neuralnetworks/1.2/utils/src/Conversions.cpp - platform/hardware/interfaces - Git at Google

 /*
  * 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/1.2/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/1.0/Conversions.h>
 #include <nnapi/hal/1.1/Conversions.h>
 #include <nnapi/hal/CommonUtils.h>
 #include <nnapi/hal/HandleError.h>

 #include <algorithm>
 #include <functional>
 #include <iterator>
 #include <memory>
 #include <type_traits>
 #include <utility>

 #include "Utils.h"

 namespace {

 template <typename Type>
 constexpr std::underlying_type_t<Type> underlyingType(Type value) {
     return static_cast<std::underlying_type_t<Type>>(value);
 }

 using HalDuration = std::chrono::duration<uint64_t, std::micro>;

 }  // namespace

 namespace android::nn {
 namespace {

 using hardware::hidl_handle;
 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_2::utils::compliantVersion(canonical));
     return canonical;
 }

 template <typename Type>
 GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> validatedConvert(
         const hidl_vec<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;
 }

 }  // anonymous namespace

 GeneralResult<OperandType> unvalidatedConvert(const hal::V1_2::OperandType& operandType) {
     return static_cast<OperandType>(operandType);
 }

 GeneralResult<OperationType> unvalidatedConvert(const hal::V1_2::OperationType& operationType) {
     return static_cast<OperationType>(operationType);
 }

 GeneralResult<DeviceType> unvalidatedConvert(const hal::V1_2::DeviceType& deviceType) {
     return static_cast<DeviceType>(deviceType);
 }

 GeneralResult<Capabilities> unvalidatedConvert(const hal::V1_2::Capabilities& capabilities) {
     const bool validOperandTypes = std::all_of(
             capabilities.operandPerformance.begin(), capabilities.operandPerformance.end(),
             [](const hal::V1_2::Capabilities::OperandPerformance& operandPerformance) {
                 return validatedConvert(operandPerformance.type).has_value();
             });
     if (!validOperandTypes) {
         return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
                << "Invalid OperandType when converting OperandPerformance in Capabilities";
     }

     const auto relaxedFloat32toFloat16PerformanceScalar =
             NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar));
     const auto relaxedFloat32toFloat16PerformanceTensor =
             NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor));
     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 = relaxedFloat32toFloat16PerformanceScalar,
             .relaxedFloat32toFloat16PerformanceTensor = relaxedFloat32toFloat16PerformanceTensor,
             .operandPerformance = std::move(table),
     };
 }

 GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
         const hal::V1_2::Capabilities::OperandPerformance& operandPerformance) {
     return Capabilities::OperandPerformance{
             .type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
             .info = NN_TRY(unvalidatedConvert(operandPerformance.info)),
     };
 }

 GeneralResult<Operation> unvalidatedConvert(const hal::V1_2::Operation& operation) {
     return Operation{
             .type = NN_TRY(unvalidatedConvert(operation.type)),
             .inputs = operation.inputs,
             .outputs = operation.outputs,
     };
 }

 GeneralResult<Operand::SymmPerChannelQuantParams> unvalidatedConvert(
         const hal::V1_2::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
     return Operand::SymmPerChannelQuantParams{
             .scales = symmPerChannelQuantParams.scales,
             .channelDim = symmPerChannelQuantParams.channelDim,
     };
 }

 GeneralResult<Operand> unvalidatedConvert(const hal::V1_2::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)),
             .extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),
     };
 }

 GeneralResult<Operand::ExtraParams> unvalidatedConvert(
         const hal::V1_2::Operand::ExtraParams& extraParams) {
     using Discriminator = hal::V1_2::Operand::ExtraParams::hidl_discriminator;
     switch (extraParams.getDiscriminator()) {
         case Discriminator::none:
             return Operand::NoParams{};
         case Discriminator::channelQuant:
             return unvalidatedConvert(extraParams.channelQuant());
         case Discriminator::extension:
             return extraParams.extension();
     }
     return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
            << "Unrecognized Operand::ExtraParams discriminator: "
            << underlyingType(extraParams.getDiscriminator());
 }

 GeneralResult<Model> unvalidatedConvert(const hal::V1_2::Model& model) {
     auto operations = NN_TRY(unvalidatedConvert(model.operations));

