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/*
* Copyright (C) 2020 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "PreparedModel.h"
#include "Callbacks.h"
#include "Conversions.h"
#include "Utils.h"
#include <android/hardware/neuralnetworks/1.0/types.h>
#include <android/hardware/neuralnetworks/1.1/types.h>
#include <android/hardware/neuralnetworks/1.2/IPreparedModel.h>
#include <android/hardware/neuralnetworks/1.2/types.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/Result.h>
#include <nnapi/Types.h>
#include <nnapi/hal/1.0/Conversions.h>
#include <nnapi/hal/CommonUtils.h>
#include <nnapi/hal/HandleError.h>
#include <nnapi/hal/ProtectCallback.h>
#include <memory>
#include <tuple>
#include <utility>
#include <vector>
namespace android::hardware::neuralnetworks::V1_2::utils {
namespace {
nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
convertExecutionResultsHelper(const hidl_vec<OutputShape>& outputShapes, const Timing& timing) {
return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
NN_TRY(validatedConvertToCanonical(timing)));
}
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> convertExecutionResults(
const hidl_vec<OutputShape>& outputShapes, const Timing& timing) {
return hal::utils::makeExecutionFailure(convertExecutionResultsHelper(outputShapes, timing));
}
} // namespace
nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
sp<V1_2::IPreparedModel> preparedModel) {
if (preparedModel == nullptr) {
return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
<< "V1_2::utils::PreparedModel::create must have non-null preparedModel";
}
auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(preparedModel));
return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel),
std::move(deathHandler));
}
PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/, sp<V1_2::IPreparedModel> preparedModel,
hal::utils::DeathHandler deathHandler)
: kPreparedModel(std::move(preparedModel)), kDeathHandler(std::move(deathHandler)) {}
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
PreparedModel::executeSynchronously(const V1_0::Request& request, MeasureTiming measure) const {
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
const auto cb = [&result](V1_0::ErrorStatus status, const hidl_vec<OutputShape>& outputShapes,
const Timing& timing) {
if (status != V1_0::ErrorStatus::NONE) {
const auto canonical =
validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
result = NN_ERROR(canonical) << "executeSynchronously failed with " << toString(status);
} else {
result = convertExecutionResults(outputShapes, timing);
}
};
const auto ret = kPreparedModel->executeSynchronously(request, measure, cb);
NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
return result;
}
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
PreparedModel::executeAsynchronously(const V1_0::Request& request, MeasureTiming measure) const {
const auto cb = sp<ExecutionCallback>::make();
const auto scoped = kDeathHandler.protectCallback(cb.get());
const auto ret = kPreparedModel->execute_1_2(request, measure, cb);
const auto status =
NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
if (status != V1_0::ErrorStatus::NONE) {
const auto canonical =
validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
return NN_ERROR(canonical) << "execute failed with " << toString(status);
}
return cb->get();
}
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
const nn::Request& request, nn::MeasureTiming measure,
const nn::OptionalTimePoint& /*deadline*/,
const nn::OptionalTimeoutDuration& /*loopTimeoutDuration*/) const {
// Ensure that request is ready for IPC.
std::optional<nn::Request> maybeRequestInShared;
const nn::Request& requestInShared = NN_TRY(hal::utils::makeExecutionFailure(
hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared)));
const auto hidlRequest =
NN_TRY(hal::utils::makeExecutionFailure(V1_0::utils::convert(requestInShared)));
const auto hidlMeasure = NN_TRY(hal::utils::makeExecutionFailure(convert(measure)));
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
const bool preferSynchronous = true;
// Execute synchronously if allowed.
if (preferSynchronous) {
result = executeSynchronously(hidlRequest, hidlMeasure);
}
// Run asymchronous execution if execution has not already completed.
if (!result.has_value()) {
result = executeAsynchronously(hidlRequest, hidlMeasure);
}
// Flush output buffers if suxcessful execution.
if (result.has_value()) {
NN_TRY(hal::utils::makeExecutionFailure(
hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
}
return result;
}
nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
PreparedModel::executeFenced(
const nn::Request& /*request*/, const std::vector<nn::SyncFence>& /*waitFor*/,
nn::MeasureTiming /*measure*/, const nn::OptionalTimePoint& /*deadline*/,
const nn::OptionalTimeoutDuration& /*loopTimeoutDuration*/,
const nn::OptionalTimeoutDuration& /*timeoutDurationAfterFence*/) const {
return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "IPreparedModel::executeFenced is not supported on 1.2 HAL service";
}
std::any PreparedModel::getUnderlyingResource() const {
sp<V1_0::IPreparedModel> resource = kPreparedModel;
return resource;
}
} // namespace android::hardware::neuralnetworks::V1_2::utils