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