     // Verify number of consumers.
     const auto numberOfConsumers =
             NN_TRY(hal::utils::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(nn::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)),
             .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
             .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
     };
 }

 GeneralResult<Model::ExtensionNameAndPrefix> unvalidatedConvert(
         const hal::V1_2::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
     return Model::ExtensionNameAndPrefix{
             .name = extensionNameAndPrefix.name,
             .prefix = extensionNameAndPrefix.prefix,
     };
 }

 GeneralResult<OutputShape> unvalidatedConvert(const hal::V1_2::OutputShape& outputShape) {
     return OutputShape{
             .dimensions = outputShape.dimensions,
             .isSufficient = outputShape.isSufficient,
     };
 }

 GeneralResult<MeasureTiming> unvalidatedConvert(const hal::V1_2::MeasureTiming& measureTiming) {
     return static_cast<MeasureTiming>(measureTiming);
 }

 GeneralResult<Timing> unvalidatedConvert(const hal::V1_2::Timing& timing) {
     constexpr uint64_t kMaxTiming = std::chrono::floor<HalDuration>(Duration::max()).count();
     constexpr auto convertTiming = [](uint64_t halTiming) -> OptionalDuration {
         constexpr uint64_t kNoTiming = std::numeric_limits<uint64_t>::max();
         if (halTiming == kNoTiming) {
             return {};
         }
         if (halTiming > kMaxTiming) {
             return Duration::max();
         }
         return HalDuration{halTiming};
     };
     return Timing{.timeOnDevice = convertTiming(timing.timeOnDevice),
                   .timeInDriver = convertTiming(timing.timeInDriver)};
 }

 GeneralResult<Extension> unvalidatedConvert(const hal::V1_2::Extension& extension) {
     return Extension{
             .name = extension.name,
             .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
     };
 }

 GeneralResult<Extension::OperandTypeInformation> unvalidatedConvert(
         const hal::V1_2::Extension::OperandTypeInformation& operandTypeInformation) {
     return Extension::OperandTypeInformation{
             .type = operandTypeInformation.type,
             .isTensor = operandTypeInformation.isTensor,
             .byteSize = operandTypeInformation.byteSize,
     };
 }

 GeneralResult<SharedHandle> unvalidatedConvert(const hidl_handle& hidlHandle) {
     if (hidlHandle.getNativeHandle() == nullptr) {
         return nullptr;
     }
     auto handle = NN_TRY(hal::utils::sharedHandleFromNativeHandle(hidlHandle.getNativeHandle()));
     return std::make_shared<const Handle>(std::move(handle));
 }

 GeneralResult<DeviceType> convert(const hal::V1_2::DeviceType& deviceType) {
     return validatedConvert(deviceType);
 }

 GeneralResult<Capabilities> convert(const hal::V1_2::Capabilities& capabilities) {
     return validatedConvert(capabilities);
 }

 GeneralResult<Model> convert(const hal::V1_2::Model& model) {
     return validatedConvert(model);
 }

 GeneralResult<MeasureTiming> convert(const hal::V1_2::MeasureTiming& measureTiming) {
     return validatedConvert(measureTiming);
 }

 GeneralResult<Timing> convert(const hal::V1_2::Timing& timing) {
     return validatedConvert(timing);
 }

 GeneralResult<SharedMemory> convert(const hardware::hidl_memory& memory) {
     return validatedConvert(memory);
 }

 GeneralResult<std::vector<Extension>> convert(const hidl_vec<hal::V1_2::Extension>& extensions) {
     return validatedConvert(extensions);
 }

 GeneralResult<std::vector<SharedHandle>> convert(const hidl_vec<hidl_handle>& handles) {
     return validatedConvert(handles);
 }

 GeneralResult<std::vector<OutputShape>> convert(
         const hidl_vec<hal::V1_2::OutputShape>& outputShapes) {
     return validatedConvert(outputShapes);
 }

