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/*
* 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 "Execution.h"
#include "Conversions.h"
#include "PreparedModel.h"
#include "Utils.h"
#include <aidl/android/hardware/neuralnetworks/Request.h>
#include <nnapi/IExecution.h>
#include <nnapi/Result.h>
#include <nnapi/Types.h>
#include <nnapi/hal/CommonUtils.h>
#include <memory>
#include <utility>
#include <vector>
// See hardware/interfaces/neuralnetworks/utils/README.md for more information on HIDL interface
// lifetimes across processes and for protecting asynchronous calls across HIDL.
namespace aidl::android::hardware::neuralnetworks::utils {
nn::GeneralResult<std::shared_ptr<const Execution>> Execution::create(
std::shared_ptr<const PreparedModel> preparedModel, Request request,
hal::utils::RequestRelocation relocation, bool measure, int64_t loopTimeoutDuration) {
if (preparedModel == nullptr) {
return NN_ERROR() << "aidl::utils::Execution::create must have non-null preparedModel";
}
return std::make_shared<const Execution>(PrivateConstructorTag{}, std::move(preparedModel),
std::move(request), std::move(relocation), measure,
loopTimeoutDuration);
}
Execution::Execution(PrivateConstructorTag /*tag*/,
std::shared_ptr<const PreparedModel> preparedModel, Request request,
hal::utils::RequestRelocation relocation, bool measure,
int64_t loopTimeoutDuration)
: kPreparedModel(std::move(preparedModel)),
kRequest(std::move(request)),
kRelocation(std::move(relocation)),
kMeasure(measure),
kLoopTimeoutDuration(loopTimeoutDuration) {}
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> Execution::compute(
const nn::OptionalTimePoint& deadline) const {
const auto aidlDeadline = NN_TRY(convert(deadline));
return kPreparedModel->executeInternal(kRequest, kMeasure, aidlDeadline, kLoopTimeoutDuration,
kRelocation);
}
nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> Execution::computeFenced(
const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
const nn::OptionalDuration& timeoutDurationAfterFence) const {
const auto aidlWaitFor = NN_TRY(convert(waitFor));
const auto aidlDeadline = NN_TRY(convert(deadline));
const auto aidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
return kPreparedModel->executeFencedInternal(kRequest, aidlWaitFor, kMeasure, aidlDeadline,
kLoopTimeoutDuration,
aidlTimeoutDurationAfterFence, kRelocation);
}
} // namespace aidl::android::hardware::neuralnetworks::utils
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