wehub-resource-sync
55 lines
1.7 KiB
C++
55 lines
1.7 KiB
C++
//
|
|
// QNNPadding.cpp
|
|
// MNN
|
|
//
|
|
// Created by MNN on b'2025/04/10'.
|
|
// Copyright © 2018, Alibaba Group Holding Limited
|
|
//
|
|
|
|
#include "QNNPadding.hpp"
|
|
|
|
namespace MNN {
|
|
namespace QNN {
|
|
#ifdef ENABLE_QNN_ONLINE_FINALIZE
|
|
|
|
ErrorCode QNNPadding::onEncode(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
|
|
MNN_ASSERT(inputs.size() == 2);
|
|
|
|
mNodeType = "Pad";
|
|
|
|
auto input = inputs[0];
|
|
auto padding = inputs[1];
|
|
auto output = outputs[0];
|
|
int * paddingDataSrc = padding->host<int>();
|
|
|
|
auto size = padding->elementSize();
|
|
auto dimensions = input->dimensions();
|
|
MNN_ASSERT(size == (2 * dimensions));
|
|
|
|
this->createParamScalar("scheme", (uint32_t) 0); // 0 means 'CONSTANT'
|
|
mParams.push_back(*(mParamScalarWrappers.back()->getNativeParam()));
|
|
|
|
this->createParamTensor("pad_amount", QNN_DATATYPE_UINT_32, {(uint32_t)dimensions, 2}, (void *) paddingDataSrc);
|
|
mParams.push_back(*(mParamTensorWrappers.back()->getNativeParam()));
|
|
|
|
mInputs.push_back(*(mBackend->getNativeTensor(inputs[0])));
|
|
mOutputs.push_back(*(mBackend->getNativeTensor(outputs[0])));
|
|
mBackend->addNodeToGraph(mOpConfigVersion, mNodeName.c_str(), mPackageName.c_str(), mNodeType.c_str(), mParams, mInputs, mOutputs);
|
|
|
|
return NO_ERROR;
|
|
}
|
|
|
|
|
|
class QNNPaddingCreator : public QnnBackend::Creator {
|
|
public:
|
|
virtual QNNCommonExecution * onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs, const MNN::Op* op,
|
|
Backend* backend) const override {
|
|
return new QNNPadding(backend, op);
|
|
}
|
|
};
|
|
|
|
REGISTER_QNN_OP_CREATOR(QNNPaddingCreator, OpType_Padding)
|
|
#endif
|
|
} // end namespace QNN
|
|
} // end namespace MNN
|