 }  // namespace android::nn

 namespace android::hardware::neuralnetworks::V1_2::utils {
 namespace {

 using utils::unvalidatedConvert;

 nn::GeneralResult<V1_0::OperandLifeTime> unvalidatedConvert(const nn::Operand::LifeTime& lifetime) {
     return V1_0::utils::unvalidatedConvert(lifetime);
 }

 nn::GeneralResult<V1_0::PerformanceInfo> unvalidatedConvert(
         const nn::Capabilities::PerformanceInfo& performanceInfo) {
     return V1_0::utils::unvalidatedConvert(performanceInfo);
 }

 nn::GeneralResult<V1_0::DataLocation> unvalidatedConvert(const nn::DataLocation& location) {
     return V1_0::utils::unvalidatedConvert(location);
 }

 nn::GeneralResult<hidl_vec<uint8_t>> unvalidatedConvert(
         const nn::Model::OperandValues& operandValues) {
     return V1_0::utils::unvalidatedConvert(operandValues);
 }

 nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory) {
     return V1_0::utils::unvalidatedConvert(memory);
 }

 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(unvalidatedConvert(arguments[i]));
     }
     return halObject;
 }

 nn::GeneralResult<Operand::ExtraParams> makeExtraParams(nn::Operand::NoParams /*noParams*/) {
     return Operand::ExtraParams{};
 }

 nn::GeneralResult<Operand::ExtraParams> makeExtraParams(
         const nn::Operand::SymmPerChannelQuantParams& channelQuant) {
     Operand::ExtraParams ret;
     ret.channelQuant(NN_TRY(unvalidatedConvert(channelQuant)));
     return ret;
 }

 nn::GeneralResult<Operand::ExtraParams> makeExtraParams(
         const nn::Operand::ExtensionParams& extension) {
     Operand::ExtraParams ret;
     ret.extension(extension);
     return ret;
 }

 template <typename Type>
 nn::GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& canonical) {
     NN_TRY(compliantVersion(canonical));
     return unvalidatedConvert(canonical);
 }

 template <typename Type>
 nn::GeneralResult<hidl_vec<UnvalidatedConvertOutput<Type>>> validatedConvert(
         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(validatedConvert(arguments[i]));
     }
     return halObject;
 }

 }  // 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<DeviceType> unvalidatedConvert(const nn::DeviceType& deviceType) {
     switch (deviceType) {
         case nn::DeviceType::UNKNOWN:
             return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Invalid DeviceType UNKNOWN";
         case nn::DeviceType::OTHER:
         case nn::DeviceType::CPU:
         case nn::DeviceType::GPU:
         case nn::DeviceType::ACCELERATOR:
             return static_cast<DeviceType>(deviceType);
     }
     return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
            << "Invalid DeviceType " << underlyingType(deviceType);
 }

 nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {
     std::vector<nn::Capabilities::OperandPerformance> operandPerformance;
     operandPerformance.reserve(capabilities.operandPerformance.asVector().size());
     std::copy_if(capabilities.operandPerformance.asVector().begin(),
                  capabilities.operandPerformance.asVector().end(),
                  std::back_inserter(operandPerformance),
                  [](const nn::Capabilities::OperandPerformance& operandPerformance) {
                      return compliantVersion(operandPerformance.type).has_value();
                  });

     return Capabilities{
             .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
                     unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
             .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
                     unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
             .operandPerformance = NN_TRY(unvalidatedConvert(operandPerformance)),
     };
 }

 nn::GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
         const nn::Capabilities::OperandPerformance& operandPerformance) {
     return Capabilities::OperandPerformance{
             .type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
             .info = NN_TRY(unvalidatedConvert(operandPerformance.info)),
     };
 }

 nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation) {
     return Operation{
             .type = NN_TRY(unvalidatedConvert(operation.type)),
             .inputs = operation.inputs,
             .outputs = operation.outputs,
     };
 }

 nn::GeneralResult<SymmPerChannelQuantParams> unvalidatedConvert(
         const nn::Operand::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
     return SymmPerChannelQuantParams{
             .scales = symmPerChannelQuantParams.scales,
             .channelDim = symmPerChannelQuantParams.channelDim,
     };
 }

