mirror of
https://github.com/openharmony/neural_network_runtime.git
synced 2026-07-01 08:12:02 -04:00
yangyongjie
116 lines
3.8 KiB
C++
116 lines
3.8 KiB
C++
/*
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* Copyright (c) 2022 Huawei Device Co., Ltd.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "add_builder.h"
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#include "frameworks/native/transform.h"
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#include "frameworks/native/validation.h"
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namespace OHOS {
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namespace NeuralNetworkRuntime {
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namespace Ops {
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static const int INPUT_NUM = 2;
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static const int OUTPUT_NUM = 1;
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static const std::string OP_NAME = "Add";
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AddBuilder::AddBuilder() {}
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AddBuilder::~AddBuilder() {}
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OH_NN_ReturnCode AddBuilder::SetActivation(std::shared_ptr<NNTensor>& tensor)
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{
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tensor->IdentifyOpParameter();
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if (tensor->GetDataType() != OH_NN_INT8) {
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LOGE("[Add] SetActivation failed, the activationType should be type OH_NN_INT8.");
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return OH_NN_INVALID_PARAMETER;
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}
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void* buffer = tensor->GetBuffer();
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if (buffer == nullptr) {
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LOGE("[Add] SetActivation GetBuffer return nullptr.");
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return OH_NN_INVALID_PARAMETER;
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}
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int8_t* fuseData = static_cast<int8_t*>(buffer);
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if (!Validation::ValidateFuseType(static_cast<OH_NN_FuseType>(*fuseData))) {
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LOGE("[Add] SetActivation failed, fuse activation type is invalid.");
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return OH_NN_INVALID_PARAMETER;
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}
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m_activationType = NNToMS::TransfromFusionType(static_cast<OH_NN_FuseType>(*fuseData));
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return OH_NN_SUCCESS;
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}
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OH_NN_ReturnCode AddBuilder::Build(const std::vector<uint32_t>& paramsIndex,
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const std::vector<uint32_t>& inputsIndex,
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const std::vector<uint32_t>& outputsIndex,
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const std::vector<std::shared_ptr<NNTensor>>& allTensors)
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{
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if (m_isBuild) {
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LOGE("[Add] Build failed, operation has been build, cannot build again.");
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return OH_NN_OPERATION_FORBIDDEN;
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}
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auto ret = CheckIOIndex(inputsIndex, outputsIndex, allTensors, INPUT_NUM, OUTPUT_NUM);
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if (ret != OH_NN_SUCCESS) {
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LOGE("[Add] Build failed, the input or output index of Add operation is invalid.");
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return ret;
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}
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m_inputsIndex = inputsIndex;
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m_outputsIndex = outputsIndex;
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for (uint32_t i : paramsIndex) {
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std::shared_ptr<NNTensor> tensor = allTensors[i];
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switch (tensor->GetType()) {
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case OH_NN_ADD_ACTIVATIONTYPE:
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ret = SetActivation(tensor);
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break;
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default:
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LOGE("[Add] Build failed, param invalid, type = %d.", tensor->GetType());
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return OH_NN_INVALID_PARAMETER;
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}
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if (ret != OH_NN_SUCCESS) {
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LOGE("[Add] Build failed, passed invalid param.");
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return ret;
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}
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}
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// The quantization type of the first output determinies that of the operator.
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SetQuantType(outputsIndex, allTensors);
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m_name = OP_NAME;
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m_isBuild = true;
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return OH_NN_SUCCESS;
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}
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LiteGraphPrimitvePtr AddBuilder::GetPrimitive()
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{
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if (!m_isBuild) {
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LOGE("[Add] GetPrimitive failed, cannot get primitive before call build.");
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return {nullptr, DestroyLiteGraphPrimitive};
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}
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void* primitive = mindspore::lite::MindIR_AddFusion_CreatePrimitive(m_activationType);
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LiteGraphPrimitvePtr graphPrimitivePtr(primitive, DestroyLiteGraphPrimitive) ;
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return graphPrimitivePtr;
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}
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REGISTER_OPS(AddBuilder, OH_NN_OPS_ADD);
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} // namespace Ops
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} // namespace NeuralNetworkRuntime
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} // namespace OHOS
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