From 534556391ae153b1e8fdd11b233e2dc6ecd1e530 Mon Sep 17 00:00:00 2001 From: Michael Butler Date: Mon, 25 Oct 2021 11:20:33 -0700 Subject: [PATCH 1/2] Create NN AIDL adapter This change adds the following adapters: * nn::IDevice -> BnDevice * nn::IPreparedModel -> BnPreparedModel * nn::IBurst -> BnBurst * nn::IBuffer -> BnBuffer Bug: N/A Test: mma Test: locally created a binderized service with this adapter code, which passed VtsHalNeuralnetworksTargetTest Change-Id: I966f65a1e4d75284c050b77f3f40c515e4970130 --- .../include/nnapi/hal/aidl/Conversions.h | 12 +- neuralnetworks/aidl/utils/src/Conversions.cpp | 173 +++++++--- neuralnetworks/utils/adapter/aidl/Android.bp | 42 +++ .../aidl/include/nnapi/hal/aidl/Adapter.h | 73 +++++ .../aidl/include/nnapi/hal/aidl/Buffer.h | 47 +++ .../aidl/include/nnapi/hal/aidl/Burst.h | 72 +++++ .../aidl/include/nnapi/hal/aidl/Device.h | 83 +++++ .../include/nnapi/hal/aidl/PreparedModel.h | 62 ++++ .../utils/adapter/aidl/src/Adapter.cpp | 46 +++ .../utils/adapter/aidl/src/Buffer.cpp | 88 +++++ .../utils/adapter/aidl/src/Burst.cpp | 179 +++++++++++ .../utils/adapter/aidl/src/Device.cpp | 304 ++++++++++++++++++ .../utils/adapter/aidl/src/PreparedModel.cpp | 225 +++++++++++++ .../utils/adapter/{ => hidl}/Android.bp | 0 .../{ => hidl}/include/nnapi/hal/Adapter.h | 0 .../{ => hidl}/include/nnapi/hal/Buffer.h | 0 .../{ => hidl}/include/nnapi/hal/Burst.h | 0 .../{ => hidl}/include/nnapi/hal/Device.h | 0 .../include/nnapi/hal/PreparedModel.h | 0 .../utils/adapter/{ => hidl}/src/Adapter.cpp | 0 .../utils/adapter/{ => hidl}/src/Buffer.cpp | 0 .../utils/adapter/{ => hidl}/src/Burst.cpp | 0 .../utils/adapter/{ => hidl}/src/Device.cpp | 0 .../adapter/{ => hidl}/src/PreparedModel.cpp | 0 24 files changed, 1360 insertions(+), 46 deletions(-) create mode 100644 neuralnetworks/utils/adapter/aidl/Android.bp create mode 100644 neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h create mode 100644 neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Buffer.h create mode 100644 neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Burst.h create mode 100644 neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Device.h create mode 100644 neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/PreparedModel.h create mode 100644 neuralnetworks/utils/adapter/aidl/src/Adapter.cpp create mode 100644 neuralnetworks/utils/adapter/aidl/src/Buffer.cpp create mode 100644 neuralnetworks/utils/adapter/aidl/src/Burst.cpp create mode 100644 neuralnetworks/utils/adapter/aidl/src/Device.cpp create mode 100644 neuralnetworks/utils/adapter/aidl/src/PreparedModel.cpp rename neuralnetworks/utils/adapter/{ => hidl}/Android.bp (100%) rename neuralnetworks/utils/adapter/{ => hidl}/include/nnapi/hal/Adapter.h (100%) rename neuralnetworks/utils/adapter/{ => hidl}/include/nnapi/hal/Buffer.h (100%) rename neuralnetworks/utils/adapter/{ => hidl}/include/nnapi/hal/Burst.h (100%) rename neuralnetworks/utils/adapter/{ => hidl}/include/nnapi/hal/Device.h (100%) rename neuralnetworks/utils/adapter/{ => hidl}/include/nnapi/hal/PreparedModel.h (100%) rename neuralnetworks/utils/adapter/{ => hidl}/src/Adapter.cpp (100%) rename neuralnetworks/utils/adapter/{ => hidl}/src/Buffer.cpp (100%) rename neuralnetworks/utils/adapter/{ => hidl}/src/Burst.cpp (100%) rename neuralnetworks/utils/adapter/{ => hidl}/src/Device.cpp (100%) rename neuralnetworks/utils/adapter/{ => hidl}/src/PreparedModel.cpp (100%) diff --git a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h index 78433a74e9..477b311598 100644 --- a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h +++ b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Conversions.h @@ -112,11 +112,15 @@ GeneralResult convert(const aidl_hal::Priority& priority); GeneralResult convert(const aidl_hal::Request& request); GeneralResult convert(const aidl_hal::Timing& timing); GeneralResult convert(const ndk::ScopedFileDescriptor& handle); +GeneralResult convert(const aidl_hal::BufferDesc& bufferDesc); GeneralResult> convert(const std::vector& extension); GeneralResult> convert(const std::vector& memories); GeneralResult> convert( const std::vector& outputShapes); +GeneralResult> convert( + const std::vector& handles); +GeneralResult> convert(const std::vector& roles); GeneralResult> toUnsigned(const std::vector& vec); @@ -129,6 +133,7 @@ namespace nn = ::android::nn; nn::GeneralResult> unvalidatedConvert(const nn::CacheToken& cacheToken); nn::GeneralResult unvalidatedConvert(const nn::BufferDesc& bufferDesc); nn::GeneralResult unvalidatedConvert(const nn::BufferRole& bufferRole); +nn::GeneralResult unvalidatedConvert(const nn::DeviceType& deviceType); nn::GeneralResult unvalidatedConvert(const nn::MeasureTiming& measureTiming); nn::GeneralResult unvalidatedConvert(const nn::SharedMemory& memory); nn::GeneralResult unvalidatedConvert(const nn::OutputShape& outputShape); @@ -154,14 +159,16 @@ nn::GeneralResult unvalidatedConvert(const nn::Request& request); nn::GeneralResult unvalidatedConvert(const nn::Request::Argument& requestArgument); nn::GeneralResult unvalidatedConvert(const nn::Request::MemoryPool& memoryPool); nn::GeneralResult unvalidatedConvert(const nn::Timing& timing); -nn::GeneralResult unvalidatedConvert(const nn::Duration& duration); nn::GeneralResult unvalidatedConvert(const nn::OptionalDuration& optionalDuration); nn::GeneralResult unvalidatedConvert(const nn::OptionalTimePoint& optionalTimePoint); nn::GeneralResult unvalidatedConvert(const nn::SyncFence& syncFence); nn::GeneralResult unvalidatedConvert(const nn::SharedHandle& handle); +nn::GeneralResult unvalidatedConvert(const nn::Capabilities& capabilities); +nn::GeneralResult unvalidatedConvert(const nn::Extension& extension); nn::GeneralResult> convert(const nn::CacheToken& cacheToken); nn::GeneralResult convert(const nn::BufferDesc& bufferDesc); +nn::GeneralResult convert(const nn::DeviceType& deviceType); nn::GeneralResult convert(const nn::MeasureTiming& measureTiming); nn::GeneralResult convert(const nn::SharedMemory& memory); nn::GeneralResult convert(const nn::ErrorStatus& errorStatus); @@ -172,6 +179,8 @@ nn::GeneralResult convert(const nn::Request& request); nn::GeneralResult convert(const nn::Timing& timing); nn::GeneralResult convert(const nn::OptionalDuration& optionalDuration); nn::GeneralResult convert(const nn::OptionalTimePoint& optionalTimePoint); +nn::GeneralResult convert(const nn::Capabilities& capabilities); +nn::GeneralResult convert(const nn::Extension& extension); nn::GeneralResult> convert(const std::vector& bufferRoles); nn::GeneralResult> convert( @@ -180,6 +189,7 @@ nn::GeneralResult> convert( const std::vector& handles); nn::GeneralResult> convert( const std::vector& syncFences); +nn::GeneralResult> convert(const std::vector& extensions); nn::GeneralResult> toSigned(const std::vector& vec); diff --git a/neuralnetworks/aidl/utils/src/Conversions.cpp b/neuralnetworks/aidl/utils/src/Conversions.cpp index 45628c8e73..113d2da955 100644 --- a/neuralnetworks/aidl/utils/src/Conversions.cpp +++ b/neuralnetworks/aidl/utils/src/Conversions.cpp @@ -551,6 +551,10 @@ GeneralResult convert(const ndk::ScopedFileDescriptor& handle) { return validatedConvert(handle); } +GeneralResult convert(const aidl_hal::BufferDesc& bufferDesc) { + return validatedConvert(bufferDesc); +} + GeneralResult> convert(const std::vector& extension) { return validatedConvert(extension); } @@ -564,6 +568,15 @@ GeneralResult> convert( return validatedConvert(outputShapes); } +GeneralResult> convert( + const std::vector& handles) { + return validatedConvert(handles); +} + +GeneralResult> convert(const std::vector& roles) { + return validatedConvert(roles); +} + GeneralResult> toUnsigned(const std::vector& 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"; @@ -576,42 +589,7 @@ GeneralResult> toUnsigned(const std::vector& vec) namespace aidl::android::hardware::neuralnetworks::utils { namespace { -template -using UnvalidatedConvertOutput = - std::decay_t()).value())>; - -template -nn::GeneralResult>> unvalidatedConvertVec( - const std::vector& arguments) { - std::vector> halObject; - halObject.reserve(arguments.size()); - for (const auto& argument : arguments) { - halObject.push_back(NN_TRY(unvalidatedConvert(argument))); - } - return halObject; -} - -template -nn::GeneralResult>> unvalidatedConvert( - const std::vector& arguments) { - return unvalidatedConvertVec(arguments); -} - -template -nn::GeneralResult> validatedConvert(const