 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)),
             .extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),
     };
 }

 nn::GeneralResult<Operand::ExtraParams> unvalidatedConvert(
         const nn::Operand::ExtraParams& extraParams) {
     return std::visit([](const auto& x) { return makeExtraParams(x); }, extraParams);
 }

 nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) {
     if (!hal::utils::hasNoPointerData(model)) {
         return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
                << "Model 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(hal::utils::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)),
             .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
             .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
     };
 }

 nn::GeneralResult<Model::ExtensionNameAndPrefix> unvalidatedConvert(
         const nn::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
     return Model::ExtensionNameAndPrefix{
             .name = extensionNameAndPrefix.name,
             .prefix = extensionNameAndPrefix.prefix,
     };
 }

 nn::GeneralResult<OutputShape> unvalidatedConvert(const nn::OutputShape& outputShape) {
     return OutputShape{.dimensions = outputShape.dimensions,
                        .isSufficient = outputShape.isSufficient};
 }

 nn::GeneralResult<MeasureTiming> unvalidatedConvert(const nn::MeasureTiming& measureTiming) {
     return static_cast<MeasureTiming>(measureTiming);
 }

 nn::GeneralResult<Timing> unvalidatedConvert(const nn::Timing& timing) {
     constexpr auto convertTiming = [](nn::OptionalDuration canonicalTiming) -> uint64_t {
         constexpr uint64_t kNoTiming = std::numeric_limits<uint64_t>::max();
         if (!canonicalTiming.has_value()) {
             return kNoTiming;
         }
         return std::chrono::ceil<HalDuration>(*canonicalTiming).count();
     };
     return Timing{.timeOnDevice = convertTiming(timing.timeOnDevice),
                   .timeInDriver = convertTiming(timing.timeInDriver)};
 }

 nn::GeneralResult<Extension> unvalidatedConvert(const nn::Extension& extension) {
     return Extension{
             .name = extension.name,
             .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
     };
 }

 nn::GeneralResult<Extension::OperandTypeInformation> unvalidatedConvert(
         const nn::Extension::OperandTypeInformation& operandTypeInformation) {
     return Extension::OperandTypeInformation{
             .type = operandTypeInformation.type,
             .isTensor = operandTypeInformation.isTensor,
             .byteSize = operandTypeInformation.byteSize,
     };
 }

 nn::GeneralResult<hidl_handle> unvalidatedConvert(const nn::SharedHandle& handle) {
     if (handle == nullptr) {
         return {};
     }
     return hal::utils::hidlHandleFromSharedHandle(*handle);
 }

 nn::GeneralResult<DeviceType> convert(const nn::DeviceType& deviceType) {
     return validatedConvert(deviceType);
 }

 nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
     return validatedConvert(capabilities);
 }

 nn::GeneralResult<Model> convert(const nn::Model& model) {
     return validatedConvert(model);
 }

 nn::GeneralResult<MeasureTiming> convert(const nn::MeasureTiming& measureTiming) {
     return validatedConvert(measureTiming);
 }

 nn::GeneralResult<Timing> convert(const nn::Timing& timing) {
     return validatedConvert(timing);
 }

 nn::GeneralResult<hidl_vec<Extension>> convert(const std::vector<nn::Extension>& extensions) {
     return validatedConvert(extensions);
 }

 nn::GeneralResult<hidl_vec<hidl_handle>> convert(const std::vector<nn::SharedHandle>& handles) {
     return validatedConvert(handles);
 }

 nn::GeneralResult<hidl_vec<OutputShape>> convert(const std::vector<nn::OutputShape>& outputShapes) {
     return validatedConvert(outputShapes);
 }

 nn::GeneralResult<V1_0::DeviceStatus> convert(const nn::DeviceStatus& deviceStatus) {
     return V1_1::utils::convert(deviceStatus);
 }

 nn::GeneralResult<V1_0::Request> convert(const nn::Request& request) {
     return V1_1::utils::convert(request);
 }

 nn::GeneralResult<V1_0::ErrorStatus> convert(const nn::ErrorStatus& status) {
     return V1_1::utils::convert(status);
 }

 nn::GeneralResult<V1_1::ExecutionPreference> convert(
         const nn::ExecutionPreference& executionPreference) {
     return V1_1::utils::convert(executionPreference);
 }

 }  // namespace android::hardware::neuralnetworks::V1_2::utils
	/*
	* 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/1.2/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/1.0/Conversions.h>
	#include <nnapi/hal/1.1/Conversions.h>
	#include <nnapi/hal/CommonUtils.h>
	#include <nnapi/hal/HandleError.h>

