mirror of
https://github.com/openharmony/neural_network_runtime.git
synced 2026-07-20 04:23:56 -04:00
7f4a0afc68
* add neural network runtime
132 lines
4.2 KiB
C++
132 lines
4.2 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 "sub_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 = "Sub";
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SubBuilder::SubBuilder() {}
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SubBuilder::~SubBuilder() {}
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OH_NN_ReturnCode SubBuilder::SetActivationType(std::shared_ptr<NNTensor> tensor)
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{
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if (tensor->GetDataType() != OH_NN_INT8) {
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LOGE("[SubBuilder] The 3rd input activation should be type OH_NN_INT8.");
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return OH_NN_INVALID_PARAMETER;
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}
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if (tensor->GetElementCount() != 1) {
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LOGE("[SubBuilder] The 3rd input activation should be scaler.");
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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("[SubBuilder] Tensor buffer is 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 (!OHOS::NeuralNetworkRuntime::Validation::ValidateFuseType(static_cast<OH_NN_FuseType>(*fuseData))) {
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LOGE("[SubBuilder] Fuse activation type is invalid");
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return OH_NN_INVALID_PARAMETER;
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}
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auto fuseType = (OH_NN_FuseType)(*fuseData);
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m_activationType = NNToMS::TransfromFusionType(fuseType);
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return OH_NN_SUCCESS;
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}
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/**
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* Build method.
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* 1.set attr of ops.
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* 2.set inputIndex of ops.
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* 3.set outputIndex of ops.
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*/
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OH_NN_ReturnCode SubBuilder::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("[SubBuilder] Sub operation has been build, cannot build again.");
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return OH_NN_OPERATION_FORBIDDEN;
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}
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OH_NN_ReturnCode returnCode = CheckIOIndex(inputsIndex, outputsIndex, allTensors, INPUT_NUM, OUTPUT_NUM);
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if (returnCode != OH_NN_SUCCESS) {
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LOGE("[SubBuilder] Passed invalid input or output index.");
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return returnCode;
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}
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m_inputsIndex = inputsIndex;
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m_outputsIndex = outputsIndex;
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for (int i : paramsIndex) {
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std::shared_ptr<NNTensor> tensor = allTensors[i];
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tensor->IdentifyOpParameter();
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switch (tensor->GetType()) {
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case OH_NN_SUB_ACTIVATIONTYPE:
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returnCode = SetActivationType(tensor);
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break;
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default:
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LOGE("[SubBuilder] Parameter Type is invalid. type=%d", tensor->GetType());
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return OH_NN_INVALID_PARAMETER;
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}
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if (returnCode != OH_NN_SUCCESS) {
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LOGE("[SubBuilder] Passed invalid param.");
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return returnCode;
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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_isBuild = true;
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m_name = "Sub";
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return OH_NN_SUCCESS;
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}
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LiteGraphPrimitvePtr SubBuilder::GetPrimitive()
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{
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if (!m_isBuild) {
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LOGE("[SubBuilder] Cannot get primitive before call build.");
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return {nullptr, DestroyLiteGraphPrimitive};
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}
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auto primitive = mindspore::lite::MindIR_SubFusion_CreatePrimitive(m_activationType);
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if (primitive == nullptr) {
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LOGE("[SubBuilder] MindIR_SubFusion_CreatePrimitive failed.");
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return {nullptr, DestroyLiteGraphPrimitive};
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}
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LiteGraphPrimitvePtr graphPrimitivePtr(primitive, DestroyLiteGraphPrimitive);
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return graphPrimitivePtr;
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}
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REGISTER_OPS(SubBuilder, OH_NN_OPS_SUB);
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} // namespace Ops
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} // namespace NeuralNetworkRuntime
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} // namespace OHOS
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