Type& canonical) { - NN_TRY(compliantVersion(canonical)); - return utils::unvalidatedConvert(canonical); -} - -template -nn::GeneralResult>> validatedConvert( - const std::vector& arguments) { - std::vector> halObject(arguments.size()); - for (size_t i = 0; i < arguments.size(); ++i) { - halObject[i] = NN_TRY(validatedConvert(arguments[i])); - } - return halObject; -} +using utils::unvalidatedConvert; // Helper template for std::visit template @@ -721,6 +699,74 @@ nn::GeneralResult unvalidatedConvert(const nn::Memory::Unknown& /*memory operator nn::GeneralResult(); } +nn::GeneralResult unvalidatedConvert( + const nn::Capabilities::PerformanceInfo& info) { + return PerformanceInfo{.execTime = info.execTime, .powerUsage = info.powerUsage}; +} + +nn::GeneralResult unvalidatedConvert( + const nn::Capabilities::OperandPerformance& operandPerformance) { + return OperandPerformance{.type = NN_TRY(unvalidatedConvert(operandPerformance.type)), + .info = NN_TRY(unvalidatedConvert(operandPerformance.info))}; +} + +nn::GeneralResult> unvalidatedConvert( + const nn::Capabilities::OperandPerformanceTable& table) { + std::vector operandPerformances; + operandPerformances.reserve(table.asVector().size()); + for (const auto& operandPerformance : table.asVector()) { + operandPerformances.push_back(NN_TRY(unvalidatedConvert(operandPerformance))); + } + return operandPerformances; +} + +nn::GeneralResult unvalidatedConvert( + const nn::Extension::OperandTypeInformation& info) { + return ExtensionOperandTypeInformation{.type = info.type, + .isTensor = info.isTensor, + .byteSize = static_cast(info.byteSize)}; +} + +nn::GeneralResult unvalidatedConvert(const nn::Duration& duration) { + if (duration < nn::Duration::zero()) { + return NN_ERROR() << "Unable to convert invalid (negative) duration"; + } + constexpr std::chrono::nanoseconds::rep kIntMax = std::numeric_limits::max(); + const auto count = duration.count(); + return static_cast(std::min(count, kIntMax)); +} + +template +using UnvalidatedConvertOutput = + std::decay_t()).value())>; + +template +nn::GeneralResult>> unvalidatedConvert( + const std::vector& arguments) { + std::vector> halObject; + halObject.reserve(arguments.size()); + for (const auto& argument : arguments) { + halObject.push_back(NN_TRY(unvalidatedConvert(argument))); + } + return halObject; +} + +template +nn::GeneralResult> validatedConvert(const Type& canonical) { + NN_TRY(compliantVersion(canonical)); + return utils::unvalidatedConvert(canonical); +} + +template +nn::GeneralResult>> validatedConvert( + const std::vector& arguments) { + std::vector> halObject(arguments.size()); + for (size_t i = 0; i < arguments.size(); ++i) { + halObject[i] = NN_TRY(validatedConvert(arguments[i])); + } + return halObject; +} + } // namespace nn::GeneralResult> unvalidatedConvert(const nn::CacheToken& cacheToken) { @@ -743,6 +789,19 @@ nn::GeneralResult unvalidatedConvert(const nn::BufferRole& bufferRol }; } +nn::GeneralResult unvalidatedConvert(const nn::DeviceType& deviceType) { + switch (deviceType) { + case nn::DeviceType::UNKNOWN: + break; + case nn::DeviceType::OTHER: + case nn::DeviceType::CPU: + case nn::DeviceType::GPU: + case nn::DeviceType::ACCELERATOR: + return static_cast(deviceType); + } + return NN_ERROR() << "Invalid DeviceType " << deviceType; +} + nn::GeneralResult unvalidatedConvert(const nn::MeasureTiming& measureTiming) { return measureTiming == nn::MeasureTiming::YES; } @@ -956,15 +1015,6 @@ nn::GeneralResult unvalidatedConvert(const nn::Timing& timing) { }; } -nn::GeneralResult unvalidatedConvert(const nn::Duration& duration) { - if (duration < nn::Duration::zero()) { - return NN_ERROR() << "Unable to convert invalid (negative) duration"; - } - constexpr std::chrono::nanoseconds::rep kIntMax = std::numeric_limits::max(); - const auto count = duration.count(); - return static_cast(std::min(count, kIntMax)); -} - nn::GeneralResult unvalidatedConvert(const nn::OptionalDuration& optionalDuration) { if (!optionalDuration.has_value()) { return kNoTiming; @@ -989,6 +1039,23 @@ nn::GeneralResult unvalidatedConvert(const nn::Shared return ndk::ScopedFileDescriptor(duplicatedFd.release()); } +nn::GeneralResult unvalidatedConvert(const nn::Capabilities& capabilities) { + return Capabilities{ + .relaxedFloat32toFloat16PerformanceTensor = NN_TRY( + unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)), + .relaxedFloat32toFloat16PerformanceScalar = NN_TRY( + unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)), + .operandPerformance = NN_TRY(unvalidatedConvert(capabilities.operandPerformance)), + .ifPerformance = NN_TRY(unvalidatedConvert(capabilities.ifPerformance)), + .whilePerformance = NN_TRY(unvalidatedConvert(capabilities.whilePerformance)), + }; +} + +nn::GeneralResult unvalidatedConvert(const nn::Extension& extension) { + return Extension{.name = extension.name, + .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes))}; +} + nn::GeneralResult> convert(const nn::CacheToken& cacheToken) { return validatedConvert(cacheToken); } @@ -997,6 +1064,10 @@ nn::GeneralResult convert(const nn::BufferDesc& bufferDesc) { return validatedConvert(bufferDesc); } +nn::GeneralResult convert(const nn::DeviceType& deviceType) { + return validatedConvert(deviceType); +} + nn::GeneralResult convert(const nn::MeasureTiming& measureTiming) { return validatedConvert(measureTiming); } @@ -1037,6 +1108,14 @@ nn::GeneralResult convert(const nn::OptionalTimePoint& outputShapes) { return validatedConvert(outputShapes); } +nn::GeneralResult convert(const nn::Capabilities& capabilities) { + return validatedConvert(capabilities); +} + +nn::GeneralResult convert(const nn::Extension& extension) { + return validatedConvert(extension); +} + nn::GeneralResult> convert(const std::vector& bufferRoles) { return validatedConvert(bufferRoles); } @@ -1056,6 +1135,10 @@ nn::GeneralResult> convert( return validatedConvert(syncFences); } +nn::GeneralResult> convert(const std::vector& extensions) { + return validatedConvert(extensions); +} + nn::GeneralResult> toSigned(const std::vector& vec) { if (!std::all_of(vec.begin(), vec.end(), [](uint32_t v) { return v <= std::numeric_limits::max(); })) { diff --git a/neuralnetworks/utils/adapter/aidl/Android.bp b/neuralnetworks/utils/adapter/aidl/Android.bp new file mode 100644 index 0000000000..8269a3d4aa --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/Android.bp @@ -0,0 +1,42 @@ +// +// 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. +// + +package { + // See: http://go/android-license-faq + // A large-scale-change added 'default_applicable_licenses' to import + // all of the 'license_kinds' from "hardware_interfaces_license" + // to get the below license kinds: + // SPDX-license-identifier-Apache-2.0 + default_applicable_licenses: ["hardware_interfaces_license"], +} + +cc_library_static { + name: "neuralnetworks_utils_hal_adapter_aidl", + defaults: [ + "neuralnetworks_use_latest_utils_hal_aidl", + "neuralnetworks_utils_defaults", + ], + srcs: ["src/*"], + local_include_dirs: ["include/nnapi/hal/aidl/"], + export_include_dirs: ["include"], + static_libs: [ + "neuralnetworks_types", + "neuralnetworks_utils_hal_common", + ], + shared_libs: [ + "libbinder_ndk", + ], +} diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h new file mode 100644 index 0000000000..4c0b3286de --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h @@ -0,0 +1,73 @@ +/* + * 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. + */ + +#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_ADAPTER_H +#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_ADAPTER_H + +#include +#include +#include + +#include +#include + +// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface +// lifetimes across processes and for protecting asynchronous calls across AIDL. + +namespace aidl::android::hardware::neuralnetworks::adapter { + +/** + * A self-contained unit of work to be executed. + */ +using Task = std::function; + +/** + * A type-erased executor which executes a task asynchronously. + * + * This executor is also provided an optional deadline for when the caller expects is the upper + * bound for the amount of time to complete the task. If needed, the Executor can retrieve the + * Application ID (Android User ID) by calling AIBinder_getCallingUid in android/binder_ibinder.h. + */ +using Executor = std::function; + +/** + * Adapt an NNAPI canonical interface object to a AIDL NN HAL interface object. + * + * The IPreparedModel object created from IDevice::prepareModel or IDevice::preparedModelFromCache + * must return "const nn::Model*" from IPreparedModel::getUnderlyingResource(). + * + * @param device NNAPI canonical IDevice interface object to be adapted. + * @param executor Type-erased executor to handle executing tasks asynchronously. + * @return AIDL NN HAL IDevice interface object. + */ +std::shared_ptr adapt(::android::nn::SharedDevice device, Executor executor); + +/** + * Adapt an NNAPI canonical interface object to a AIDL NN HAL interface object. + * + * The IPreparedModel object created from IDevice::prepareModel or IDevice::preparedModelFromCache + * must return "const nn::Model*" from IPreparedModel::getUnderlyingResource(). + * + * This function uses a default executor, which will execute tasks from a detached thread. + * + * @param device NNAPI canonical IDevice interface object to be adapted. + * @return AIDL NN HAL IDevice interface object. + */ +std::shared_ptr adapt(::android::nn::SharedDevice device); + +} // namespace aidl::android::hardware::neuralnetworks::adapter + +#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_ADAPTER_H diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Buffer.