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/*
* Copyright (C) 2020 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 <android-base/logging.h>
#include <android/hardware/neuralnetworks/1.0/types.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 <algorithm>
#include <functional>
#include <iterator>
#include <memory>
#include <type_traits>
#include <utility>
#include <variant>
#include "Utils.h"
#ifdef __ANDROID__
#include <android/hardware_buffer.h>
#include <vndk/hardware_buffer.h>
#endif // __ANDROID__
namespace {
template <typename Type>
constexpr std::underlying_type_t<Type> underlyingType(Type value) {
return static_cast<std::underlying_type_t<Type>>(value);
}
} // namespace
namespace android::nn {
namespace {
using hardware::hidl_handle;
using hardware::hidl_memory;
using hardware::hidl_vec;
template <typename Input>
using UnvalidatedConvertOutput =
std::decay_t<decltype(unvalidatedConvert(std::declval<Input>()).value())>;
template <typename Type>
GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> unvalidatedConvert(
const hidl_vec<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<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& halObject) {
auto canonical = NN_TRY(nn::unvalidatedConvert(halObject));
NN_TRY(hal::V1_0::utils::compliantVersion(canonical));
return canonical;
}
nn::GeneralResult<nn::Memory::Unknown::Handle> unknownHandleFromNativeHandle(
const native_handle_t* handle) {
if (handle == nullptr) {
return NN_ERROR() << "unknownHandleFromNativeHandle failed because handle is nullptr";
}
std::vector<base::unique_fd> fds =
NN_TRY(nn::dupFds(handle->data + 0, handle->data + handle->numFds));
std::vector<int> ints(handle->data + handle->numFds,
handle->data + handle->numFds + handle->numInts);
return nn::Memory::Unknown::Handle{.fds = std::move(fds), .ints = std::move(ints)};
}
nn::GeneralResult<nn::SharedMemory> createSharedMemoryFromHidlMemory(const hidl_memory& memory) {
CHECK_LE(memory.size(), std::numeric_limits<size_t>::max());
if (!memory.valid()) {
return NN_ERROR() << "Unable to convert invalid hidl_memory";
}
if (memory.name() == "ashmem") {
if (memory.handle()->numFds != 1) {
return NN_ERROR() << "Unable to convert invalid ashmem memory object with "
<< memory.handle()->numFds << " numFds, but expected 1";
}
if (memory.handle()->numInts != 0) {
return NN_ERROR() << "Unable to convert invalid ashmem memory object with "
<< memory.handle()->numInts << " numInts, but expected 0";
}
auto handle = nn::Memory::Ashmem{
.fd = NN_TRY(nn::dupFd(memory.handle()->data[0])),
.size = static_cast<size_t>(memory.size()),
};
return std::make_shared<const nn::Memory>(nn::Memory{.handle = std::move(handle)});
}
if (memory.name() == "mmap_fd") {
if (memory.handle()->numFds != 1) {
return NN_ERROR() << "Unable to convert invalid mmap_fd memory object with "
<< memory.handle()->numFds << " numFds, but expected 1";
}
if (memory.handle()->numInts != 3) {
return NN_ERROR() << "Unable to convert invalid mmap_fd memory object with "
<< memory.handle()->numInts << " numInts, but expected 3";
}
const int fd = memory.handle()->data[0];
const int prot = memory.handle()->data[1];
const int lower = memory.handle()->data[2];
const int higher = memory.handle()->data[3];
const size_t offset = nn::getOffsetFromInts(lower, higher);
return nn::createSharedMemoryFromFd(static_cast<size_t>(memory.size()), prot, fd, offset);
}
if (memory.name() != "hardware_buffer_blob") {
auto handle = nn::Memory::Unknown{
.handle = NN_TRY(unknownHandleFromNativeHandle(memory.handle())),
.size = static_cast<size_t>(memory.size()),
.name = memory.name(),
};
return std::make_shared<const nn::Memory>(nn::Memory{.handle = std::move(handle)});
}
#ifdef __ANDROID__
constexpr auto roundUpToMultiple = [](uint32_t value, uint32_t multiple) -> uint32_t {
return (value + multiple - 1) / multiple * multiple;
};
const auto size = 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.
