_NON_NEGATIVE(bufferRole.modelIndex) << "BufferRole: modelIndex must not be negative";
+    VERIFY_NON_NEGATIVE(bufferRole.ioIndex) << "BufferRole: ioIndex must not be negative";
+    return BufferRole{
+            .modelIndex = static_cast<uint32_t>(bufferRole.modelIndex),
+            .ioIndex = static_cast<uint32_t>(bufferRole.ioIndex),
+            .frequency = bufferRole.frequency,
+    };
+}
+
+GeneralResult<Request> unvalidatedConvert(const aidl_hal::Request& request) {
+    return Request{
+            .inputs = NN_TRY(unvalidatedConvert(request.inputs)),
+            .outputs = NN_TRY(unvalidatedConvert(request.outputs)),
+            .pools = NN_TRY(unvalidatedConvert(request.pools)),
+    };
+}
+
+GeneralResult<Request::Argument> unvalidatedConvert(const aidl_hal::RequestArgument& argument) {
+    const auto lifetime = argument.hasNoValue ? Request::Argument::LifeTime::NO_VALUE
+                                              : Request::Argument::LifeTime::POOL;
+    return Request::Argument{
+            .lifetime = lifetime,
+            .location = NN_TRY(unvalidatedConvert(argument.location)),
+            .dimensions = NN_TRY(toUnsigned(argument.dimensions)),
+    };
+}
+
+GeneralResult<Request::MemoryPool> unvalidatedConvert(
+        const aidl_hal::RequestMemoryPool& memoryPool) {
+    using Tag = aidl_hal::RequestMemoryPool::Tag;
+    switch (memoryPool.getTag()) {
+        case Tag::pool:
+            return unvalidatedConvert(memoryPool.get<Tag::pool>());
+        case Tag::token: {
+            const auto token = memoryPool.get<Tag::token>();
+            VERIFY_NON_NEGATIVE(token) << "Memory pool token must not be negative";
+            return static_cast<Request::MemoryDomainToken>(token);
+        }
+    }
+    return NN_ERROR() << "Invalid Request::MemoryPool tag " << underlyingType(memoryPool.getTag());
+}
+
+GeneralResult<ErrorStatus> unvalidatedConvert(const aidl_hal::ErrorStatus& status) {
+    switch (status) {
+        case aidl_hal::ErrorStatus::NONE:
+        case aidl_hal::ErrorStatus::DEVICE_UNAVAILABLE:
+        case aidl_hal::ErrorStatus::GENERAL_FAILURE:
+        case aidl_hal::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE:
+        case aidl_hal::ErrorStatus::INVALID_ARGUMENT:
+        case aidl_hal::ErrorStatus::MISSED_DEADLINE_TRANSIENT:
+        case aidl_hal::ErrorStatus::MISSED_DEADLINE_PERSISTENT:
+        case aidl_hal::ErrorStatus::RESOURCE_EXHAUSTED_TRANSIENT:
+        case aidl_hal::ErrorStatus::RESOURCE_EXHAUSTED_PERSISTENT:
+            return static_cast<ErrorStatus>(status);
+    }
+    return NN_ERROR() << "Invalid ErrorStatus " << underlyingType(status);
+}
+
+GeneralResult<ExecutionPreference> unvalidatedConvert(
+        const aidl_hal::ExecutionPreference& executionPreference) {
+    return static_cast<ExecutionPreference>(executionPreference);
+}
+
+GeneralResult<SharedHandle> unvalidatedConvert(const NativeHandle& aidlNativeHandle) {
+    return std::make_shared<const Handle>(NN_TRY(unvalidatedConvertHelper(aidlNativeHandle)));
+}
+
+GeneralResult<ExecutionPreference> convert(
+        const aidl_hal::ExecutionPreference& executionPreference) {
+    return validatedConvert(executionPreference);
+}
+
+GeneralResult<SharedMemory> convert(const aidl_hal::Memory& operand) {
