yolo_standard_libray/tensorrtx-master/swin-transformer/semantic-segmentation/layerNorm.h
2025-03-07 11:35:40 +08:00

131 lines
3.5 KiB
C++

#ifndef LAYERNORM_H
#define LAYERNORM_H
#include <vector>
#include <string>
#include <iostream>
#include <NvInfer.h>
#include <memory>
#include <string.h>
#include <cstdint>
#include <stdlib.h>
using namespace std;
struct welford
{
int count = 0;
double mean = 0.f;
double M2 = 0.f;
};
namespace nvinfer1{
class layernorm : public IPluginV2IOExt
{
public:
layernorm();
layernorm(const void* data, size_t length);
~layernorm();
int getNbOutputs() const override
{
return 2;
}
Dims getOutputDimensions(int index, const Dims* inputs, int nbInputDims) override;
int initialize() override;
virtual void terminate() override {};
virtual size_t getWorkspaceSize(int maxBatchSize) const override { return 0; }
virtual int enqueue(int batchSize, const void*const * inputs, void** outputs, void* workspace, cudaStream_t stream) override;
virtual size_t getSerializationSize() const override;
virtual void serialize(void* buffer) const override;
bool supportsFormatCombination(int pos, const PluginTensorDesc* inOut, int nbInputs, int nbOutputs) const override {
return inOut[pos].format == TensorFormat::kLINEAR && inOut[pos].type == DataType::kFLOAT;
}
void setPluginNamespace(const char* pluginNamespace) override;
const char* getPluginNamespace() const override;
const char* getPluginType() const override;
const char* getPluginVersion() const override;
void destroy() override;
IPluginV2IOExt* clone() const override;
DataType getOutputDataType(int index, const nvinfer1::DataType* inputTypes, int nbInputs) const override;
bool isOutputBroadcastAcrossBatch(int outputIndex, const bool* inputIsBroadcasted, int nbInputs) const override;
bool canBroadcastInputAcrossBatch(int inputIndex) const override;
void attachToContext(
cudnnContext* cudnnContext, cublasContext* cublasContext, IGpuAllocator* gpuAllocator) override;
void configurePlugin(const PluginTensorDesc* in, int nbInput, const PluginTensorDesc* out, int nbOutput) override;
void detachFromContext() override;
void setInputSize(int s, int l) {
mInputSize = s;
Length = l;
}
private:
void forwardGpu(const float *const * inputs, float *mean, float *std, cudaStream_t stream, int batchSize = 1);
int mThreadCount = 256;
int mInputSize;
int Length;
Dims outputDims ;
const char* mPluginNamespace;
};
class layernormCreator : public IPluginCreator
{
public:
layernormCreator();
~layernormCreator() override = default;
const char* getPluginName() const override;
const char* getPluginVersion() const override;
const PluginFieldCollection* getFieldNames() override;
IPluginV2IOExt* createPlugin(const char* name, const PluginFieldCollection* fc) override;
IPluginV2IOExt* deserializePlugin(const char* name, const void* serialData, size_t serialLength) override;
void setPluginNamespace(const char* libNamespace) override
{
mNamespace = libNamespace;
}
const char* getPluginNamespace() const override
{
return mNamespace.c_str();
}
private:
std::string mNamespace;
static PluginFieldCollection mFC;
static std::vector<PluginField> mPluginAttributes;
};
REGISTER_TENSORRT_PLUGIN(layernormCreator);
};
#endif // LAYERNORM_H