// 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, memory.handle(),
AHARDWAREBUFFER_CREATE_FROM_HANDLE_METHOD_CLONE,
&hardwareBuffer);
if (status == NO_ERROR) {
break;
}
}
if (status != NO_ERROR) {
return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Can't create AHardwareBuffer from handle. Error: " << status;
}
return nn::createSharedMemoryFromAHWB(hardwareBuffer, /*takeOwnership=*/true);
#else // __ANDROID__
LOG(FATAL) << "nn::GeneralResult<nn::SharedMemory> createSharedMemoryFromHidlMemory(const "
"hidl_memory& memory): Not Available on Host Build";
return (NN_ERROR() << "createSharedMemoryFromHidlMemory failed")
.
operator nn::GeneralResult<nn::SharedMemory>();
#endif // __ANDROID__
}
} // anonymous namespace
GeneralResult<OperandType> unvalidatedConvert(const hal::V1_0::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
GeneralResult<OperationType> unvalidatedConvert(const hal::V1_0::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
GeneralResult<Operand::LifeTime> unvalidatedConvert(const hal::V1_0::OperandLifeTime& lifetime) {
return static_cast<Operand::LifeTime>(lifetime);
}
GeneralResult<DeviceStatus> unvalidatedConvert(const hal::V1_0::DeviceStatus& deviceStatus) {
return static_cast<DeviceStatus>(deviceStatus);
}
GeneralResult<Capabilities::PerformanceInfo> unvalidatedConvert(
const hal::V1_0::PerformanceInfo& performanceInfo) {
return Capabilities::PerformanceInfo{
.execTime = performanceInfo.execTime,
.powerUsage = performanceInfo.powerUsage,
};
}
GeneralResult<Capabilities> unvalidatedConvert(const hal::V1_0::Capabilities& capabilities) {
const auto quantized8Performance =
NN_TRY(unvalidatedConvert(capabilities.quantized8Performance));
const auto float32Performance = NN_TRY(unvalidatedConvert(capabilities.float32Performance));
auto table = hal::utils::makeQuantized8PerformanceConsistentWithP(float32Performance,
quantized8Performance);
return Capabilities{
.relaxedFloat32toFloat16PerformanceScalar = float32Performance,
.relaxedFloat32toFloat16PerformanceTensor = float32Performance,
.operandPerformance = std::move(table),
};
}
GeneralResult<DataLocation> unvalidatedConvert(const hal::V1_0::DataLocation& location) {
return DataLocation{
.poolIndex = location.poolIndex,
.offset = location.offset,
.length = location.length,
};
}
GeneralResult<Operand> unvalidatedConvert(const hal::V1_0::Operand& operand) {
return Operand{
.type = NN_TRY(unvalidatedConvert(operand.type)),
.dimensions = operand.dimensions,
.scale = operand.scale,
.zeroPoint = operand.zeroPoint,
.lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),
.location = NN_TRY(unvalidatedConvert(operand.location)),
};
}
GeneralResult<Operation> unvalidatedConvert(const hal::V1_0::Operation& operation) {
return Operation{
.type = NN_TRY(unvalidatedConvert(operation.type)),
.inputs = operation.inputs,
.outputs = operation.outputs,
};
}
GeneralResult<Model::OperandValues> unvalidatedConvert(const hidl_vec<uint8_t>& operandValues) {
return Model::OperandValues(operandValues.data(), operandValues.size());
}
GeneralResult<SharedHandle> unvalidatedConvert(const hidl_handle& handle) {
if (handle.getNativeHandle() == nullptr) {
return nullptr;
}
if (handle->numFds != 1 || handle->numInts != 0) {
return NN_ERROR()
<< "unvalidatedConvert failed because handle does not only hold a single fd";
}
auto duplicatedFd = NN_TRY(nn::dupFd(handle->data[0]));
return std::make_shared<const Handle>(std::move(duplicatedFd));
}
GeneralResult<SharedMemory> unvalidatedConvert(const hidl_memory& memory) {
return createSharedMemoryFromHidlMemory(memory);
}
GeneralResult<Model> unvalidatedConvert(const hal::V1_0::Model& model) {
auto operations = NN_TRY(unvalidatedConvert(model.operations));
// Verify number of consumers.