+    return validatedConvert(operand);
+}
+
+GeneralResult<Model> convert(const aidl_hal::Model& model) {
+    return validatedConvert(model);
+}
+
+GeneralResult<Operand> convert(const aidl_hal::Operand& operand) {
+    return unvalidatedConvert(operand);
+}
+
+GeneralResult<OperandType> convert(const aidl_hal::OperandType& operandType) {
+    return unvalidatedConvert(operandType);
+}
+
+GeneralResult<Priority> convert(const aidl_hal::Priority& priority) {
+    return validatedConvert(priority);
+}
+
+GeneralResult<Request::MemoryPool> convert(const aidl_hal::RequestMemoryPool& memoryPool) {
+    return unvalidatedConvert(memoryPool);
+}
+
+GeneralResult<Request> convert(const aidl_hal::Request& request) {
+    return validatedConvert(request);
+}
+
+GeneralResult<std::vector<Operation>> convert(const std::vector<aidl_hal::Operation>& operations) {
+    return unvalidatedConvert(operations);
+}
+
+GeneralResult<std::vector<SharedMemory>> convert(const std::vector<aidl_hal::Memory>& memories) {
+    return validatedConvert(memories);
+}
+
+GeneralResult<std::vector<uint32_t>> toUnsigned(const std::vector<int32_t>& vec) {
+    if (!std::all_of(vec.begin(), vec.end(), [](int32_t v) { return v >= 0; })) {
+        return NN_ERROR() << "Negative value passed to conversion from signed to unsigned";
+    }
+    return std::vector<uint32_t>(vec.begin(), vec.end());
+}
+
+}  // namespace android::nn
+
+namespace aidl::android::hardware::neuralnetworks::utils {
+namespace {
+
+template <typename Input>
+using UnvalidatedConvertOutput =
+        std::decay_t<decltype(unvalidatedConvert(std::declval<Input>()).value())>;
+
+template <typename Type>
+nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvertVec(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> halObject(arguments.size());
+    for (size_t i = 0; i < arguments.size(); ++i) {
+        halObject[i] = NN_TRY(unvalidatedConvert(arguments[i]));
+    }
+    return halObject;
+}
+
+template <typename Type>
+nn::GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& canonical) {
+    const auto maybeVersion = nn::validate(canonical);
+    if (!maybeVersion.has_value()) {
+        return nn::error() << maybeVersion.error();
+    }
+    const auto version = maybeVersion.value();
+    if (version > kVersion) {
+        return NN_ERROR() << "Insufficient version: " << version << " vs required " << kVersion;
+    }
+    return utils::unvalidatedConvert(canonical);
+}
+
+template <typename Type>
+nn::GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> validatedConvert(
+        const std::vector<Type>& arguments) {
+    std::vector<UnvalidatedConvertOutput<Type>> halObject(arguments.size());
+    for (size_t i = 0; i < arguments.size(); ++i) {
+        halObject[i] = NN_TRY(validatedConvert(arguments[i]));
+    }
+    return halObject;
+}
+
+nn::GeneralResult<common::NativeHandle> unvalidatedConvert(const nn::Handle& handle) {
+    common::NativeHandle aidlNativeHandle;
+    aidlNativeHandle.fds.reserve(handle.fds.size());
+    for (const auto& fd : handle.fds) {
+        const int dupFd = dup(fd.get());
+        if (dupFd == -1) {
+            // TODO(b/120417090): is ANEURALNETWORKS_UNEXPECTED_NULL the correct error to return
+            // here?
+            return NN_ERROR() << "Failed to dup the fd";
+        }
+        aidlNativeHandle.fds.emplace_back(dupFd);
+    }
+    aidlNativeHandle.ints = handle.ints;
+    return aidlNativeHandle;
+}
+
+static nn::GeneralResult<common::NativeHandle> aidlHandleFromNativeHandle(
+        const native_handle_t& handle) {
+    common::NativeHandle aidlNativeHandle;
+
+    aidlNativeHandle.fds.reserve(handle.numFds);
+    for (int i = 0; i < handle.numFds; ++i) {
+        const int dupFd = dup(handle.data[i]);
+        if (dupFd == -1) {
+            return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Failed to dup the fd";
+        }
+        aidlNativeHandle.fds.emplace_back(dupFd);
+    }
+
+    aidlNativeHandle.ints = std::vector<int>(&handle.data[handle.numFds],
+                                             &handle.data[handle.numFds + handle.numInts]);
+
+    return aidlNativeHandle;
+}
+
+}  // namespace
+
+nn::GeneralResult<common::NativeHandle> unvalidatedConvert(const nn::SharedHandle& sharedHandle) {
+    CHECK(sharedHandle != nullptr);
+    return unvalidatedConvert(*sharedHandle);
+}
+
+nn::GeneralResult<Memory> unvalidatedConvert(const nn::SharedMemory& memory) {
+    CHECK(memory != nullptr);
+    if (memory->size > std::numeric_limits<int64_t>::max()) {
+        return NN_ERROR() << "Memory size doesn't fit into int64_t.";
+    }
+    if (const auto* handle = std::get_if<nn::Handle>(&memory->handle)) {
+        return Memory{
+                .handle = NN_TRY(unvalidatedConvert(*handle)),
+                .size = static_cast<int64_t>(memory->size),
+                .name = memory->name,
+        };
+    }
+
+    const auto* ahwb = std::get<nn::HardwareBufferHandle>(memory->handle).get();
+    AHardwareBuffer_Desc bufferDesc;
+    AHardwareBuffer_describe(ahwb, &bufferDesc);
+
+    if (bufferDesc.format == AHARDWAREBUFFER_FORMAT_BLOB) {
+        CHECK_EQ(memory->size, bufferDesc.width);
+        CHECK_EQ(memory->name, "hardware_buffer_blob");
+    } else {
+        CHECK_EQ(memory->size, 0u);
+        CHECK_EQ(memory->name, "hardware_buffer");
+    }
+
+    const native_handle_t* nativeHandle = AHardwareBuffer_getNativeHandle(ahwb);
+    if (nativeHandle == nullptr) {
+        return NN_ERROR() << "unvalidatedConvert failed because AHardwareBuffer_getNativeHandle "
+                             "returned nullptr";
+    }
+
+    return Memory{
+            .handle = NN_TRY(aidlHandleFromNativeHandle(*nativeHandle)),
+            .size = static_cast<int64_t>(memory->size),
+            .name = memory->name,
+    };
+}
+
+nn::GeneralResult<ErrorStatus> unvalidatedConvert(const nn::ErrorStatus& errorStatus) {
+    switch (errorStatus) {
+        case nn::ErrorStatus::NONE:
+        case nn::ErrorStatus::DEVICE_UNAVAILABLE:
+        case nn::ErrorStatus::GENERAL_FAILURE:
+        case nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE:
+        case nn::ErrorStatus::INVALID_ARGUMENT:
+        case nn::ErrorStatus::MISSED_DEADLINE_TRANSIENT:
+        case nn::ErrorStatus::MISSED_DEADLINE_PERSISTENT:
+        case nn::ErrorStatus::RESOURCE_EXHAUSTED_TRANSIENT:
+        case nn::ErrorStatus::RESOURCE_EXHAUSTED_PERSISTENT:
+            return static_cast<ErrorStatus>(errorStatus);
+        default:
+            return ErrorStatus::GENERAL_FAILURE;
+    }
+}
+
+nn::GeneralResult<OutputShape> unvalidatedConvert(const nn::OutputShape& outputShape) {
+    return OutputShape{.dimensions = NN_TRY(toSigned(outputShape.dimensions)),
+                       .isSufficient = outputShape.isSufficient};
+}
+
+nn::GeneralResult<Memory> convert(const nn::SharedMemory& memory) {
+    return validatedConvert(memory);
+}
+
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus) {
+    return validatedConvert(errorStatus);
+}
+
+nn::GeneralResult<std::vector<OutputShape>> convert(
+        const std::vector<nn::OutputShape>& outputShapes) {
+    return validatedConvert(outputShapes);
+}
+
+nn::GeneralResult<std::vector<int32_t>> toSigned(const std::vector<uint32_t>& vec) {
+    if (!std::all_of(vec.begin(), vec.end(),
+                     [](uint32_t v) { return v <= std::numeric_limits<int32_t>::max(); })) {
+        return NN_ERROR() << "Vector contains a value that doesn't fit into int32_t.";
+    }
+    return std::vector<int32_t>(vec.begin(), vec.end());
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::utils