	#include <algorithm>
	#include <functional>
	#include <iterator>
	#include <memory>
	#include <type_traits>
	#include <utility>

	#include "Utils.h"

	namespace {

	template <typename Type>
	constexpr std::underlying_type_t<Type> underlyingType(Type value) {
	return static_cast<std::underlying_type_t<Type>>(value);
	}

	using HalDuration = std::chrono::duration<uint64_t, std::micro>;

	} // namespace

	namespace android::nn {
	namespace {

	using hardware::hidl_handle;
	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_2::utils::compliantVersion(canonical));
	return canonical;
	}

	template <typename Type>
	GeneralResult<std::vector<UnvalidatedConvertOutput<Type>>> validatedConvert(
	const hidl_vec<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;
	}

	} // anonymous namespace

	GeneralResult<OperandType> unvalidatedConvert(const hal::V1_2::OperandType& operandType) {
	return static_cast<OperandType>(operandType);
	}

	GeneralResult<OperationType> unvalidatedConvert(const hal::V1_2::OperationType& operationType) {
	return static_cast<OperationType>(operationType);
	}

	GeneralResult<DeviceType> unvalidatedConvert(const hal::V1_2::DeviceType& deviceType) {
	return static_cast<DeviceType>(deviceType);
	}

	GeneralResult<Capabilities> unvalidatedConvert(const hal::V1_2::Capabilities& capabilities) {
	const bool validOperandTypes = std::all_of(
	capabilities.operandPerformance.begin(), capabilities.operandPerformance.end(),
	[](const hal::V1_2::Capabilities::OperandPerformance& operandPerformance) {
	return validatedConvert(operandPerformance.type).has_value();
	});
	if (!validOperandTypes) {
	return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
	<< "Invalid OperandType when converting OperandPerformance in Capabilities";
	}

	const auto relaxedFloat32toFloat16PerformanceScalar =
	NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar));
	const auto relaxedFloat32toFloat16PerformanceTensor =
	NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor));
	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 = relaxedFloat32toFloat16PerformanceScalar,
	.relaxedFloat32toFloat16PerformanceTensor = relaxedFloat32toFloat16PerformanceTensor,
	.operandPerformance = std::move(table),
	};
	}

	GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
	const hal::V1_2::Capabilities::OperandPerformance& operandPerformance) {
	return Capabilities::OperandPerformance{
	.type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
	.info = NN_TRY(unvalidatedConvert(operandPerformance.info)),
	};
	}

	GeneralResult<Operation> unvalidatedConvert(const hal::V1_2::Operation& operation) {
	return Operation{
	.type = NN_TRY(unvalidatedConvert(operation.type)),
	.inputs = operation.inputs,
	.outputs = operation.outputs,
	};
	}

	GeneralResult<Operand::SymmPerChannelQuantParams> unvalidatedConvert(
	const hal::V1_2::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
	return Operand::SymmPerChannelQuantParams{
	.scales = symmPerChannelQuantParams.scales,
	.channelDim = symmPerChannelQuantParams.channelDim,
	};
	}

	GeneralResult<Operand> unvalidatedConvert(const hal::V1_2::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)),
	.extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),
	};
	}

	GeneralResult<Operand::ExtraParams> unvalidatedConvert(
	const hal::V1_2::Operand::ExtraParams& extraParams) {
	using Discriminator = hal::V1_2::Operand::ExtraParams::hidl_discriminator;
	switch (extraParams.getDiscriminator()) {
	case Discriminator::none:
	return Operand::NoParams{};
	case Discriminator::channelQuant:
	return unvalidatedConvert(extraParams.channelQuant());
	case Discriminator::extension:
	return extraParams.extension();
	}
	return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
	<< "Unrecognized Operand::ExtraParams discriminator: "
	<< underlyingType(extraParams.getDiscriminator());
	}

	GeneralResult<Model> unvalidatedConvert(const hal::V1_2::Model& model) {
	auto operations = NN_TRY(unvalidatedConvert(model.operations));

	// Verify number of consumers.
	const auto numberOfConsumers =
	NN_TRY(hal::utils::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(nn::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)),
	.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
	.extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
	};
	}