const auto numberOfConsumers =
NN_TRY(countNumberOfConsumers(model.operands.size(), operations));
CHECK(model.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < model.operands.size(); ++i) {
if (model.operands[i].numberOfConsumers != numberOfConsumers[i]) {
return NN_ERROR(ErrorStatus::GENERAL_FAILURE)
<< "Invalid numberOfConsumers for operand " << i << ", expected "
<< numberOfConsumers[i] << " but found " << model.operands[i].numberOfConsumers;
}
}
auto main = Model::Subgraph{
.operands = NN_TRY(unvalidatedConvert(model.operands)),
.operations = std::move(operations),
.inputIndexes = model.inputIndexes,
.outputIndexes = model.outputIndexes,
};
return Model{
.main = std::move(main),
.operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
.pools = NN_TRY(unvalidatedConvert(model.pools)),
};
}
GeneralResult<Request::Argument> unvalidatedConvert(const hal::V1_0::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 = argument.dimensions,
};
}
GeneralResult<Request> unvalidatedConvert(const hal::V1_0::Request& request) {
auto memories = NN_TRY(unvalidatedConvert(request.pools));
std::vector<Request::MemoryPool> pools;
pools.reserve(memories.size());
std::move(memories.begin(), memories.end(), std::back_inserter(pools));
return Request{
.inputs = NN_TRY(unvalidatedConvert(request.inputs)),
.outputs = NN_TRY(unvalidatedConvert(request.outputs)),
.pools = std::move(pools),
};
}
GeneralResult<ErrorStatus> unvalidatedConvert(const hal::V1_0::ErrorStatus& status) {
switch (status) {
case hal::V1_0::ErrorStatus::NONE:
case hal::V1_0::ErrorStatus::DEVICE_UNAVAILABLE:
case hal::V1_0::ErrorStatus::GENERAL_FAILURE:
case hal::V1_0::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE:
case hal::V1_0::ErrorStatus::INVALID_ARGUMENT:
return static_cast<ErrorStatus>(status);
}
return NN_ERROR(ErrorStatus::GENERAL_FAILURE)
<< "Invalid ErrorStatus " << underlyingType(status);
}
GeneralResult<DeviceStatus> convert(const hal::V1_0::DeviceStatus& deviceStatus) {
return validatedConvert(deviceStatus);
}
GeneralResult<Capabilities> convert(const hal::V1_0::Capabilities& capabilities) {
return validatedConvert(capabilities);
}
GeneralResult<Model> convert(const hal::V1_0::Model& model) {
return validatedConvert(model);
}
GeneralResult<Request> convert(const hal::V1_0::Request& request) {
return validatedConvert(request);
}
GeneralResult<ErrorStatus> convert(const hal::V1_0::ErrorStatus& status) {
return validatedConvert(status);
}
} // namespace android::nn
namespace android::hardware::neuralnetworks::V1_0::utils {
namespace {
template <typename Input>
using UnvalidatedConvertOutput =
std::decay_t<decltype(unvalidatedConvert(std::declval<Input>()).value())>;
template <typename Type>
nn::GeneralResult<hidl_vec<UnvalidatedConvertOutput<Type>>> unvalidatedConvert(
const std::vector<Type>& arguments) {
hidl_vec<UnvalidatedConvertOutput<Type>> halObject(arguments.size());
for (size_t i = 0; i < arguments.size(); ++i) {
halObject[i] = NN_TRY(utils::unvalidatedConvert(arguments[i]));
}
return halObject;
}
template <typename Type>
nn::GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& canonical) {
NN_TRY(compliantVersion(canonical));
return utils::unvalidatedConvert(canonical);
}
nn::GeneralResult<hidl_handle> createNativeHandleFrom(std::vector<base::unique_fd> fds,
const std::vector<int32_t>& ints) {
constexpr size_t kIntMax = std::numeric_limits<int>::max();
CHECK_LE(fds.size(), kIntMax);
CHECK_LE(ints.size(), kIntMax);
native_handle_t* nativeHandle =
native_handle_create(static_cast<int>(fds.size()), static_cast<int>(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(ints.begin(), ints.end(), nativeHandle->data + nativeHandle->numFds);
hidl_handle handle;
handle.setTo(nativeHandle, /*shouldOwn=*/true);
return handle;
}
nn::GeneralResult<hidl_handle> createNativeHandleFrom(base::unique_fd fd,
const std::vector<int32_t>& ints) {
std::vector<base::unique_fd> fds;
