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前言

caffeParser.h中宣告了CaffeParser這個類別。其具體實作則位於 caffeParser.cpp。

因為caffeParser.cpp內容較多，它的介紹共分為：

TensorRT/parsers/caffe/caffeParser/caffeParser.h

/* * Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved. * * 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. */#ifndef TRT_CAFFE_PARSER_CAFFE_PARSER_H#define TRT_CAFFE_PARSER_CAFFE_PARSER_H#include 
   
    #include 
    
     #include 
     
      #include 
      
       #include "NvCaffeParser.h"#include "caffeWeightFactory.h"#include "blobNameToTensor.h"#include "trtcaffe.pb.h"namespace nvcaffeparser1{   //繼承自TensorRT/include/NvCaffeParser.h裡的抽象類別ICaffeParser//ICafferParser裡宣告的都是virtual function，在這個ICafferParser的子類別中會賦予它們具體的定義class CaffeParser : public ICaffeParser{   public:    const IBlobNameToTensor* parse(const char* deploy,                                   const char* model,                                   nvinfer1::INetworkDefinition& network,                                   nvinfer1::DataType weightType) override;    const IBlobNameToTensor* parseBuffers(const char* deployBuffer,                                          size_t deployLength,                                          const char* modelBuffer,                                          size_t modelLength,                                          nvinfer1::INetworkDefinition& network,                                          nvinfer1::DataType weightType) override;    void setProtobufBufferSize(size_t size) override {    mProtobufBufferSize = size; }    void setPluginFactory(nvcaffeparser1::IPluginFactory* factory) override {    mPluginFactory = factory; }    void setPluginFactoryExt(nvcaffeparser1::IPluginFactoryExt* factory) override    {           mPluginFactory = factory;        mPluginFactoryIsExt = true;    }    void setPluginFactoryV2(nvcaffeparser1::IPluginFactoryV2* factory) override {    mPluginFactoryV2 = factory; }    void setPluginNamespace(const char* libNamespace) override {    mPluginNamespace = libNamespace; }    IBinaryProtoBlob* parseBinaryProto(const char* fileName) override;    void destroy() override {    delete this; }    //以下二函數override ICaffeParser中的函數，但未實做    //(void)recorder的作用是？    void setErrorRecorder(nvinfer1::IErrorRecorder* recorder) override {    (void)recorder; assert(!"TRT- Not implemented."); }    nvinfer1::IErrorRecorder* getErrorRecorder() const override {    assert(!"TRT- Not implemented."); return nullptr; }private:    ~CaffeParser() override;    /*    以下五個函數的作用都是將trtcaffe::LayerParameter裡的資料    整理成std::vector
       
        的格式後回傳    */    std::vector
        
          parseNormalizeParam(const trtcaffe::LayerParameter& msg, CaffeWeightFactory& weightFactory, BlobNameToTensor& tensors); std::vector
         
           parsePriorBoxParam(const trtcaffe::LayerParameter& msg, CaffeWeightFactory& weightFactory, BlobNameToTensor& tensors); std::vector
          
            parseDetectionOutputParam(const trtcaffe::LayerParameter& msg, CaffeWeightFactory& weightFactory, BlobNameToTensor& tensors); std::vector
           
             parseLReLUParam(const trtcaffe::LayerParameter& msg, CaffeWeightFactory& weightFactory, BlobNameToTensor& tensors); std::vector
            
              parseRPROIParam(const trtcaffe::LayerParameter& msg, CaffeWeightFactory& weightFactory, BlobNameToTensor& tensors); //分配size（默認為1）大小的T型別的空間，然後放到mTmpAllocs裡集中管理 template 
             
               T* allocMemory(int size = 1) { T* tmpMem = static_cast
              
               (malloc(sizeof(T) * size)); mTmpAllocs.push_back(tmpMem); return tmpMem; } const IBlobNameToTensor* parse(nvinfer1::INetworkDefinition& network, nvinfer1::DataType weightType, bool hasModel);private: //用於表示模型架構 std::shared_ptr
               
                 mDeploy; //用於儲存模型權重 std::shared_ptr
                
                  mModel; /* 為CaffeWeightFactory所用， 用於記錄分配或轉換權重時，使用malloc新申請的記憶體 */ std::vector
                 
                   mTmpAllocs; /* BlobNameToTensor 定義於TensorRT/parsers/caffe/blobNameToTensor.h 其核心為mMap這個字典，用於把blob name對應到ITensor* */ BlobNameToTensor* mBlobNameToTensor{ nullptr}; /* 為TensorRT/parsers/caffe/caffeParser/readProto.h中的函數readBinaryProto所用， 表示stream讀取的最大byte數 */ size_t mProtobufBufferSize{ INT_MAX}; /* nvcaffeparser1::IPluginFactory 定義於TensorRT/include/NvCaffeParser.h Plugin factory used to configure plugins. */ nvcaffeparser1::IPluginFactory* mPluginFactory{ nullptr}; /* nvcaffeparser1::IPluginFactoryV2 定義於TensorRT/include/NvCaffeParser.h Plugin factory used to configure plugins. */ nvcaffeparser1::IPluginFactoryV2* mPluginFactoryV2{ nullptr}; bool mPluginFactoryIsExt{ false}; //用於存放nvinfer1::IPluginV2的向量 std::vector
                  
                    mNewPlugins; //用於儲存的plugin名稱對應到nvinfer1::IPluginCreator*字典 std::unordered_map
                   
                     mPluginRegistry; //作為nvcaffeparser1::IPluginFactoryV2::createPlugin函數的參數使用 std::string mPluginNamespace = "";};} //namespace nvcaffeparser1#endif //TRT_CAFFE_PARSER_CAFFE_PARSER_H
                   
                  
                 
                
               
              
             
            
           
          
         
        
       
      
     
    
   

delete this

destroy函數的內容是delete this，詳見。

std::unordered_map

在caffeParser.h中宣告了CaffeParser類別，其中有一個成員mPluginRegistry為std::unordered_map型別的：

std::unordered_map
   
     mPluginRegistry;
   

std::map內部的元素會依其key被排序； 而std::unordered_map則沒有。如果要隨機存取一個元素，使用std::unordered_map的速度會比較快。

參考連結