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Buffer.h new file mode 100644 index 0000000000..701e43eb01 --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Buffer.h @@ -0,0 +1,47 @@ +/* + * 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. + */ + +#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BUFFER_H +#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BUFFER_H + +#include +#include +#include +#include + +#include +#include + +// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface +// lifetimes across processes and for protecting asynchronous calls across AIDL. + +namespace aidl::android::hardware::neuralnetworks::adapter { + +// Class that adapts nn::IBuffer to BnBuffer. +class Buffer : public BnBuffer { + public: + explicit Buffer(::android::nn::SharedBuffer buffer); + + ndk::ScopedAStatus copyFrom(const Memory& src, const std::vector& dimensions) override; + ndk::ScopedAStatus copyTo(const Memory& dst) override; + + private: + const ::android::nn::SharedBuffer kBuffer; +}; + +} // namespace aidl::android::hardware::neuralnetworks::adapter + +#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BUFFER_H diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Burst.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Burst.h new file mode 100644 index 0000000000..f2687c4a69 --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Burst.h @@ -0,0 +1,72 @@ +/* + * 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. + */ + +#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BURST_H +#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BURST_H + +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include + +// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface +// lifetimes across processes and for protecting asynchronous calls across AIDL. + +namespace aidl::android::hardware::neuralnetworks::adapter { + +// Class that adapts nn::Burst to BnBurst. +class Burst : public BnBurst { + public: + // Precondition: burst != nullptr + explicit Burst(::android::nn::SharedBurst burst); + + ndk::ScopedAStatus executeSynchronously(const Request& request, + const std::vector& memoryIdentifierTokens, + bool measureTiming, int64_t deadlineNs, + int64_t loopTimeoutDurationNs, + ExecutionResult* executionResult) override; + ndk::ScopedAStatus releaseMemoryResource(int64_t memoryIdentifierToken) override; + + class ThreadSafeMemoryCache { + public: + using Value = + std::pair<::android::nn::SharedMemory, ::android::nn::IBurst::OptionalCacheHold>; + + Value add(int64_t token, const ::android::nn::SharedMemory& memory, + const ::android::nn::IBurst& burst) const; + void remove(int64_t token) const; + + private: + mutable std::mutex mMutex; + mutable std::unordered_map mCache GUARDED_BY(mMutex); + }; + + private: + const ::android::nn::SharedBurst kBurst; + const ThreadSafeMemoryCache kMemoryCache; +}; + +} // namespace aidl::android::hardware::neuralnetworks::adapter + +#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_BURST_H diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Device.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Device.h new file mode 100644 index 0000000000..aa29d63b6b --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Device.h @@ -0,0 +1,83 @@ +/* + * 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. + */ + +#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_DEVICE_H +#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_DEVICE_H + +#include "nnapi/hal/aidl/Adapter.h" + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include + +// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface +// lifetimes across processes and for protecting asynchronous calls across AIDL. + +namespace aidl::android::hardware::neuralnetworks::adapter { + +// Class that adapts nn::IDevice to BnDevice. +class Device : public BnDevice { + public: + Device(::android::nn::SharedDevice device, Executor executor); + + ndk::ScopedAStatus allocate(const BufferDesc& desc, + const std::vector& preparedModels, + const std::vector& inputRoles, + const std::vector& outputRoles, + DeviceBuffer* buffer) override; + ndk::ScopedAStatus getCapabilities(Capabilities* capabilities) override; + ndk::ScopedAStatus getNumberOfCacheFilesNeeded(NumberOfCacheFiles* numberOfCacheFiles) override; + ndk::ScopedAStatus getSupportedExtensions(std::vector* extensions) override; + ndk::ScopedAStatus getSupportedOperations(const Model& model, + std::vector* supported) override; + ndk::ScopedAStatus getType(DeviceType* deviceType) override; + ndk::ScopedAStatus getVersionString(std::string* version) override; + ndk::ScopedAStatus prepareModel( + const Model& model, ExecutionPreference preference, Priority priority, + int64_t deadlineNs, const std::vector& modelCache, + const std::vector& dataCache, + const std::vector& token, + const std::shared_ptr& callback) override; + ndk::ScopedAStatus prepareModelFromCache( + int64_t deadlineNs, const std::vector& modelCache, + const std::vector& dataCache, + const std::vector& token, + const std::shared_ptr& callback) override; + + protected: + const ::android::nn::SharedDevice kDevice; + const Executor kExecutor; +}; + +} // namespace aidl::android::hardware::neuralnetworks::adapter + +#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_DEVICE_H diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/PreparedModel.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/PreparedModel.h new file mode 100644 index 0000000000..93e0427426 --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/PreparedModel.h @@ -0,0 +1,62 @@ +/* + * 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. + */ + +#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_PREPARED_MDOEL_H +#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_PREPARED_MDOEL_H + +#include "nnapi/hal/aidl/Adapter.h" + +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include + +// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface +// lifetimes across processes and for protecting asynchronous calls across AIDL. + +namespace aidl::android::hardware::neuralnetworks::adapter { + +// Class that adapts nn::IPreparedModel to BnPreparedModel. +class PreparedModel : public BnPreparedModel { + public: + explicit PreparedModel(::android::nn::SharedPreparedModel preparedModel); + + ndk::ScopedAStatus executeSynchronously(const Request& request, bool measureTiming, + int64_t deadlineNs, int64_t loopTimeoutDurationNs, + ExecutionResult* executionResult) override; + ndk::ScopedAStatus executeFenced(const Request& request, + const std::vector& waitFor, + bool measureTiming, int64_t deadlineNs, + int64_t loopTimeoutDurationNs, int64_t durationNs, + FencedExecutionResult* executionResult) override; + ndk::ScopedAStatus configureExecutionBurst(std::shared_ptr* burst) override; + + ::android::nn::SharedPreparedModel getUnderlyingPreparedModel() const; + + protected: + const ::android::nn::SharedPreparedModel kPreparedModel; +}; + +} // namespace aidl::android::hardware::neuralnetworks::adapter + +#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_ADAPTER_AIDL_PREPARED_MDOEL_H diff --git a/neuralnetworks/utils/adapter/aidl/src/Adapter.cpp b/neuralnetworks/utils/adapter/aidl/src/Adapter.cpp new file mode 100644 index 0000000000..d0b56e89cc --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/src/Adapter.cpp @@ -0,0 +1,46 @@ +/* + * 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 "Adapter.h" + +#include "Device.h" + +#include +#include +#include +#include + +#include +#include +#include + +// See hardware/interfaces/neuralnetworks/utils/README.md for more information on AIDL interface +// lifetimes across processes and for protecting asynchronous calls across AIDL. + +namespace aidl::android::hardware::neuralnetworks::adapter { + +std::shared_ptr adapt(::android::nn::SharedDevice device, Executor executor) { + return ndk::SharedRefBase::make(std::move(device), std::move(executor)); +} + +std::shared_ptr adapt(::android::nn::SharedDevice device) { + Executor defaultExecutor = [](Task task, ::android::nn::OptionalTimePoint /*deadline*/) { + std::thread(std::move(task)).detach(); + }; + return adapt(std::move(device), std::move(defaultExecutor)); +} + +} // namespace aidl::android::hardware::neuralnetworks::adapter diff --git a/neuralnetworks/utils/adapter/aidl/src/Buffer.cpp b/neuralnetworks/utils/adapter/aidl/src/Buffer.cpp new file mode 100644 index 0000000000..c15ab659c5 --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/src/Buffer.cpp @@ -0,0 +1,88 @@ +/* + * 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 "Buffer.h" + +#include +#include +#include +#include +#include +#include +#include +#include + +namespace aidl::android::hardware::neuralnetworks::adapter { +namespace { + +template +auto convertInput(const Type& object) -> decltype(nn::convert(std::declval())) { + auto result = nn::convert(object); + if (!result.has_value()) { + result.error().code = nn::ErrorStatus::INVALID_ARGUMENT; + } + return result; +} + +nn::GeneralResult> inputToUnsigned(const std::vector& dims) { + auto result = nn::toUnsigned(dims); + if (!result.has_value()) { + result.error().code = nn::ErrorStatus::INVALID_ARGUMENT; + } + return result; +} + +nn::GeneralResult copyTo(const nn::IBuffer& buffer, const Memory& dst) { + const auto nnDst = NN_TRY(convertInput(dst)); + return buffer.copyTo(nnDst); +} + +nn::GeneralResult copyFrom(const nn::IBuffer& buffer, const Memory& src, + const std::vector& dimensions) { + const auto nnSrc = NN_TRY(convertInput(src)); + const auto nnDims = NN_TRY(inputToUnsigned(dimensions)); + return buffer.copyFrom(nnSrc, nnDims); +} + +} // namespace + +Buffer::Buffer(nn::SharedBuffer buffer) : kBuffer(std::move(buffer)) { + CHECK(kBuffer != nullptr); +} + +ndk::ScopedAStatus Buffer::copyTo(const Memory& dst) { + const auto result = adapter::copyTo(*kBuffer, dst); + if (!result.has_value()) { + const auto& [message, code] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Buffer::copyFrom(const Memory& src, const std::vector& dimensions) { + const auto result = adapter::copyFrom(*kBuffer, src, dimensions); + if (!result.has_value()) { + const auto& [message, code] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + return ndk::ScopedAStatus::ok(); +} + +} // namespace aidl::android::hardware::neuralnetworks::adapter diff --git a/neuralnetworks/utils/adapter/aidl/src/Burst.cpp b/neuralnetworks/utils/adapter/aidl/src/Burst.cpp new file mode 100644 index 0000000000..4fabb20635 --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/src/Burst.cpp @@ -0,0 +1,179 @@ +/* + * 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 "Burst.h" + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include +#include +#include +#include + +namespace aidl::android::hardware::neuralnetworks::adapter { +namespace { + +using Value = Burst::ThreadSafeMemoryCache::Value; + +template +auto convertInput(const Type& object) -> decltype(nn::convert(std::declval())) { + auto result = nn::convert(object); + if (!result.has_value()) { + result.error().code = nn::ErrorStatus::INVALID_ARGUMENT; + } + return result; +} + +nn::Duration makeDuration(int64_t durationNs) { + return nn::Duration(std::chrono::nanoseconds(durationNs)); +} + +nn::GeneralResult makeOptionalDuration(int64_t durationNs) { + if (durationNs < -1) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid duration " << durationNs; + } + return durationNs < 0 ? nn::OptionalDuration{} : makeDuration(durationNs); +} + +nn::GeneralResult makeOptionalTimePoint(int64_t durationNs) { + if (durationNs < -1) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid time point " << durationNs; + } + return durationNs < 0 ? nn::OptionalTimePoint{} : nn::TimePoint(makeDuration(durationNs)); +} + +std::vector ensureAllMemoriesAreCached( + nn::Request* request, const std::vector& memoryIdentifierTokens, + const nn::IBurst& burst, const Burst::ThreadSafeMemoryCache& cache) { + std::vector holds; + holds.reserve(memoryIdentifierTokens.size()); + + for (size_t i = 0; i < memoryIdentifierTokens.size(); ++i) { + const auto& pool = request->pools[i]; + const auto token = memoryIdentifierTokens[i]; + constexpr int64_t kNoToken = -1; + if (token == kNoToken || !std::holds_alternative(pool)) { + continue; + } + + const auto& memory = std::get(pool); + auto [storedMemory, hold] = cache.add(token, memory, burst); + + request->pools[i] = std::move(storedMemory); + holds.push_back(std::move(hold)); + } + + return holds; +} + +nn::ExecutionResult executeSynchronously( + const nn::IBurst& burst, const Burst::ThreadSafeMemoryCache& cache, const Request& request, + const std::vector& memoryIdentifierTokens, bool measureTiming, int64_t deadlineNs, + int64_t loopTimeoutDurationNs) { + if (request.pools.size() != memoryIdentifierTokens.size()) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) + << "request.pools.size() != memoryIdentifierTokens.size()"; + } + if (!std::all_of(memoryIdentifierTokens.begin(), memoryIdentifierTokens.end(), + [](int64_t token) { return token >= -1; })) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid memoryIdentifierTokens"; + } + + auto nnRequest = NN_TRY(convertInput(request)); + const auto nnMeasureTiming = measureTiming ? nn::MeasureTiming::YES : nn::MeasureTiming::NO; + const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs)); + const auto nnLoopTimeoutDuration = NN_TRY(makeOptionalDuration(loopTimeoutDurationNs)); + + const auto hold = ensureAllMemoriesAreCached(&nnRequest, memoryIdentifierTokens, burst, cache); + + const auto result = + burst.execute(nnRequest, nnMeasureTiming, nnDeadline, nnLoopTimeoutDuration); + + if (!result.ok() && result.error().code == nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) { + const auto& [message, code, outputShapes] = result.error(); + return ExecutionResult{.outputSufficientSize = false, + .outputShapes = utils::convert(outputShapes).value(), + .timing = {.timeInDriverNs = -1, .timeOnDeviceNs = -1}}; + } + + const auto& [outputShapes, timing] = NN_TRY(result); + return ExecutionResult{.outputSufficientSize = true, + .outputShapes = utils::convert(outputShapes).value(), + .timing = utils::convert(timing).value()}; +} + +} // namespace + +Value Burst::ThreadSafeMemoryCache::add(int64_t token, const nn::SharedMemory& memory, + const nn::IBurst& burst) const { + std::lock_guard guard(mMutex); + if (const auto it = mCache.find(token); it != mCache.end()) { + return it->second; + } + auto hold = burst.cacheMemory(memory); + auto [it, _] = mCache.emplace(token, std::make_pair(memory, std::move(hold))); + return it->second; +} + +void Burst::ThreadSafeMemoryCache::remove(int64_t token) const { + std::lock_guard guard(mMutex); + mCache.erase(token); +} + +Burst::Burst(nn::SharedBurst burst) : kBurst(std::move(burst)) { + CHECK(kBurst != nullptr); +} + +ndk::ScopedAStatus Burst::executeSynchronously(const Request& request, + const std::vector& memoryIdentifierTokens, + bool measureTiming, int64_t deadlineNs, + int64_t loopTimeoutDurationNs, + ExecutionResult* executionResult) { + auto result = + adapter::executeSynchronously(*kBurst, kMemoryCache, request, memoryIdentifierTokens, + measureTiming, deadlineNs, loopTimeoutDurationNs); + if (!result.has_value()) { + auto [message, code, _] = std::move(result).error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + *executionResult = std::move(result).value(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Burst::releaseMemoryResource(int64_t memoryIdentifierToken) { + if (memoryIdentifierToken < -1) { + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(ErrorStatus::INVALID_ARGUMENT), + "Invalid memoryIdentifierToken"); + } + kMemoryCache.remove(memoryIdentifierToken); + return