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pybind11和numpy进行交互的方法

时间:2020-10-08 13:26:45 | 栏目:Python代码 | 点击:

使用一个遵循buffer protocol的对象就可以和numpy交互了.

这个buffer_protocol要有哪些东西呢? 要有如下接口:

struct buffer_info {
  void *ptr;
  ssize_t itemsize;
  std::string format;
  ssize_t ndim;
  std::vector<ssize_t> shape;
  std::vector<ssize_t> strides;
};

其实就是一个指向数组的指针+各个维度的信息就可以了. 然后我们就可以用指针+偏移来访问数字中的任意位置上的数字了.

下面是一个可以跑的例子:

#include <pybind11/pybind11.h>
 #include <pybind11/numpy.h>
 namespace py = pybind11;
 py::array_t<double> add_arrays(py::array_t<double> input1, py::array_t<double> input2) {
   py::buffer_info buf1 = input1.request(), buf2 = input2.request();
   if (buf1.ndim != 1 || buf2.ndim != 1)
     throw std::runtime_error("Number of dimensions must be one");
   if (buf1.size != buf2.size)
     throw std::runtime_error("Input shapes must match");
   /* No pointer is passed, so NumPy will allocate the buffer */
   auto result = py::array_t<double>(buf1.size);
   py::buffer_info buf3 = result.request();
   double *ptr1 = (double *) buf1.ptr,
      *ptr2 = (double *) buf2.ptr,
      *ptr3 = (double *) buf3.ptr;
   for (size_t idx = 0; idx < buf1.shape[0]; idx++)
     ptr3[idx] = ptr1[idx] + ptr2[idx];
   return result;
 }
 
 PYBIND11_MODULE(test, m) {
   m.def("add_arrays", &add_arrays, "Add two NumPy arrays");
 }

array_t里的buf就是一个兼容的接口.

buf中可以得到指针和对应数字的维度信息.

为了方便我们甚至可以使用Eigen当作我们兼容numpy的接口:

#include <pybind11/pybind11.h>
 #include <pybind11/eigen.h> 
 #include <Eigen/LU> 
 // N.B. this would equally work with Eigen-types that are not predefined. For example replacing
 // all occurrences of "Eigen::MatrixXd" with "MatD", with the following definition:
 //
 // typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> MatD;
 
 Eigen::MatrixXd inv(const Eigen::MatrixXd &xs)
 {
  return xs.inverse();
 }
 
 double det(const Eigen::MatrixXd &xs)
 {
  return xs.determinant();
 }
 
 namespace py = pybind11;
 
 PYBIND11_MODULE(example,m)
 {
  m.doc() = "pybind11 example plugin";
 
  m.def("inv", &inv);
 
  m.def("det", &det);
 }

更多参考:

https://pybind11.readthedocs.io/en/stable/advanced/pycpp/numpy.html

https://github.com/tdegeus/pybind11_examples

总结

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