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neural_network_runtime/frameworks/native/ops/sub_builder.cpp
T
yangyongjie 7f4a0afc68 !1 Add Neural Network Runtime code
* add neural network runtime
2022-10-28 02:32:29 +00:00

132 lines
4.2 KiB
C++

/*
* Copyright (c) 2022 Huawei Device Co., Ltd.
* 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 "sub_builder.h"
#include "frameworks/native/transform.h"
#include "frameworks/native/validation.h"
namespace OHOS {
namespace NeuralNetworkRuntime {
namespace Ops {
static const int INPUT_NUM = 2;
static const int OUTPUT_NUM = 1;
static const std::string OP_NAME = "Sub";
SubBuilder::SubBuilder() {}
SubBuilder::~SubBuilder() {}
OH_NN_ReturnCode SubBuilder::SetActivationType(std::shared_ptr<NNTensor> tensor)
{
if (tensor->GetDataType() != OH_NN_INT8) {
LOGE("[SubBuilder] The 3rd input activation should be type OH_NN_INT8.");
return OH_NN_INVALID_PARAMETER;
}
if (tensor->GetElementCount() != 1) {
LOGE("[SubBuilder] The 3rd input activation should be scaler.");
return OH_NN_INVALID_PARAMETER;
}
void* buffer = tensor->GetBuffer();
if (buffer == nullptr) {
LOGE("[SubBuilder] Tensor buffer is nullptr.");
return OH_NN_INVALID_PARAMETER;
}
int8_t* fuseData = static_cast<int8_t*>(buffer);
if (!OHOS::NeuralNetworkRuntime::Validation::ValidateFuseType(static_cast<OH_NN_FuseType>(*fuseData))) {
LOGE("[SubBuilder] Fuse activation type is invalid");
return OH_NN_INVALID_PARAMETER;
}
auto fuseType = (OH_NN_FuseType)(*fuseData);
m_activationType = NNToMS::TransfromFusionType(fuseType);
return OH_NN_SUCCESS;
}
/**
* Build method.
* 1.set attr of ops.
* 2.set inputIndex of ops.
* 3.set outputIndex of ops.
*/
OH_NN_ReturnCode SubBuilder::Build(const std::vector<uint32_t>& paramsIndex,
const std::vector<uint32_t>& inputsIndex,
const std::vector<uint32_t>& outputsIndex,
const std::vector<std::shared_ptr<NNTensor>>& allTensors)
{
if (m_isBuild) {
LOGE("[SubBuilder] Sub operation has been build, cannot build again.");
return OH_NN_OPERATION_FORBIDDEN;
}
OH_NN_ReturnCode returnCode = CheckIOIndex(inputsIndex, outputsIndex, allTensors, INPUT_NUM, OUTPUT_NUM);
if (returnCode != OH_NN_SUCCESS) {
LOGE("[SubBuilder] Passed invalid input or output index.");
return returnCode;
}
m_inputsIndex = inputsIndex;
m_outputsIndex = outputsIndex;
for (int i : paramsIndex) {
std::shared_ptr<NNTensor> tensor = allTensors[i];
tensor->IdentifyOpParameter();
switch (tensor->GetType()) {
case OH_NN_SUB_ACTIVATIONTYPE:
returnCode = SetActivationType(tensor);
break;
default:
LOGE("[SubBuilder] Parameter Type is invalid. type=%d", tensor->GetType());
return OH_NN_INVALID_PARAMETER;
}
if (returnCode != OH_NN_SUCCESS) {
LOGE("[SubBuilder] Passed invalid param.");
return returnCode;
}
}
// The quantization type of the first output determinies that of the operator.
SetQuantType(outputsIndex, allTensors);
m_isBuild = true;
m_name = "Sub";
return OH_NN_SUCCESS;
}
LiteGraphPrimitvePtr SubBuilder::GetPrimitive()
{
if (!m_isBuild) {
LOGE("[SubBuilder] Cannot get primitive before call build.");
return {nullptr, DestroyLiteGraphPrimitive};
}
auto primitive = mindspore::lite::MindIR_SubFusion_CreatePrimitive(m_activationType);
if (primitive == nullptr) {
LOGE("[SubBuilder] MindIR_SubFusion_CreatePrimitive failed.");
return {nullptr, DestroyLiteGraphPrimitive};
}
LiteGraphPrimitvePtr graphPrimitivePtr(primitive, DestroyLiteGraphPrimitive);
return graphPrimitivePtr;
}
REGISTER_OPS(SubBuilder, OH_NN_OPS_SUB);
} // namespace Ops
} // namespace NeuralNetworkRuntime
} // namespace OHOS