ndk::ScopedAStatus::ok(); +} + +} // namespace aidl::android::hardware::neuralnetworks::adapter diff --git a/neuralnetworks/utils/adapter/aidl/src/Device.cpp b/neuralnetworks/utils/adapter/aidl/src/Device.cpp new file mode 100644 index 0000000000..763be7f3fa --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/src/Device.cpp @@ -0,0 +1,304 @@ +/* + * 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 "Device.h" + +#include "Adapter.h" +#include "Buffer.h" +#include "PreparedModel.h" + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include + +namespace aidl::android::hardware::neuralnetworks::adapter { +namespace { + +template +auto convertInput(const Type& object) -> decltype(nn::convert(std::declval())) { + auto result = nn::convert(object); + if (!result.has_value()) { + result.error().code = nn::ErrorStatus::INVALID_ARGUMENT; + } + return result; +} + +nn::Duration makeDuration(int64_t durationNs) { + return nn::Duration(std::chrono::nanoseconds(durationNs)); +} + +nn::GeneralResult makeOptionalTimePoint(int64_t durationNs) { + if (durationNs < -1) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid time point " << durationNs; + } + return durationNs < 0 ? nn::OptionalTimePoint{} : nn::TimePoint(makeDuration(durationNs)); +} + +nn::GeneralResult convertCacheToken(const std::vector& token) { + nn::CacheToken nnToken; + if (token.size() != nnToken.size()) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid token"; + } + std::copy(token.begin(), token.end(), nnToken.begin()); + return nnToken; +} + +nn::GeneralResult downcast(const IPreparedModelParcel& preparedModel) { + if (preparedModel.preparedModel == nullptr) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "preparedModel is nullptr"; + } + if (preparedModel.preparedModel->isRemote()) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Cannot convert remote models"; + } + + // This static_cast is safe because adapter::PreparedModel is the only class that implements + // the IPreparedModel interface in the adapter service code. + const auto* casted = static_cast(preparedModel.preparedModel.get()); + return casted->getUnderlyingPreparedModel(); +} + +nn::GeneralResult> downcastAll( + const std::vector& preparedModels) { + std::vector canonical; + canonical.reserve(preparedModels.size()); + for (const auto& preparedModel : preparedModels) { + canonical.push_back(NN_TRY(downcast(preparedModel))); + } + return canonical; +} + +nn::GeneralResult allocate(const nn::IDevice& device, const BufferDesc& desc, + const std::vector& preparedModels, + const std::vector& inputRoles, + const std::vector& outputRoles) { + auto nnDesc = NN_TRY(convertInput(desc)); + auto nnPreparedModels = NN_TRY(downcastAll(preparedModels)); + auto nnInputRoles = NN_TRY(convertInput(inputRoles)); + auto nnOutputRoles = NN_TRY(convertInput(outputRoles)); + + auto buffer = NN_TRY(device.allocate(nnDesc, nnPreparedModels, nnInputRoles, nnOutputRoles)); + CHECK(buffer != nullptr); + + const nn::Request::MemoryDomainToken token = buffer->getToken(); + auto aidlBuffer = ndk::SharedRefBase::make(std::move(buffer)); + return DeviceBuffer{.buffer = std::move(aidlBuffer), .token = static_cast(token)}; +} + +nn::GeneralResult> getSupportedOperations(const nn::IDevice& device, + const Model& model) { + const auto nnModel = NN_TRY(convertInput(model)); + return device.getSupportedOperations(nnModel); +} + +using PrepareModelResult = nn::GeneralResult; + +std::shared_ptr adaptPreparedModel(nn::SharedPreparedModel preparedModel) { + if (preparedModel == nullptr) { + return nullptr; + } + return ndk::SharedRefBase::make(std::move(preparedModel)); +} + +void notify(IPreparedModelCallback* callback, PrepareModelResult result) { + if (!result.has_value()) { + const auto& [message, status] = result.error(); + LOG(ERROR) << message; + const auto aidlCode = utils::convert(status).value_or(ErrorStatus::GENERAL_FAILURE); + callback->notify(aidlCode, nullptr); + } else { + auto preparedModel = std::move(result).value(); + auto aidlPreparedModel = adaptPreparedModel(std::move(preparedModel)); + callback->notify(ErrorStatus::NONE, std::move(aidlPreparedModel)); + } +} + +nn::GeneralResult prepareModel(const nn::SharedDevice& device, const Executor& executor, + const Model& model, ExecutionPreference preference, + Priority priority, int64_t deadlineNs, + const std::vector& modelCache, + const std::vector& dataCache, + const std::vector& token, + const std::shared_ptr& callback) { + if (callback.get() == nullptr) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback"; + } + + auto nnModel = NN_TRY(convertInput(model)); + const auto nnPreference = NN_TRY(convertInput(preference)); + const auto nnPriority = NN_TRY(convertInput(priority)); + const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs)); + auto nnModelCache = NN_TRY(convertInput(modelCache)); + auto nnDataCache = NN_TRY(convertInput(dataCache)); + const auto nnToken = NN_TRY(convertCacheToken(token)); + + Task task = [device, nnModel = std::move(nnModel), nnPreference, nnPriority, nnDeadline, + nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache), + nnToken, callback] { + auto result = device->prepareModel(nnModel, nnPreference, nnPriority, nnDeadline, + nnModelCache, nnDataCache, nnToken); + notify(callback.get(), std::move(result)); + }; + executor(std::move(task), nnDeadline); + + return {}; +} + +nn::GeneralResult prepareModelFromCache( + const nn::SharedDevice& device, const Executor& executor, int64_t deadlineNs, + const std::vector& modelCache, + const std::vector& dataCache, const std::vector& token, + const std::shared_ptr& callback) { + if (callback.get() == nullptr) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback"; + } + + const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs)); + auto nnModelCache = NN_TRY(convertInput(modelCache)); + auto nnDataCache = NN_TRY(convertInput(dataCache)); + const auto nnToken = NN_TRY(convertCacheToken(token)); + + auto task = [device, nnDeadline, nnModelCache = std::move(nnModelCache), + nnDataCache = std::move(nnDataCache), nnToken, callback] { + auto result = device->prepareModelFromCache(nnDeadline, nnModelCache, nnDataCache, nnToken); + notify(callback.get(), std::move(result)); + }; + executor(std::move(task), nnDeadline); + + return {}; +} + +} // namespace + +Device::Device(::android::nn::SharedDevice device, Executor executor) + : kDevice(std::move(device)), kExecutor(std::move(executor)) { + CHECK(kDevice != nullptr); + CHECK(kExecutor != nullptr); +} + +ndk::ScopedAStatus Device::allocate(const BufferDesc& desc, + const std::vector& preparedModels, + const std::vector& inputRoles, + const std::vector& outputRoles, + DeviceBuffer* buffer) { + auto result = adapter::allocate(*kDevice, desc, preparedModels, inputRoles, outputRoles); + if (!result.has_value()) { + const auto& [message, code] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + *buffer = std::move(result).value(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Device::getCapabilities(Capabilities* capabilities) { + *capabilities = utils::convert(kDevice->getCapabilities()).value(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Device::getNumberOfCacheFilesNeeded(NumberOfCacheFiles* numberOfCacheFiles) { + const auto [numModelCache, numDataCache] = kDevice->getNumberOfCacheFilesNeeded(); + *numberOfCacheFiles = NumberOfCacheFiles{.numModelCache = static_cast(numModelCache), + .numDataCache = static_cast(numDataCache)}; + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Device::getSupportedExtensions(std::vector* extensions) { + *extensions = utils::convert(kDevice->getSupportedExtensions()).value(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Device::getSupportedOperations(const Model& model, + std::vector* supported) { + auto result = adapter::getSupportedOperations(*kDevice, model); + if (!result.has_value()) { + const auto& [message, code] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + *supported = std::move(result).value(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Device::getType(DeviceType* deviceType) { + *deviceType = utils::convert(kDevice->getType()).value(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Device::getVersionString(std::string* version) { + *version = kDevice->getVersionString(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Device::prepareModel(const Model& model, ExecutionPreference preference, + Priority priority, int64_t deadlineNs, + const std::vector& modelCache, + const