MNN/source/backend/tensorrt/execution/TRTLayerNorm.cpp

75 lines
2.2 KiB
C++
Executable File

//
// TRTLayerNorm.cpp
// MNN
//
// Created by MNN on 2021/02/08.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "TRTLayerNorm.hpp"
#include <core/TensorUtils.hpp>
#include "TRTBackend.hpp"
#include "schema/current/MNNPlugin_generated.h"
using namespace std;
namespace MNN {
TRTLayerNorm::TRTLayerNorm(Backend *b, const Op *op, const std::vector<Tensor *> &inputs,
const std::vector<Tensor *> &outputs)
: MNN::TRTCommonExecution(b, op) {
}
std::vector<ITensor *> TRTLayerNorm::onEncode(const std::vector<ITensor *> &xOp) {
#ifdef TRT_LOG
printf("TRTLayerNorm in\n");
#endif
auto plu = createPluginWithOutput(mOutputs);
const auto* layer_norm_param = mOp->main_as_LayerNorm();
int axis_size = layer_norm_param->axis()->size();
std::vector<int> axis_;
axis_.resize(axis_size);
for (int i = 0; i < axis_size; ++i) {
axis_[i] = layer_norm_param->axis()->Get(i);
}
int outter_size_ = 1;
int inner_size_ = 1;
int rank = mInputs[0]->dimensions();
std::vector<int> axis(axis_.size());
for (int i = 0; i < axis_.size(); ++i) {
if (axis_[i] < 0) {
axis[i] += rank;
}
}
std::sort(axis.begin(), axis.end());
for (int i = 0; i < rank - axis.size(); ++i) {
outter_size_ *= mInputs[0]->length(i);
}
for (int i = rank - axis.size(); i < rank; ++i) {
inner_size_ *= mInputs[0]->length(i);
}
plu->main.type = MNNTRTPlugin::Parameter_OneHotInfo;
plu->main.value = new MNNTRTPlugin::OneHotInfoT;
auto onehotp = plu->main.AsOneHotInfo();
onehotp->outerSize = outter_size_;
onehotp->innerSize = inner_size_;
auto interpPlugin = (nvinfer1::IPluginExt *)MNNTRTCreatePlugion(mOp, plu.get());
nvinfer1::IPluginLayer *plugin = mTrtBackend->getNetwork()->addPluginExt(&xOp[0], mInputs.size(), *((nvinfer1::IPluginExt *)interpPlugin));
if (plugin == nullptr) {
printf("Interp plugin == nullptr !!!\n");
}
mTrtBackend->pushReleaseLayer(interpPlugin);
return {plugin->getOutput(0)};
}
TRTCreatorRegister<TypedCreator<TRTLayerNorm>> __layer_norm_op(OpType_LayerNorm);
} // namespace MNN