	GeneralResult<Model::ExtensionNameAndPrefix> unvalidatedConvert(
	const hal::V1_2::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
	return Model::ExtensionNameAndPrefix{
	.name = extensionNameAndPrefix.name,
	.prefix = extensionNameAndPrefix.prefix,
	};
	}

	GeneralResult<OutputShape> unvalidatedConvert(const hal::V1_2::OutputShape& outputShape) {
	return OutputShape{
	.dimensions = outputShape.dimensions,
	.isSufficient = outputShape.isSufficient,
	};
	}

	GeneralResult<MeasureTiming> unvalidatedConvert(const hal::V1_2::MeasureTiming& measureTiming) {
	return static_cast<MeasureTiming>(measureTiming);
	}

	GeneralResult<Timing> unvalidatedConvert(const hal::V1_2::Timing& timing) {
	constexpr uint64_t kMaxTiming = std::chrono::floor<HalDuration>(Duration::max()).count();
	constexpr auto convertTiming = [](uint64_t halTiming) -> OptionalDuration {
	constexpr uint64_t kNoTiming = std::numeric_limits<uint64_t>::max();
	if (halTiming == kNoTiming) {
	return {};
	}
	if (halTiming > kMaxTiming) {
	return Duration::max();
	}
	return HalDuration{halTiming};
	};
	return Timing{.timeOnDevice = convertTiming(timing.timeOnDevice),
	.timeInDriver = convertTiming(timing.timeInDriver)};
	}

	GeneralResult<Extension> unvalidatedConvert(const hal::V1_2::Extension& extension) {
	return Extension{
	.name = extension.name,
	.operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
	};
	}

	GeneralResult<Extension::OperandTypeInformation> unvalidatedConvert(
	const hal::V1_2::Extension::OperandTypeInformation& operandTypeInformation) {
	return Extension::OperandTypeInformation{
	.type = operandTypeInformation.type,
	.isTensor = operandTypeInformation.isTensor,
	.byteSize = operandTypeInformation.byteSize,
	};
	}

	GeneralResult<SharedHandle> unvalidatedConvert(const hidl_handle& hidlHandle) {
	if (hidlHandle.getNativeHandle() == nullptr) {
	return nullptr;
	}
	auto handle = NN_TRY(hal::utils::sharedHandleFromNativeHandle(hidlHandle.getNativeHandle()));
	return std::make_shared<const Handle>(std::move(handle));
	}

	GeneralResult<DeviceType> convert(const hal::V1_2::DeviceType& deviceType) {
	return validatedConvert(deviceType);
	}

	GeneralResult<Capabilities> convert(const hal::V1_2::Capabilities& capabilities) {
	return validatedConvert(capabilities);
	}

	GeneralResult<Model> convert(const hal::V1_2::Model& model) {
	return validatedConvert(model);
	}

	GeneralResult<MeasureTiming> convert(const hal::V1_2::MeasureTiming& measureTiming) {
	return validatedConvert(measureTiming);
	}

	GeneralResult<Timing> convert(const hal::V1_2::Timing& timing) {
	return validatedConvert(timing);
	}

	GeneralResult<SharedMemory> convert(const hardware::hidl_memory& memory) {
	return validatedConvert(memory);
	}

	GeneralResult<std::vector<Extension>> convert(const hidl_vec<hal::V1_2::Extension>& extensions) {
	return validatedConvert(extensions);
	}

	GeneralResult<std::vector<SharedHandle>> convert(const hidl_vec<hidl_handle>& handles) {
	return validatedConvert(handles);
	}

	GeneralResult<std::vector<OutputShape>> convert(
	const hidl_vec<hal::V1_2::OutputShape>& outputShapes) {
	return validatedConvert(outputShapes);
	}