std::vector& dataCache, + const std::vector& token, + const std::shared_ptr& callback) { + const auto result = adapter::prepareModel(kDevice, kExecutor, model, preference, priority, + deadlineNs, modelCache, dataCache, token, callback); + if (!result.has_value()) { + const auto& [message, code] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + callback->notify(aidlCode, nullptr); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus Device::prepareModelFromCache( + int64_t deadlineNs, const std::vector& modelCache, + const std::vector& dataCache, const std::vector& token, + const std::shared_ptr& callback) { + const auto result = adapter::prepareModelFromCache(kDevice, kExecutor, deadlineNs, modelCache, + dataCache, token, callback); + if (!result.has_value()) { + const auto& [message, code] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + callback->notify(aidlCode, nullptr); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + return ndk::ScopedAStatus::ok(); +} + +} // namespace aidl::android::hardware::neuralnetworks::adapter diff --git a/neuralnetworks/utils/adapter/aidl/src/PreparedModel.cpp b/neuralnetworks/utils/adapter/aidl/src/PreparedModel.cpp new file mode 100644 index 0000000000..71ed1a857b --- /dev/null +++ b/neuralnetworks/utils/adapter/aidl/src/PreparedModel.cpp @@ -0,0 +1,225 @@ +/* + * 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 "PreparedModel.h" + +#include "Burst.h" + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include + +namespace aidl::android::hardware::neuralnetworks::adapter { +namespace { + +class FencedExecutionCallback : public BnFencedExecutionCallback { + public: + FencedExecutionCallback(nn::ExecuteFencedInfoCallback callback) + : kCallback(std::move(callback)) {} + + ndk::ScopedAStatus getExecutionInfo(Timing* timingLaunched, Timing* timingFenced, + ErrorStatus* errorStatus) override { + const auto result = kCallback(); + if (result.ok()) { + const auto& [nnTimingLaunched, nnTimingFenced] = result.value(); + *timingLaunched = utils::convert(nnTimingLaunched).value(); + *timingFenced = utils::convert(nnTimingFenced).value(); + *errorStatus = ErrorStatus::NONE; + } else { + constexpr auto kNoTiming = Timing{.timeOnDeviceNs = -1, .timeInDriverNs = -1}; + const auto& [message, code] = result.error(); + LOG(ERROR) << "getExecutionInfo failed with " << code << ": " << message; + const auto aidlStatus = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + *timingLaunched = kNoTiming; + *timingFenced = kNoTiming; + *errorStatus = aidlStatus; + } + return ndk::ScopedAStatus::ok(); + } + + private: + const nn::ExecuteFencedInfoCallback kCallback; +}; + +template +auto convertInput(const Type& object) -> decltype(nn::convert(std::declval())) { + auto result = nn::convert(object); + if (!result.has_value()) { + result.error().code = nn::ErrorStatus::INVALID_ARGUMENT; + } + return result; +} + +nn::GeneralResult> convertSyncFences( + const std::vector& waitFor) { + auto handles = NN_TRY(convertInput(waitFor)); + + constexpr auto valid = [](const nn::SharedHandle& handle) { + return handle != nullptr && handle->ok(); + }; + if (!std::all_of(handles.begin(), handles.end(), valid)) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid sync fence"; + } + + std::vector syncFences; + syncFences.reserve(waitFor.size()); + for (auto& handle : handles) { + syncFences.push_back(nn::SyncFence::create(std::move(handle)).value()); + } + return syncFences; +} + +nn::Duration makeDuration(int64_t durationNs) { + return nn::Duration(std::chrono::nanoseconds(durationNs)); +} + +nn::GeneralResult makeOptionalDuration(int64_t durationNs) { + if (durationNs < -1) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid duration " << durationNs; + } + return durationNs < 0 ? nn::OptionalDuration{} : makeDuration(durationNs); +} + +nn::GeneralResult makeOptionalTimePoint(int64_t durationNs) { + if (durationNs < -1) { + return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid time point " << durationNs; + } + return durationNs < 0 ? nn::OptionalTimePoint{} : nn::TimePoint(makeDuration(durationNs)); +} + +nn::ExecutionResult executeSynchronously(const nn::IPreparedModel& preparedModel, + const Request& request, + bool measureTiming, int64_t deadlineNs, + int64_t loopTimeoutDurationNs) { + const auto nnRequest = NN_TRY(convertInput(request)); + const auto nnMeasureTiming = measureTiming ? nn::MeasureTiming::YES : nn::MeasureTiming::NO; + const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs)); + const auto nnLoopTimeoutDuration = NN_TRY(makeOptionalDuration(loopTimeoutDurationNs)); + + const auto result = + preparedModel.execute(nnRequest, nnMeasureTiming, nnDeadline, nnLoopTimeoutDuration); + + if (!result.ok() && result.error().code == nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) { + const auto& [message, code, outputShapes] = result.error(); + LOG(ERROR) << "executeSynchronously failed with " << code << ": " << message; + return ExecutionResult{.outputSufficientSize = false, + .outputShapes = utils::convert(outputShapes).value(), + .timing = {.timeInDriverNs = -1, .timeOnDeviceNs = -1}}; + } + + const auto& [outputShapes, timing] = NN_TRY(result); + return ExecutionResult{.outputSufficientSize = true, + .outputShapes = utils::convert(outputShapes).value(), + .timing = utils::convert(timing).value()}; +} + +nn::GeneralResult executeFenced( + const nn::IPreparedModel& preparedModel, const Request& request, + const std::vector& waitFor, bool measureTiming, + int64_t deadlineNs, int64_t loopTimeoutDurationNs, int64_t durationNs) { + const auto nnRequest = NN_TRY(convertInput(request)); + const auto nnWaitFor = NN_TRY(convertSyncFences(waitFor)); + const auto nnMeasureTiming = measureTiming ? nn::MeasureTiming::YES : nn::MeasureTiming::NO; + const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs)); + const auto nnLoopTimeoutDuration = NN_TRY(makeOptionalDuration(loopTimeoutDurationNs)); + const auto nnDuration = NN_TRY(makeOptionalDuration(durationNs)); + + auto [syncFence, executeFencedInfoCallback] = NN_TRY(preparedModel.executeFenced( + nnRequest, nnWaitFor, nnMeasureTiming, nnDeadline, nnLoopTimeoutDuration, nnDuration)); + + ndk::ScopedFileDescriptor fileDescriptor; + if (syncFence.hasFd()) { + auto uniqueFd = NN_TRY(nn::dupFd(syncFence.getFd())); + fileDescriptor = ndk::ScopedFileDescriptor(uniqueFd.release()); + } + + return FencedExecutionResult{.callback = ndk::SharedRefBase::make( + std::move(executeFencedInfoCallback)), + .syncFence = std::move(fileDescriptor)}; +} + +} // namespace + +PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel) + : kPreparedModel(std::move(preparedModel)) { + CHECK(kPreparedModel != nullptr); +} + +ndk::ScopedAStatus PreparedModel::executeSynchronously(const Request& request, bool measureTiming, + int64_t deadlineNs, + int64_t loopTimeoutDurationNs, + ExecutionResult* executionResult) { + auto result = adapter::executeSynchronously(*kPreparedModel, request, measureTiming, deadlineNs, + loopTimeoutDurationNs); + if (!result.has_value()) { + const auto& [message, code, _] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + *executionResult = std::move(result).value(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus PreparedModel::executeFenced( + const Request& request, const std::vector& waitFor, + bool measureTiming, int64_t deadlineNs, int64_t loopTimeoutDurationNs, int64_t durationNs, + FencedExecutionResult* executionResult) { + auto result = adapter::executeFenced(*kPreparedModel, request, waitFor, measureTiming, + deadlineNs, loopTimeoutDurationNs, durationNs); + if (!result.has_value()) { + const auto& [message, code] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + *executionResult = std::move(result).value(); + return ndk::ScopedAStatus::ok(); +} + +ndk::ScopedAStatus PreparedModel::configureExecutionBurst(std::shared_ptr* burst) { + auto result = kPreparedModel->configureExecutionBurst(); + if (!result.has_value()) { + const auto& [message, code] = result.error(); + const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE); + return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage( + static_cast(aidlCode), message.c_str()); + } + *burst = ndk::SharedRefBase::make(std::move(result).value()); + return ndk::ScopedAStatus::ok(); +} + +nn::SharedPreparedModel PreparedModel::getUnderlyingPreparedModel() const { + return kPreparedModel; +} + +} // namespace aidl::android::hardware::neuralnetworks::adapter diff --git a/neuralnetworks/utils/adapter/Android.bp b/neuralnetworks/utils/adapter/hidl/Android.bp similarity index 100% rename from neuralnetworks/utils/adapter/Android.bp rename to neuralnetworks/utils/adapter/hidl/Android.bp diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Adapter.