使用谷歌库序列化Eigen :: Matrix

Question

更新:我用谷歌搜索并在代码中读取doxygen注释后设法让它工作.问题是我在使用resize()方法之前错过了演员,也没有std::ios::binary用于流.如果你想做类似的事情,最好检查Azoth的答案.

我正在尝试Eigen::Matrix使用Cereal 序列化类型.这就是我所拥有的(松散地基于https://gist.github.com/mtao/5798888和其中的类型cereal/types):

#include <cereal/cereal.hpp>
#include <cereal/archives/binary.hpp>
#include <Eigen/Dense>
#include <fstream>

namespace cereal
{
    template <class Archive, class _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols> inline
        typename std::enable_if<traits::is_output_serializable<BinaryData<_Scalar>, Archive>::value, void>::type
        save(Archive & ar, Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> const & m)
    {
            int rows = m.rows();
            int cols = m.cols();
            ar(make_size_tag(static_cast<size_type>(rows * cols)));
            ar(rows);
            ar(cols);
            ar(binary_data(m.data(), rows * cols * sizeof(_Scalar)));
        }

    template <class Archive, class _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols> inline
        typename std::enable_if<traits::is_input_serializable<BinaryData<_Scalar>, Archive>::value, void>::type
        load(Archive & ar, Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> const & m)
    {
            size_type size;
            ar(make_size_tag(size));

            int rows;
            int cols;
            ar(rows);
            ar(cols);

            const_cast<Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> &>(m).resize(rows, cols);

            ar(binary_data(const_cast<_Scalar *>(m.data()), static_cast<std::size_t>(size * sizeof(_Scalar))));
        }
}

int main() {
    Eigen::MatrixXd test = Eigen::MatrixXd::Random(10, 3);
    std::ofstream out = std::ofstream("eigen.cereal", std::ios::binary);
    cereal::BinaryOutputArchive archive_o(out);
    archive_o(test);

    std::cout << "test:" << std::endl << test << std::endl;

    out.close();

    Eigen::MatrixXd test_loaded;
    std::ifstream in = std::ifstream("eigen.cereal", std::ios::binary);
    cereal::BinaryInputArchive archive_i(in);
    archive_i(test_loaded);

    std::cout << "test loaded:" << std::endl << test_loaded << std::endl;
}

Answer 1

您的代码几乎是正确的,但有一些错误:

您不需要生成,size_tag因为您明确地序列化行数和列数.通常谷物size_tag用于可调整大小的容器,如载体或列表.即使矩阵可以调整大小,仅仅明确地序列化行和列也更有意义.

1. 您的加载函数应该通过非const引用接受其参数
2. 您不应该将operator =与std::ofstream对象一起使用
3. 更好的做法是让范围界定和RAII处理关闭/拆除std::ofstream谷物档案(二进制档案库将立即清除其内容,但一般情况下谷物档案只能保证在销毁时清除其内容)

这是一个在g ++和clang ++下编译并生成正确输出的版本:

#include <cereal/cereal.hpp>
#include <cereal/archives/binary.hpp>
#include <Eigen/Dense>
#include <fstream>

namespace cereal
{
  template <class Archive, class _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols> inline
    typename std::enable_if<traits::is_output_serializable<BinaryData<_Scalar>, Archive>::value, void>::type
    save(Archive & ar, Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> const & m)
    {
      int32_t rows = m.rows();
      int32_t cols = m.cols();
      ar(rows);
      ar(cols);
      ar(binary_data(m.data(), rows * cols * sizeof(_Scalar)));
    }

  template <class Archive, class _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols> inline
    typename std::enable_if<traits::is_input_serializable<BinaryData<_Scalar>, Archive>::value, void>::type
    load(Archive & ar, Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> & m)
    {
      int32_t rows;
      int32_t cols;
      ar(rows);
      ar(cols);

      m.resize(rows, cols);

      ar(binary_data(m.data(), static_cast<std::size_t>(rows * cols * sizeof(_Scalar))));
    }
}

int main() {
  Eigen::MatrixXd test = Eigen::MatrixXd::Random(10, 3);

  {
    std::ofstream out("eigen.cereal", std::ios::binary);
    cereal::BinaryOutputArchive archive_o(out);
    archive_o(test);
  }

  std::cout << "test:" << std::endl << test << std::endl;

  Eigen::MatrixXd test_loaded;

  {
    std::ifstream in("eigen.cereal", std::ios::binary);
    cereal::BinaryInputArchive archive_i(in);
    archive_i(test_loaded);
  }

  std::cout << "test loaded:" << std::endl << test_loaded << std::endl;
}