	} // namespace android::nn

	namespace android::hardware::neuralnetworks::V1_2::utils {
	namespace {

	using utils::unvalidatedConvert;

	nn::GeneralResult<V1_0::OperandLifeTime> unvalidatedConvert(const nn::Operand::LifeTime& lifetime) {
	return V1_0::utils::unvalidatedConvert(lifetime);
	}

	nn::GeneralResult<V1_0::PerformanceInfo> unvalidatedConvert(
	const nn::Capabilities::PerformanceInfo& performanceInfo) {
	return V1_0::utils::unvalidatedConvert(performanceInfo);
	}

	nn::GeneralResult<V1_0::DataLocation> unvalidatedConvert(const nn::DataLocation& location) {
	return V1_0::utils::unvalidatedConvert(location);
	}

	nn::GeneralResult<hidl_vec<uint8_t>> unvalidatedConvert(
	const nn::Model::OperandValues& operandValues) {
	return V1_0::utils::unvalidatedConvert(operandValues);
	}

	nn::GeneralResult<hidl_memory> unvalidatedConvert(const nn::SharedMemory& memory) {
	return V1_0::utils::unvalidatedConvert(memory);
	}

	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(unvalidatedConvert(arguments[i]));
	}
	return halObject;
	}

	nn::GeneralResult<Operand::ExtraParams> makeExtraParams(nn::Operand::NoParams /noParams/) {
	return Operand::ExtraParams{};
	}

	nn::GeneralResult<Operand::ExtraParams> makeExtraParams(
	const nn::Operand::SymmPerChannelQuantParams& channelQuant) {
	Operand::ExtraParams ret;
	ret.channelQuant(NN_TRY(unvalidatedConvert(channelQuant)));
	return ret;
	}

	nn::GeneralResult<Operand::ExtraParams> makeExtraParams(
	const nn::Operand::ExtensionParams& extension) {
	Operand::ExtraParams ret;
	ret.extension(extension);
	return ret;
	}

	template <typename Type>
	nn::GeneralResult<UnvalidatedConvertOutput<Type>> validatedConvert(const Type& canonical) {
	NN_TRY(compliantVersion(canonical));
	return unvalidatedConvert(canonical);
	}

	template <typename Type>
	nn::GeneralResult<hidl_vec<UnvalidatedConvertOutput<Type>>> validatedConvert(
	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(validatedConvert(arguments[i]));
	}
	return halObject;
	}

	} // 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<DeviceType> unvalidatedConvert(const nn::DeviceType& deviceType) {
	switch (deviceType) {
	case nn::DeviceType::UNKNOWN:
	return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Invalid DeviceType UNKNOWN";
	case nn::DeviceType::OTHER:
	case nn::DeviceType::CPU:
	case nn::DeviceType::GPU:
	case nn::DeviceType::ACCELERATOR:
	return static_cast<DeviceType>(deviceType);
	}
	return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
	<< "Invalid DeviceType " << underlyingType(deviceType);
	}

	nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {
	std::vector<nn::Capabilities::OperandPerformance> operandPerformance;
	operandPerformance.reserve(capabilities.operandPerformance.asVector().size());
	std::copy_if(capabilities.operandPerformance.asVector().begin(),
	capabilities.operandPerformance.asVector().end(),
	std::back_inserter(operandPerformance),
	[](const nn::Capabilities::OperandPerformance& operandPerformance) {
	return compliantVersion(operandPerformance.type).has_value();
	});

	return Capabilities{
	.relaxedFloat32toFloat16PerformanceScalar = NN_TRY(
	unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),
	.relaxedFloat32toFloat16PerformanceTensor = NN_TRY(
	unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
	.operandPerformance = NN_TRY(unvalidatedConvert(operandPerformance)),
	};
	}

	nn::GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(
	const nn::Capabilities::OperandPerformance& operandPerformance) {
	return Capabilities::OperandPerformance{
	.type = NN_TRY(unvalidatedConvert(operandPerformance.type)),
	.info = NN_TRY(unvalidatedConvert(operandPerformance.info)),
	};
	}

	nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation) {
	return Operation{
	.type = NN_TRY(unvalidatedConvert(operation.type)),
	.inputs = operation.inputs,
	.outputs = operation.outputs,
	};
	}

	nn::GeneralResult<SymmPerChannelQuantParams> unvalidatedConvert(
	const nn::Operand::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
	return SymmPerChannelQuantParams{
	.scales = symmPerChannelQuantParams.scales,
	.channelDim = symmPerChannelQuantParams.channelDim,
	};
	}

	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)),
	.extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),
	};
	}

	nn::GeneralResult<Operand::ExtraParams> unvalidatedConvert(
	const nn::Operand::ExtraParams& extraParams) {
	return std::visit([](const auto& x) { return makeExtraParams(x); }, extraParams);
	}

	nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) {
	if (!hal::utils::hasNoPointerData(model)) {
	return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
	<< "Model 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(hal::utils::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)),
	.relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
	.extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),
	};
	}

	nn::GeneralResult<Model::ExtensionNameAndPrefix> unvalidatedConvert(
	const nn::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
	return Model::ExtensionNameAndPrefix{
	.name = extensionNameAndPrefix.name,
	.prefix = extensionNameAndPrefix.prefix,
	};
	}

	nn::GeneralResult<OutputShape> unvalidatedConvert(const nn::OutputShape& outputShape) {
	return OutputShape{.dimensions = outputShape.dimensions,
	.isSufficient = outputShape.isSufficient};
	}

	nn::GeneralResult<MeasureTiming> unvalidatedConvert(const nn::MeasureTiming& measureTiming) {
	return static_cast<MeasureTiming>(measureTiming);
	}

	nn::GeneralResult<Timing> unvalidatedConvert(const nn::Timing& timing) {
	constexpr auto convertTiming = [](nn::OptionalDuration canonicalTiming) -> uint64_t {
	constexpr uint64_t kNoTiming = std::numeric_limits<uint64_t>::max();
	if (!canonicalTiming.has_value()) {
	return kNoTiming;
	}
	return std::chrono::ceil<HalDuration>(*canonicalTiming).count();
	};
	return Timing{.timeOnDevice = convertTiming(timing.timeOnDevice),
	.timeInDriver = convertTiming(timing.timeInDriver)};
	}

	nn::GeneralResult<Extension> unvalidatedConvert(const nn::Extension& extension) {
	return Extension{
	.name = extension.name,
	.operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),
	};
	}

	nn::GeneralResult<Extension::OperandTypeInformation> unvalidatedConvert(
	const nn::Extension::OperandTypeInformation& operandTypeInformation) {
	return Extension::OperandTypeInformation{
	.type = operandTypeInformation.type,
	.isTensor = operandTypeInformation.isTensor,
	.byteSize = operandTypeInformation.byteSize,
	};
	}

	nn::GeneralResult<hidl_handle> unvalidatedConvert(const nn::SharedHandle& handle) {
	if (handle == nullptr) {
	return {};
	}
	return hal::utils::hidlHandleFromSharedHandle(*handle);
	}

	nn::GeneralResult<DeviceType> convert(const nn::DeviceType& deviceType) {
	return validatedConvert(deviceType);
	}

	nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
	return validatedConvert(capabilities);
	}

	nn::GeneralResult<Model> convert(const nn::Model& model) {
	return validatedConvert(model);
	}

	nn::GeneralResult<MeasureTiming> convert(const nn::MeasureTiming& measureTiming) {
	return validatedConvert(measureTiming);
	}

	nn::GeneralResult<Timing> convert(const nn::Timing& timing) {
	return validatedConvert(timing);
	}

	nn::GeneralResult<hidl_vec<Extension>> convert(const std::vector<nn::Extension>& extensions) {
	return validatedConvert(extensions);
	}

	nn::GeneralResult<hidl_vec<hidl_handle>> convert(const std::vector<nn::SharedHandle>& handles) {
	return validatedConvert(handles);
	}

	nn::GeneralResult<hidl_vec<OutputShape>> convert(const std::vector<nn::OutputShape>& outputShapes) {
	return validatedConvert(outputShapes);
	}

	nn::GeneralResult<V1_0::DeviceStatus> convert(const nn::DeviceStatus& deviceStatus) {
	return V1_1::utils::convert(deviceStatus);
	}

	nn::GeneralResult<V1_0::Request> convert(const nn::Request& request) {
	return V1_1::utils::convert(request);
	}

	nn::GeneralResult<V1_0::ErrorStatus> convert(const nn::ErrorStatus& status) {
	return V1_1::utils::convert(status);
	}

	nn::GeneralResult<V1_1::ExecutionPreference> convert(
	const nn::ExecutionPreference& executionPreference) {
	return V1_1::utils::convert(executionPreference);
	}

	} // namespace android::hardware::neuralnetworks::V1_2::utils