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h similarity index 100% rename from neuralnetworks/utils/adapter/include/nnapi/hal/Adapter.h rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Buffer.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Buffer.h similarity index 100% rename from neuralnetworks/utils/adapter/include/nnapi/hal/Buffer.h rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Buffer.h diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Burst.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Burst.h similarity index 100% rename from neuralnetworks/utils/adapter/include/nnapi/hal/Burst.h rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Burst.h diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/Device.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Device.h similarity index 100% rename from neuralnetworks/utils/adapter/include/nnapi/hal/Device.h rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Device.h diff --git a/neuralnetworks/utils/adapter/include/nnapi/hal/PreparedModel.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h similarity index 100% rename from neuralnetworks/utils/adapter/include/nnapi/hal/PreparedModel.h rename to neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h diff --git a/neuralnetworks/utils/adapter/src/Adapter.cpp b/neuralnetworks/utils/adapter/hidl/src/Adapter.cpp similarity index 100% rename from neuralnetworks/utils/adapter/src/Adapter.cpp rename to neuralnetworks/utils/adapter/hidl/src/Adapter.cpp diff --git a/neuralnetworks/utils/adapter/src/Buffer.cpp b/neuralnetworks/utils/adapter/hidl/src/Buffer.cpp similarity index 100% rename from neuralnetworks/utils/adapter/src/Buffer.cpp rename to neuralnetworks/utils/adapter/hidl/src/Buffer.cpp diff --git a/neuralnetworks/utils/adapter/src/Burst.cpp b/neuralnetworks/utils/adapter/hidl/src/Burst.cpp similarity index 100% rename from neuralnetworks/utils/adapter/src/Burst.cpp rename to neuralnetworks/utils/adapter/hidl/src/Burst.cpp diff --git a/neuralnetworks/utils/adapter/src/Device.cpp b/neuralnetworks/utils/adapter/hidl/src/Device.cpp similarity index 100% rename from neuralnetworks/utils/adapter/src/Device.cpp rename to neuralnetworks/utils/adapter/hidl/src/Device.cpp diff --git a/neuralnetworks/utils/adapter/src/PreparedModel.cpp b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp similarity index 100% rename from neuralnetworks/utils/adapter/src/PreparedModel.cpp rename to neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp From 594cc78a7b5330210397c004d53e52db9148e297 Mon Sep 17 00:00:00 2001 From: Michael Butler Date: Tue, 11 Jan 2022 22:53:49 -0800 Subject: [PATCH 2/2] Remove uid from NN HIDL adapter Having the adapter retrieve the uid is redundant because the implementor is already able to get the uid directly themselves with IPCThreadState::self()->getCallingUid(). Bug: N/A Test: mma Change-Id: Ifeffea053cb92556be1aae8b17a94fafa1ac98e0 --- .../adapter/hidl/include/nnapi/hal/Adapter.h | 9 ++-- .../hidl/include/nnapi/hal/PreparedModel.h | 3 +- .../utils/adapter/hidl/src/Adapter.cpp | 3 +- .../utils/adapter/hidl/src/Device.cpp | 54 ++++++++----------- .../utils/adapter/hidl/src/PreparedModel.cpp | 27 +++++----- 5 files changed, 41 insertions(+), 55 deletions(-) diff --git a/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h index da00a090ed..6fba4abe7d 100644 --- a/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h +++ b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h @@ -20,7 +20,6 @@ #include #include #include -#include #include #include @@ -37,10 +36,12 @@ using Task = std::function; /** * A type-erased executor which executes a task asynchronously. * - * This executor is also provided with an Application ID (Android User ID) and an optional deadline - * for when the caller expects is the upper bound for the amount of time to complete the task. + * This executor is also provided an optional deadline for when the caller expects is the upper + * bound for the amount of time to complete the task. If needed, the Executor can retrieve the + * Application ID (Android User ID) by calling IPCThreadState::self()->getCallingUid() in + * hwbinder/IPCThreadState.h. */ -using Executor = std::function; +using Executor = std::function; /** * Adapt an NNAPI canonical interface object to a HIDL NN HAL interface object. diff --git a/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h index 65763b8d19..9482b0d512 100644 --- a/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h +++ b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h @@ -39,7 +39,7 @@ namespace android::hardware::neuralnetworks::adapter { // Class that adapts nn::IPreparedModel to V1_3::IPreparedModel. class PreparedModel final : public V1_3::IPreparedModel { public: - PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor, uid_t userId); + PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor); Return execute(const V1_0::Request& request, const sp& callback) override; @@ -71,7 +71,6 @@ class PreparedModel final : public V1_3::IPreparedModel { private: const nn::SharedPreparedModel kPreparedModel; const Executor kExecutor; - const uid_t kUserId; }; } // namespace android::hardware::neuralnetworks::adapter diff --git a/neuralnetworks/utils/adapter/hidl/src/Adapter.cpp b/neuralnetworks/utils/adapter/hidl/src/Adapter.cpp index d6f53f05a5..782e815a83 100644 --- a/neuralnetworks/utils/adapter/hidl/src/Adapter.cpp +++ b/neuralnetworks/utils/adapter/hidl/src/Adapter.cpp @@ -21,7 +21,6 @@ #include #include #include -#include #include #include @@ -37,7 +36,7 @@ sp adapt(nn::SharedDevice device, Executor executor) { } sp adapt(nn::SharedDevice device) { - Executor defaultExecutor = [](Task task, uid_t /*uid*/, nn::OptionalTimePoint /*deadline*/) { + Executor defaultExecutor = [](Task task, nn::OptionalTimePoint /*deadline*/) { std::thread(std::move(task)).detach(); }; return adapt(std::move(device), std::move(defaultExecutor)); diff --git a/neuralnetworks/utils/adapter/hidl/src/Device.cpp b/neuralnetworks/utils/adapter/hidl/src/Device.cpp index 96142c3577..4993a80a93 100644 --- a/neuralnetworks/utils/adapter/hidl/src/Device.cpp +++ b/neuralnetworks/utils/adapter/hidl/src/Device.cpp @@ -28,7 +28,6 @@ #include #include #include -#include #include #include #include @@ -43,7 +42,6 @@ #include #include #include -#include #include @@ -64,12 +62,11 @@ auto convertInput(const Type& object) -> decltype(nn::convert(std::declval using PrepareModelResult = nn::GeneralResult; -sp adaptPreparedModel(nn::SharedPreparedModel preparedModel, Executor executor, - uid_t userId) { +sp adaptPreparedModel(nn::SharedPreparedModel preparedModel, Executor executor) { if (preparedModel == nullptr) { return nullptr; } - return sp::make(std::move(preparedModel), std::move(executor), userId); + return sp::make(std::move(preparedModel), std::move(executor)); } void notify(V1_0::IPreparedModelCallback* callback, nn::ErrorStatus status, @@ -108,15 +105,14 @@ void notify(V1_3::IPreparedModelCallback* callback, nn::ErrorStatus status, } template -void notify(CallbackType* callback, PrepareModelResult result, Executor executor, uid_t userId) { +void notify(CallbackType* callback, PrepareModelResult result, Executor executor) { if (!result.has_value()) { const auto [message, status] = std::move(result).error(); LOG(ERROR) << message; notify(callback, status, nullptr); } else { auto preparedModel = std::move(result).value(); - auto hidlPreparedModel = - adaptPreparedModel(std::move(preparedModel), std::move(executor), userId); + auto hidlPreparedModel = adaptPreparedModel(std::move(preparedModel), std::move(executor)); notify(callback, nn::ErrorStatus::NONE, std::move(hidlPreparedModel)); } } @@ -137,13 +133,12 @@ nn::GeneralResult prepareModel(const nn::SharedDevice& device, const Execu auto nnModel = NN_TRY(convertInput(model)); - const uid_t userId = hardware::IPCThreadState::self()->getCallingUid(); - Task task = [device, nnModel = std::move(nnModel), userId, executor, callback] { + Task task = [device, nnModel = std::move(nnModel), executor, callback] { auto result = device->prepareModel(nnModel, nn::ExecutionPreference::DEFAULT, nn::Priority::DEFAULT, {}, {}, {}, {}); - notify(callback.get(), std::move(result), executor, userId); + notify(callback.get(), std::move(result), executor); }; - executor(std::move(task), userId, {}); + executor(std::move(task), {}); return {}; } @@ -159,13 +154,12 @@ nn::GeneralResult prepareModel_1_1(const nn::SharedDevice& device, const E auto nnModel = NN_TRY(convertInput(model)); const auto nnPreference = NN_TRY(convertInput(preference)); - const uid_t userId = hardware::IPCThreadState::self()->getCallingUid(); - Task task = [device, nnModel = std::move(nnModel), nnPreference, userId, executor, callback] { + Task task = [device, nnModel = std::move(nnModel), nnPreference, executor, callback] { auto result = device->prepareModel(nnModel, nnPreference, nn::Priority::DEFAULT, {}, {}, {}, {}); - notify(callback.get(), std::move(result), executor, userId); + notify(callback.get(), std::move(result), executor); }; - executor(std::move(task), userId, {}); + executor(std::move(task), {}); return {}; } @@ -187,15 +181,14 @@ nn::GeneralResult prepareModel_1_2(const nn::SharedDevice& device, const E auto nnDataCache = NN_TRY(convertInput(dataCache)); const auto nnToken = nn::CacheToken(token); - const uid_t userId = hardware::IPCThreadState::self()->getCallingUid(); Task task = [device, nnModel = std::move(nnModel), nnPreference, nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache), - nnToken, userId, executor, callback] { + nnToken, executor, callback] { auto result = device->prepareModel(nnModel, nnPreference, nn::Priority::DEFAULT, {}, nnModelCache, nnDataCache, nnToken); - notify(callback.get(), std::move(result), executor, userId); + notify(callback.get(), std::move(result), executor); }; - executor(std::move(task), userId, {}); + executor(std::move(task), {}); return {}; } @@ -218,15 +211,14 @@ nn::GeneralResult prepareModel_1_3( auto nnDataCache = NN_TRY(convertInput(dataCache)); const auto nnToken = nn::CacheToken(token); - const uid_t userId = hardware::IPCThreadState::self()->getCallingUid(); Task task = [device, nnModel = std::move(nnModel), nnPreference, nnPriority, nnDeadline, nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache), - nnToken, userId, executor, callback] { + nnToken, executor, callback] { auto result = device->prepareModel(nnModel, nnPreference, nnPriority, nnDeadline, nnModelCache, nnDataCache, nnToken); - notify(callback.get(), std::move(result), executor, userId); + notify(callback.get(), std::move(result), executor); }; - executor(std::move(task), userId, nnDeadline); + executor(std::move(task), nnDeadline); return {}; } @@ -245,13 +237,12 @@ nn::GeneralResult prepareModelFromCache(const nn::SharedDevice& device, auto nnDataCache = NN_TRY(convertInput(dataCache)); const auto nnToken = nn::CacheToken(token); - const uid_t userId = hardware::IPCThreadState::self()->getCallingUid(); Task task = [device, nnModelCache = std::move(nnModelCache), - nnDataCache = std::move(nnDataCache), nnToken, userId, executor, callback] { + nnDataCache = std::move(nnDataCache), nnToken, executor, callback] { auto result = device->prepareModelFromCache({}, nnModelCache, nnDataCache, nnToken); - notify(callback.get(), std::move(result), executor, userId); + notify(callback.get(), std::move(result), executor); }; - executor(std::move(task), userId, {}); + executor(std::move(task), {}); return {}; } @@ -270,13 +261,12 @@ nn::GeneralResult prepareModelFromCache_1_3( auto nnDataCache = NN_TRY(convertInput(dataCache)); const auto nnToken = nn::CacheToken(token); - const uid_t userId = hardware::IPCThreadState::self()->getCallingUid(); auto task = [device, nnDeadline, nnModelCache = std::move(nnModelCache), - nnDataCache = std::move(nnDataCache), nnToken, userId, executor, callback] { + nnDataCache = std::move(nnDataCache), nnToken, executor, callback] { auto result = device->prepareModelFromCache(nnDeadline, nnModelCache, nnDataCache, nnToken); - notify(callback.get(), std::move(result), executor, userId); + notify(callback.get(), std::move(result), executor); }; - executor(std::move(task), userId, nnDeadline); + executor(std::move(task), nnDeadline); return {}; } diff --git a/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp index a14e782b9b..71060d5ca7 100644 --- a/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp +++ b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp @@ -28,7 +28,6 @@ #include #include #include -#include #include #include #include @@ -37,7 +36,6 @@ #include #include #include -#include #include #include @@ -145,7 +143,7 @@ void notify(CallbackType* callback, ExecutionResult result) { } } -nn::GeneralResult execute(const nn::SharedPreparedModel& preparedModel, uid_t userId, +nn::GeneralResult execute(const nn::SharedPreparedModel& preparedModel, const Executor& executor, const V1_0::Request& request, const sp& callback) { if (callback.get() == nullptr) { @@ -164,12 +162,12 @@ nn::GeneralResult execute(const nn::SharedPreparedModel& preparedModel, ui auto result = preparedModel->execute(nnRequest, nn::MeasureTiming::NO, {}, {}); notify(callback.get(), std::move(result)); }; - executor(std::move(task), userId, {}); + executor(std::move(task), {}); return {}; } -nn::GeneralResult execute_1_2(const nn::SharedPreparedModel& preparedModel, uid_t userId, +nn::GeneralResult execute_1_2(const nn::SharedPreparedModel& preparedModel, const Executor& executor, const V1_0::Request& request, V1_2::MeasureTiming measure, const sp& callback) { @@ -190,12 +188,12 @@ nn::GeneralResult execute_1_2(const nn::SharedPreparedModel& preparedModel auto result = preparedModel->execute(nnRequest, nnMeasure, {}, {}); notify(callback.get(), std::move(result)); }; - executor(std::move(task), userId, {}); + executor(std::move(task), {}); return {}; } -nn::GeneralResult execute_1_3(const nn::SharedPreparedModel& preparedModel, uid_t userId, +nn::GeneralResult execute_1_3(const nn::SharedPreparedModel& preparedModel, const Executor& executor, const V1_3::Request& request, V1_2::MeasureTiming measure, const V1_3::OptionalTimePoint& deadline, @@ -222,7 +220,7 @@ nn::GeneralResult execute_1_3(const nn::SharedPreparedModel& preparedModel preparedModel->execute(nnRequest, nnMeasure, nnDeadline, nnLoopTimeoutDuration); notify(callback.get(), std::move(result)); }; - executor(std::move(task), userId, nnDeadline); + executor(std::move(task), nnDeadline); return {}; } @@ -305,8 +303,8 @@ nn::GeneralResult>> ex } // namespace -PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor, uid_t userId) - : kPreparedModel(std::move(preparedModel)), kExecutor(std::move(executor)), kUserId(userId) { +PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor) + : kPreparedModel(std::move(preparedModel)), kExecutor(std::move(executor)) { CHECK(kPreparedModel != nullptr); CHECK(kExecutor != nullptr); } @@ -317,7 +315,7 @@ nn::SharedPreparedModel PreparedModel::getUnderlyingPreparedModel() const { Return PreparedModel::execute(const V1_0::Request& request, const sp& callback) { - auto result = adapter::execute(kPreparedModel, kUserId, kExecutor, request, callback); + auto result = adapter::execute(kPreparedModel, kExecutor, request, callback); if (!result.has_value()) { auto [message, code] = std::move(result).error(); LOG(ERROR) << "adapter::PreparedModel::execute failed with " << code << ": " << message; @@ -330,8 +328,7 @@ Return PreparedModel::execute(const V1_0::Request& request, Return PreparedModel::execute_1_2(const V1_0::Request& request, V1_2::MeasureTiming measure, const sp& callback) { - auto result = - adapter::execute_1_2(kPreparedModel, kUserId, kExecutor, request, measure, callback); + auto result = adapter::execute_1_2(kPreparedModel, kExecutor, request, measure, callback); if (!result.has_value()) { auto [message, code] = std::move(result).error(); LOG(ERROR) << "adapter::PreparedModel::execute_1_2 failed with " << code << ": " << message; @@ -346,8 +343,8 @@ Return PreparedModel::execute_1_3( const V1_3::OptionalTimePoint& deadline, const V1_3::OptionalTimeoutDuration& loopTimeoutDuration, const sp& callback) { - auto result = adapter::execute_1_3(kPreparedModel, kUserId, kExecutor, request, measure, - deadline, loopTimeoutDuration, callback); + auto result = adapter::execute_1_3(kPreparedModel, kExecutor, request, measure, deadline, + loopTimeoutDuration, callback); if (!result.has_value()) { auto [message, code] = std::move(result).error(); LOG(ERROR) << "adapter::PreparedModel::execute_1_3 failed with " << code << ": " << message;