fds.push_back(std::move(fd));
return createNativeHandleFrom(std::move(fds), ints);
}
nn::GeneralResult<hidl_handle> createNativeHandleFrom(const nn::Memory::Unknown::Handle& handle) {
std::vector<base::unique_fd> fds = NN_TRY(nn::dupFds(handle.fds.begin(), handle.fds.end()));
return createNativeHandleFrom(std::move(fds), handle.ints);
}
nn::GeneralResult<hidl_memory> createHidlMemoryFrom(const nn::Memory::Ashmem& memory) {
auto fd = NN_TRY(nn::dupFd(memory.fd));
auto handle = NN_TRY(createNativeHandleFrom(std::move(fd), {}));
return hidl_memory("ashmem", std::move(handle), memory.size);
}
nn::GeneralResult<hidl_memory> createHidlMemoryFrom(const nn::Memory::Fd& memory) {
auto fd = NN_TRY(nn::dupFd(memory.fd));
const auto [lowOffsetBits, highOffsetBits] = nn::getIntsFromOffset(memory.offset);
const std::vector<int> ints = {memory.prot, lowOffsetBits, highOffsetBits};
auto handle = NN_TRY(createNativeHandleFrom(std::move(fd), ints));
return hidl_memory("mmap_fd", std::move(handle), memory.size);
}
nn::GeneralResult<hidl_memory> createHidlMemoryFrom(const nn::Memory::HardwareBuffer& memory) {
#ifdef __ANDROID__
const auto* ahwb = memory.handle.get();
AHardwareBuffer_Desc bufferDesc;
AHardwareBuffer_describe(ahwb, &bufferDesc);
const bool isBlob = bufferDesc.format == AHARDWAREBUFFER_FORMAT_BLOB;
const size_t size = isBlob ? bufferDesc.width : 0;
const char* const name = isBlob ? "hardware_buffer_blob" : "hardware_buffer";
const native_handle_t* nativeHandle = AHardwareBuffer_getNativeHandle(ahwb);
const hidl_handle hidlHandle(nativeHandle);
hidl_handle copiedHandle(hidlHandle);
return hidl_memory(name, std::move(copiedHandle), size);
#else // __ANDROID__
LOG(FATAL) << "nn::GeneralResult<hidl_memory> createHidlMemoryFrom(const "
"nn::Memory::HardwareBuffer& memory): Not Available on Host Build";
(void)memory;
return (NN_ERROR() << "createHidlMemoryFrom failed").operator nn::GeneralResult<hidl_memory>();
#endif // __ANDROID__
}
nn::GeneralResult<hidl_memory> createHidlMemoryFrom(const nn::Memory::Unknown& memory) {
return hidl_memory(memory.name, NN_TRY(createNativeHandleFrom(memory.handle)), memory.size);
}
} // anonymous namespace
nn::GeneralResult<OperandType> unvalidatedConvert(const nn::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
nn::GeneralResult<OperationType> unvalidatedConvert(const nn::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
nn::GeneralResult<OperandLifeTime> unvalidatedConvert(const nn::Operand::LifeTime& lifetime) {
if (lifetime == nn::Operand::LifeTime::POINTER) {
return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
<< "Model cannot be unvalidatedConverted because it contains pointer-based memory";
}
return static_cast<OperandLifeTime>(lifetime);
}
nn::GeneralResult<DeviceStatus> unvalidatedConvert(const nn::DeviceStatus& deviceStatus) {
return static_cast<DeviceStatus>(deviceStatus);
}
nn::GeneralResult<PerformanceInfo> unvalidatedConvert(
const nn::Capabilities::PerformanceInfo& performanceInfo) {
return PerformanceInfo{
.execTime = performanceInfo.execTime,
.powerUsage = performanceInfo.powerUsage,
};
}
nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {
return Capabilities{
.float32Performance = NN_TRY(unvalidatedConvert(
capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32))),
.quantized8Performance = NN_TRY(unvalidatedConvert(
capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM))),
};
}
nn::GeneralResult<DataLocation> unvalidatedConvert(const nn::DataLocation& location) {
return DataLocation{
.poolIndex = location.poolIndex,
.offset = location.offset,
.length = location.length,
};
}
nn::GeneralResult<Operand> unvalidatedConvert(const nn::Operand& operand) {
return Operand{
.type = NN_TRY(unvalidatedConvert(operand.type)),
.dimensions = operand.dimensions,
.numberOfConsumers = 0,
.scale = operand.scale,
.zeroPoint = operand.zeroPoint,
.lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),
