Question

您好我有一个代码实现libeigen2来计算特征向量。现在我想使用boost :: serialization来保存稍后检索的信息。从示例tutorial我想出了以下代码！

class RandomNode {
private:
friend class boost::serialization::access;
template<class Archive>
void serialize(Archive & ar, const unsigned int version)
{
   ar & is_leaf_;
   ar & depth_;
   ar & num_classes_;
   ar & num_features_;
   // Split node members
   ar & random_feature_indices_;
   ar & random_feature_weights_;
   ar & threshold_;
   ar & leftChild_;
   ar & rightChild_;

 }
bool is_leaf_;
int depth_;
int num_classes_;
int num_features_;

// Split node members
VectorXi random_feature_indices_;
VectorXd random_feature_weights_;
double threshold_;
RandomNode* leftChild_;
RandomNode* rightChild_;
 // Methods and so on
}

现在，当我尝试运行此代码时，我收到以下错误

/usr/include/boost/serialization/access.hpp:118:9: error: ‘class Eigen::Matrix<double, 10000, 1>’ has no member named ‘serialize’

如何序列化Eigen :: Matrix类？可能吗？提前谢谢。

Answer 1

您应该阅读有关serializable概念主题的boost :: serialization文档。它基本上说类型需要是原始的或可序列化的。 Eigen类型不是它，编译器试图告诉你。为了使Eigen类型可序列化，您需要实现以下自由函数

template<class Archive>
inline void serialize(
    Archive & ar, 
    my_class & t, 
    const unsigned int file_version
) {
    ...
}

为了为Eigen做这件事，我想你可能会做这样的事情模板

以下是适用于您的示例实现：

#include <fstream>
#include <Eigen/Core>
#include <boost/archive/text_oarchive.hpp>

using namespace Eigen;

struct RandomNode {
friend class boost::serialization::access;
template<class Archive>
void serialize(Archive & ar, const unsigned int version)
{
   ar & random_feature_indices_;
   ar & random_feature_weights_;
}
// Split node members
VectorXi random_feature_indices_;
VectorXd random_feature_weights_;
};

namespace boost
{
template<class Archive, typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
inline void serialize(
    Archive & ar, 
    Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> & t, 
    const unsigned int file_version
) 
{
    size_t rows = t.rows(), cols = t.cols();
    ar & rows;
    ar & cols;
    if( rows * cols != t.size() )
    t.resize( rows, cols );

    for(size_t i=0; i<t.size(); i++)
    ar & t.data()[i];
}
}

int main()
{
    // create and open a character archive for output
    std::ofstream ofs("filename");

    RandomNode r;
    r.random_feature_indices_.resize(3,1);

    // save data to archive
    {
        boost::archive::text_oarchive oa(ofs);
        // write class instance to archive
        oa << r;
        // archive and stream closed when destructors are called
    }
}

如何使用Boost：序列化来保存Eigen :: Matrix

1 个答案: