C++ DLL 不导出函数

我正在开发一个C++库，用于在Visual Studio 2013（C++ 11）中导出为DLL，我遇到了一个挑战，即库一旦被另一个程序作为外部依赖项导入，就包含我想要的类，但不包含类的任何功能。

外部依赖项中的类视图

我包含一个特定的类，它应该是此DLL导出的一部分。

这是我的回归训练器类头文件：

#ifndef REGRESSION_TRAINER_H
#define REGRESSION_TRAINER_H
#include "MachineLearning.h"
#pragma once
#ifndef DLL_EXPORT
#define DLL_EXPORT __declspec(dllexport)
#endif
using namespace MachineLearning;
namespace MachineLearningTraining{
public class RegressionTrainer{
public:
    DLL_EXPORT RegressionTrainer();
    virtual DLL_EXPORT ~RegressionTrainer();
    std::vector<sample_type> DLL_EXPORT getInputData();
    std::vector<double> DLL_EXPORT getAugmentedOutputs();
    std::vector<double> DLL_EXPORT getNonAugmentedOutputs();
protected:
    pugi::xml_parse_result DLL_EXPORT setDataFile(pugi::xml_document &doc, char* file_name);
    void DLL_EXPORT setDataFolder(char* folder_name);
    std::vector<char*> DLL_EXPORT findDataFiles();
    char* data_folder;
    std::vector<char*> file_names;
    std::vector<sample_type> input_data;
    /*
    sample_type m;
    m(0, 0) = 14.86;
    m(1, 0) = 0.24;
    */
    std::vector<double> augmented_outputs;
    std::vector<double> non_augmented_outputs;
    pugi::xml_parse_result result;
    void DLL_EXPORT setInputData();
    void DLL_EXPORT setAugmentedOutputs();
    void DLL_EXPORT setNonAugmentedOutputs();
    virtual int DLL_EXPORT trainAugmentedModel();
    virtual int DLL_EXPORT trainNonAugmentedModel();
};
}
#endif

以下是 MachineLearning.h 的内容：

#include <vector>
#include <iostream>
#include <exception>
#include <fstream>
#include <string>
#include <dlib/svm.h>
#include "pugixml.hpp"
namespace MachineLearning{
// Here we declare that our samples will be 2 dimensional column vectors.  
    typedef dlib::matrix<double, 3, 1> sample_type;
// Now we are making a typedef for the kind of kernel we want to use.  I picked the
// radial basis kernel because it only has one parameter and generally gives good
// results without much fiddling.
    typedef dlib::radial_basis_kernel<sample_type> kernel_type;
}

这是我的回归训练器.cpp文件：

#include "Stdafx.h"
#include "RegressionTrainer.h"
#include "dirent.h"
using namespace std;
using namespace dlib;
using namespace MachineLearning;
namespace MachineLearningTraining{
RegressionTrainer::RegressionTrainer(){
    file_names = findDataFiles();
}
RegressionTrainer::~RegressionTrainer(){
}
pugi::xml_parse_result RegressionTrainer::setDataFile(pugi::xml_document &doc, char *file_name){
    return doc.load_file(file_name);
}
void RegressionTrainer::setDataFolder(char *folder_name){
    data_folder = folder_name;
}
std::vector<char*> RegressionTrainer::findDataFiles(){
    DIR *dir;
    struct dirent *ent;
    std::vector<char*> file_names;
    if ((dir = opendir(data_folder)) != NULL) {
        /* print all the files and directories within directory */
        while ((ent = readdir(dir)) != NULL) {
            file_names.push_back(ent->d_name);
        }
        closedir(dir);
    }
    else {
        /* could not open directory */
        perror("Could not open directory");
    }
    return file_names;
}
std::vector<sample_type> RegressionTrainer::getInputData(){
    return input_data;
}
std::vector<double> RegressionTrainer::getAugmentedOutputs(){
    return augmented_outputs;
}
std::vector<double> RegressionTrainer::getNonAugmentedOutputs(){
    return non_augmented_outputs;
}
void RegressionTrainer::setInputData(){
    pugi::xml_document doc;
    for (unsigned i = 0; i < file_names.size(); i++){
        setDataFile(doc, file_names[i]);
        std::cout << "Load result: " << result.description() << endl;
        pugi::xml_node measures = doc.child("case").child("measures");
        sample_type m;
        int count = 0;
        for (pugi::xml_node measure = measures.first_child(); measure; measure = measure.next_sibling()){
            m(count, 0) = measure.text().as_double();
            count++;
        }
        input_data.push_back(m);
    }
}
void RegressionTrainer::setAugmentedOutputs(){
    pugi::xml_document doc;
    for (unsigned i = 0; i < file_names.size(); i++){
        setDataFile(doc, file_names[i]);
        std::cout << "Load result: " << result.description() << endl;
        pugi::xml_node output = doc.child("case").child("studyresults").child("averageangledeviation");
        augmented_outputs.push_back(output.text().as_double());
    }
}
void RegressionTrainer::setNonAugmentedOutputs(){
    pugi::xml_document doc;
    for (unsigned i = 0; i < file_names.size(); i++){
        setDataFile(doc, file_names[i]);
        std::cout << "Load result: " << result.description() << endl;
        pugi::xml_node output = doc.child("case").child("studyresults").child("averageangledeviationAR");
            augmented_outputs.push_back(output.text().as_double());
        }
    }
    int RegressionTrainer::trainAugmentedModel(){
        return 0;
    }
    int RegressionTrainer::trainNonAugmentedModel(){
        return 0;
    }
}

欢迎任何想法！