.location = NN_TRY(unvalidatedConvert(operand.location)),
};
}
nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation) {
return Operation{
.type = NN_TRY(unvalidatedConvert(operation.type)),
.inputs = operation.inputs,
.outputs = operation.outputs,
};
}
nn::GeneralResult<hidl_vec<uint8_t>> unvalidatedConvert(
const nn::Model::OperandValues& operandValues) {
return hidl_vec<uint8_t>(operandValues.data(), operandValues.data() + operandValues.size());
}
nn::GeneralResult<hidl_handle> unvalidatedConvert(const nn::SharedHandle& handle) {
if (handle == nullptr) {
return {};
}
base::unique_fd fd = NN_TRY(nn::dupFd(handle->get()));
return createNativeHandleFrom(std::move(fd), {});
}
nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory) {
if (memory == nullptr) {
return NN_ERROR() << "Memory must be non-empty";
}
return std::visit([](const auto& x) { return createHidlMemoryFrom(x); }, memory->handle);
}
nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) {
if (!hal::utils::hasNoPointerData(model)) {
return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
<< "Mdoel cannot be unvalidatedConverted because it contains pointer-based memory";
}
auto operands = NN_TRY(unvalidatedConvert(model.main.operands));
// Update number of consumers.
const auto numberOfConsumers =
NN_TRY(countNumberOfConsumers(operands.size(), model.main.operations));
CHECK(operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < operands.size(); ++i) {
operands[i].numberOfConsumers = numberOfConsumers[i];
}
return Model{
.operands = std::move(operands),
.operations = NN_TRY(unvalidatedConvert(model.main.operations)),
.inputIndexes = model.main.inputIndexes,
.outputIndexes = model.main.outputIndexes,
.operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),
.pools = NN_TRY(unvalidatedConvert(model.pools)),
};
}
nn::GeneralResult<RequestArgument> unvalidatedConvert(
const nn::Request::Argument& requestArgument) {
if (requestArgument.lifetime == nn::Request::Argument::LifeTime::POINTER) {
return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
<< "Request cannot be unvalidatedConverted because it contains pointer-based memory";
}
const bool hasNoValue = requestArgument.lifetime == nn::Request::Argument::LifeTime::NO_VALUE;
return RequestArgument{
.hasNoValue = hasNoValue,
.location = NN_TRY(unvalidatedConvert(requestArgument.location)),
.dimensions = requestArgument.dimensions,
};
}
nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::Request::MemoryPool& memoryPool) {
return unvalidatedConvert(std::get<nn::SharedMemory>(memoryPool));
}
nn::GeneralResult<Request> unvalidatedConvert(const nn::Request& request) {
if (!hal::utils::hasNoPointerData(request)) {
return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
<< "Request cannot be unvalidatedConverted because it contains pointer-based memory";
}
return Request{
.inputs = NN_TRY(unvalidatedConvert(request.inputs)),
.outputs = NN_TRY(unvalidatedConvert(request.outputs)),
.pools = NN_TRY(unvalidatedConvert(request.pools)),
};
}
nn::GeneralResult<ErrorStatus> unvalidatedConvert(const nn::ErrorStatus& status) {
switch (status) {
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:
return static_cast<ErrorStatus>(status);
default:
return ErrorStatus::GENERAL_FAILURE;
}
}
nn::GeneralResult<DeviceStatus> convert(const nn::DeviceStatus& deviceStatus) {
return validatedConvert(deviceStatus);
}
nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
return validatedConvert(capabilities);
}
nn::GeneralResult<Model> convert(const nn::Model& model) {
return validatedConvert(model);
}
nn::GeneralResult<Request> convert(const nn::Request& request) {
return validatedConvert(request);
}
nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& status) {
return validatedConvert(status);
}
} // namespace android::hardware::neuralnetworks::V1_0::utils
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