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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 "Callbacks.h"
#include "Conversions.h"
#include "PreparedModel.h"
#include "Utils.h"
#include <android/hardware/neuralnetworks/1.0/types.h>
#include <android/hardware/neuralnetworks/1.2/types.h>
#include <android/hardware/neuralnetworks/1.3/IExecutionCallback.h>
#include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h>
#include <android/hardware/neuralnetworks/1.3/types.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/Result.h>
#include <nnapi/Types.h>
#include <nnapi/hal/1.0/Callbacks.h>
#include <nnapi/hal/1.0/Conversions.h>
#include <nnapi/hal/1.0/HandleError.h>
#include <nnapi/hal/1.0/PreparedModel.h>
#include <nnapi/hal/1.0/ProtectCallback.h>
#include <nnapi/hal/1.2/Callbacks.h>
#include <nnapi/hal/1.2/Conversions.h>
#include <nnapi/hal/1.2/PreparedModel.h>
#include <nnapi/hal/CommonUtils.h>
#include <nnapi/hal/TransferValue.h>
#include <utility>
// See hardware/interfaces/neuralnetworks/utils/README.md for more information on HIDL interface
// lifetimes across processes and for protecting asynchronous calls across HIDL.
namespace android::hardware::neuralnetworks::V1_3::utils {
namespace {
nn::GeneralResult<nn::SharedPreparedModel> prepareModelCallback(
V1_0::ErrorStatus status, const sp<V1_0::IPreparedModel>& preparedModel) {
if (const auto dynamicPreparedModel =
V1_3::IPreparedModel::castFrom(preparedModel).withDefault(nullptr)) {
const auto currentVersionStatus = NN_TRY(convertFromNonCanonical(status));
return V1_3::utils::prepareModelCallback(currentVersionStatus, dynamicPreparedModel);
}
if (const auto dynamicPreparedModel =
V1_2::IPreparedModel::castFrom(preparedModel).withDefault(nullptr)) {
return V1_2::utils::prepareModelCallback(status, dynamicPreparedModel);
}
return V1_0::utils::prepareModelCallback(status, preparedModel);
}
nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
convertExecutionGeneralResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
const V1_2::Timing& timing) {
return std::make_pair(NN_TRY(nn::convert(outputShapes)), NN_TRY(nn::convert(timing)));
}
} // namespace
nn::GeneralResult<std::vector<bool>> supportedOperationsCallback(
ErrorStatus status, const hidl_vec<bool>& supportedOperations) {
HANDLE_STATUS_HIDL(status) << "get supported operations failed with " << toString(status);
return supportedOperations;
}
nn::GeneralResult<nn::SharedPreparedModel> prepareModelCallback(
ErrorStatus status, const sp<IPreparedModel>& preparedModel) {
HANDLE_STATUS_HIDL(status) << "model preparation failed with " << toString(status);
return NN_TRY(PreparedModel::create(preparedModel, /*executeSynchronously=*/true));
}
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executionCallback(
ErrorStatus status, const hidl_vec<V1_2::OutputShape>& outputShapes,
const V1_2::Timing& timing) {
if (status == ErrorStatus::OUTPUT_INSUFFICIENT_SIZE) {
auto canonicalOutputShapes =
nn::convert(outputShapes).value_or(std::vector<nn::OutputShape>{});
return NN_ERROR(nn::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, std::move(canonicalOutputShapes))
<< "execution failed with " << toString(status);
}
HANDLE_STATUS_HIDL(status) << "execution failed with " << toString(status);
return convertExecutionGeneralResultsHelper(outputShapes, timing);
}
Return<void> PreparedModelCallback::notify(V1_0::ErrorStatus status,
const sp<V1_0::IPreparedModel>& preparedModel) {
mData.put(prepareModelCallback(status, preparedModel));
return Void();
}
Return<void> PreparedModelCallback::notify_1_2(V1_0::ErrorStatus status,
const sp<V1_2::IPreparedModel>& preparedModel) {
mData.put(prepareModelCallback(status, preparedModel));
return Void();
}
Return<void> PreparedModelCallback::notify_1_3(ErrorStatus status,
const sp<IPreparedModel>& preparedModel) {
mData.put(prepareModelCallback(status, preparedModel));
return Void();
}
void PreparedModelCallback::notifyAsDeadObject() {
mData.put(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
}
PreparedModelCallback::Data PreparedModelCallback::get() {
return mData.take();
}
// ExecutionCallback methods begin here
Return<void> ExecutionCallback::notify(V1_0::ErrorStatus status) {
mData.put(V1_0::utils::executionCallback(status));
return Void();
}
Return<void> ExecutionCallback::notify_1_2(V1_0::ErrorStatus status,
const hidl_vec<V1_2::OutputShape>& outputShapes,
const V1_2::Timing& timing) {
mData.put(V1_2::utils::executionCallback(status, outputShapes, timing));
return Void();
}
Return<void> ExecutionCallback::notify_1_3(ErrorStatus status,
const hidl_vec<V1_2::OutputShape>& outputShapes,
const V1_2::Timing& timing) {
mData.put(executionCallback(status, outputShapes, timing));
return Void();
}
void ExecutionCallback::notifyAsDeadObject() {
mData.put(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
}
ExecutionCallback::Data ExecutionCallback::get() {
return mData.take();
}
} // namespace android::hardware::neuralnetworks::V1_3::utils
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