| /* |
| * 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 "ResilientPreparedModel.h" |
| |
| #include <android-base/logging.h> |
| #include <android-base/thread_annotations.h> |
| #include <nnapi/IPreparedModel.h> |
| #include <nnapi/Result.h> |
| #include <nnapi/TypeUtils.h> |
| #include <nnapi/Types.h> |
| |
| #include <functional> |
| #include <memory> |
| #include <mutex> |
| #include <sstream> |
| #include <utility> |
| #include <vector> |
| |
| namespace android::hardware::neuralnetworks::utils { |
| namespace { |
| |
| template <typename FnType> |
| auto protect(const ResilientPreparedModel& resilientPreparedModel, const FnType& fn) |
| -> decltype(fn(*resilientPreparedModel.getPreparedModel())) { |
| auto preparedModel = resilientPreparedModel.getPreparedModel(); |
| auto result = fn(*preparedModel); |
| |
| // Immediately return if prepared model is not dead. |
| if (result.has_value() || result.error().code != nn::ErrorStatus::DEAD_OBJECT) { |
| return result; |
| } |
| |
| // Attempt recovery and return if it fails. |
| auto maybePreparedModel = resilientPreparedModel.recover(preparedModel.get()); |
| if (!maybePreparedModel.has_value()) { |
| const auto& [message, code] = maybePreparedModel.error(); |
| std::ostringstream oss; |
| oss << ", and failed to recover dead prepared model with error " << code << ": " << message; |
| result.error().message += oss.str(); |
| return result; |
| } |
| preparedModel = std::move(maybePreparedModel).value(); |
| |
| return fn(*preparedModel); |
| } |
| |
| } // namespace |
| |
| nn::GeneralResult<std::shared_ptr<const ResilientPreparedModel>> ResilientPreparedModel::create( |
| Factory makePreparedModel) { |
| if (makePreparedModel == nullptr) { |
| return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) |
| << "utils::ResilientPreparedModel::create must have non-empty makePreparedModel"; |
| } |
| auto preparedModel = NN_TRY(makePreparedModel()); |
| CHECK(preparedModel != nullptr); |
| return std::make_shared<ResilientPreparedModel>( |
| PrivateConstructorTag{}, std::move(makePreparedModel), std::move(preparedModel)); |
| } |
| |
| ResilientPreparedModel::ResilientPreparedModel(PrivateConstructorTag /*tag*/, |
| Factory makePreparedModel, |
| nn::SharedPreparedModel preparedModel) |
| : kMakePreparedModel(std::move(makePreparedModel)), mPreparedModel(std::move(preparedModel)) { |
| CHECK(kMakePreparedModel != nullptr); |
| CHECK(mPreparedModel != nullptr); |
| } |
| |
| nn::SharedPreparedModel ResilientPreparedModel::getPreparedModel() const { |
| std::lock_guard guard(mMutex); |
| return mPreparedModel; |
| } |
| |
| nn::GeneralResult<nn::SharedPreparedModel> ResilientPreparedModel::recover( |
| const nn::IPreparedModel* failingPreparedModel) const { |
| std::lock_guard guard(mMutex); |
| |
| // Another caller updated the failing prepared model. |
| if (mPreparedModel.get() != failingPreparedModel) { |
| return mPreparedModel; |
| } |
| |
| mPreparedModel = NN_TRY(kMakePreparedModel()); |
| return mPreparedModel; |
| } |
| |
| nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> |
| ResilientPreparedModel::execute(const nn::Request& request, nn::MeasureTiming measure, |
| const nn::OptionalTimePoint& deadline, |
| const nn::OptionalDuration& loopTimeoutDuration) const { |
| const auto fn = [&request, measure, &deadline, |
| &loopTimeoutDuration](const nn::IPreparedModel& preparedModel) { |
| return preparedModel.execute(request, measure, deadline, loopTimeoutDuration); |
| }; |
| return protect(*this, fn); |
| } |
| |
| nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> |
| ResilientPreparedModel::executeFenced(const nn::Request& request, |
| const std::vector<nn::SyncFence>& waitFor, |
| nn::MeasureTiming measure, |
| const nn::OptionalTimePoint& deadline, |
| const nn::OptionalDuration& loopTimeoutDuration, |
| const nn::OptionalDuration& timeoutDurationAfterFence) const { |
| const auto fn = [&request, &waitFor, measure, &deadline, &loopTimeoutDuration, |
| &timeoutDurationAfterFence](const nn::IPreparedModel& preparedModel) { |
| return preparedModel.executeFenced(request, waitFor, measure, deadline, loopTimeoutDuration, |
| timeoutDurationAfterFence); |
| }; |
| return protect(*this, fn); |
| } |
| |
| std::any ResilientPreparedModel::getUnderlyingResource() const { |
| return getPreparedModel()->getUnderlyingResource(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::utils |