PyBind11:boost::multiprecision::cpp_int 到 Python
PyBind11: boost::multiprecision::cpp_int to Python
我有兴趣使用 pybind11 to optimize some Python computation using C++. The casting documentation 对我来说没有多大意义,想知道是否有人知道如何将 boost 数据类型,特别是 cpp_int 转换为 Python 数据类型所以我可以 return 计算。我正在尝试做的一个简单示例是阶乘:
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include <boost/multiprecision/cpp_int.hpp>
using boost::multiprecision::cpp_int;
namespace py = pybind11;
py::int_ fact(int i) {
cpp_int prod = 1;
while(i-- >= 1){
prod *= (i+1);
}
return py::cast(prod);
}
PYBIND11_MODULE(fact, m) {
m.def("fact", &fact,R"pbdoc(
Returns the factorial of a number.
)pbdoc");
}
上面的编译但是当我去使用它时我得到
TypeError: Unregistered type : boost::multiprecision::number<boost::multiprecision::backends::cpp_int_backend<0u, 0u, (boost::multiprecision::cpp_integer_type)1, (boost::multiprecision::cpp_int_check_type)0, std::allocator<unsigned long long> >, (boost::multiprecision::expression_template_option)1>
所以我认为 py::cast 有些东西不工作...
我的笔记本电脑运行 Windows 10,我正在使用 Anaconda Python 3.7
C:\Users734>python
Python 3.7.1 (default, Dec 10 2018, 22:54:23) [MSC v.1915 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
和Stephan T. Lavavej's MinGW C++ 8.2.0
C:\Users734>g++ -v
Using built-in specs.
COLLECT_GCC=g++
COLLECT_LTO_WRAPPER=c:/mingw/bin/../libexec/gcc/x86_64-w64-mingw32/8.2.0/lto-wrapper.exe
Target: x86_64-w64-mingw32
Configured with: ../src/configure --enable-languages=c,c++ --build=x86_64-w64-mingw32 --host=x86_64-w64-mingw32 --target=x86_64-w64-mingw32 --disable-multilib --prefix=/c/temp/gcc/dest --with-sysroot=/c/temp/gcc/dest --disable-libstdcxx-pch --disable-libstdcxx-verbose --disable-nls --disable-shared --disable-win32-registry --with-tune=haswell --enable-threads=posix --enable-libgomp
Thread model: posix
gcc version 8.2.0 (GCC)
我也在为位于“C:\ProgramFiles(x86)\MicrosoftVisualStudio17\BuildTools\VC\Redist\MSVC.16.27012\onecore\x64\Microsoft 中的 vcruntime140.dll 使用 Build Tools for Visual Studio 2017。 VC141.CRT”(我将其复制并粘贴到“C:\MinGW\lib”)。我还将“C:\Anaconda3\Lib\distutils\cygwinccompiler.py”中的所有字符串"gcc"更改为"g++"(我没有 用 gcc 改变变量名。
关键词:
"pybind11"; "Boost"; "C++ and Python"; "boost::multiprecision::cpp_int"
我成功了:
#include <boost/multiprecision/cpp_int.hpp>
#include <iomanip>
#include <pybind11/pybind11.h>
#include <sstream>
using cpp_int = boost::multiprecision::cpp_int;
namespace py = pybind11;
namespace pybind11
{
namespace detail
{
template <>
struct type_caster<cpp_int> {
/**
* This macro establishes the name 'cpp_int' in
* function signatures and declares a local variable
* 'value' of type cpp_int
*/
PYBIND11_TYPE_CASTER(cpp_int, _("cpp_int"));
/**
* Conversion part 1 (Python->C++): convert a PyObject into a cpp_int
* instance or return false upon failure. The second argument
* indicates whether implicit conversions should be applied.
*/
bool load(handle src, bool)
{
// Convert into base 16 string (PyNumber_ToBase prepend '0x')
PyObject* tmp = PyNumber_ToBase(src.ptr(), 16);
if (!tmp) return false;
std::string s = py::cast<std::string>(tmp);
value = cpp_int{s}; // explicit cast from string to cpp_int,
// don't need a base here because
// `PyNumber_ToBase` already prepended '0x'
Py_DECREF(tmp);
/* Ensure return code was OK (to avoid out-of-range errors etc) */
return !PyErr_Occurred();
}
/**
* Conversion part 2 (C++ -> Python): convert an cpp_int instance into
* a Python object. The second and third arguments are used to
* indicate the return value policy and parent object (for
* ``return_value_policy::reference_internal``) and are generally
* ignored by implicit casters.
*/
static handle cast(const cpp_int& src, return_value_policy, handle)
{
// Convert cpp_int to base 16 string
std::ostringstream oss;
oss << std::hex << src;
return PyLong_FromString(oss.str().c_str(), nullptr, 16);
}
};
} // namespace detail
} // namespace pybind11
py::int_ fact(int i)
{
cpp_int prod = 1;
while (i-- > 1) prod *= i + 1;
return py::cast(prod);
}
PYBIND11_MODULE(python_example, m)
{
m.def("fact", &fact, R"pbdoc(
Returns the factorial of a number.
)pbdoc");
}
可能不是最快的方法,因为它先将 cpp_int
转换为临时的 16 进制字符串,然后再将此字符串转换为 Python 整数。
我有兴趣使用 pybind11 to optimize some Python computation using C++. The casting documentation 对我来说没有多大意义,想知道是否有人知道如何将 boost 数据类型,特别是 cpp_int 转换为 Python 数据类型所以我可以 return 计算。我正在尝试做的一个简单示例是阶乘:
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include <boost/multiprecision/cpp_int.hpp>
using boost::multiprecision::cpp_int;
namespace py = pybind11;
py::int_ fact(int i) {
cpp_int prod = 1;
while(i-- >= 1){
prod *= (i+1);
}
return py::cast(prod);
}
PYBIND11_MODULE(fact, m) {
m.def("fact", &fact,R"pbdoc(
Returns the factorial of a number.
)pbdoc");
}
上面的编译但是当我去使用它时我得到
TypeError: Unregistered type : boost::multiprecision::number<boost::multiprecision::backends::cpp_int_backend<0u, 0u, (boost::multiprecision::cpp_integer_type)1, (boost::multiprecision::cpp_int_check_type)0, std::allocator<unsigned long long> >, (boost::multiprecision::expression_template_option)1>
所以我认为 py::cast 有些东西不工作...
我的笔记本电脑运行 Windows 10,我正在使用 Anaconda Python 3.7
C:\Users734>python
Python 3.7.1 (default, Dec 10 2018, 22:54:23) [MSC v.1915 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
和Stephan T. Lavavej's MinGW C++ 8.2.0
C:\Users734>g++ -v
Using built-in specs.
COLLECT_GCC=g++
COLLECT_LTO_WRAPPER=c:/mingw/bin/../libexec/gcc/x86_64-w64-mingw32/8.2.0/lto-wrapper.exe
Target: x86_64-w64-mingw32
Configured with: ../src/configure --enable-languages=c,c++ --build=x86_64-w64-mingw32 --host=x86_64-w64-mingw32 --target=x86_64-w64-mingw32 --disable-multilib --prefix=/c/temp/gcc/dest --with-sysroot=/c/temp/gcc/dest --disable-libstdcxx-pch --disable-libstdcxx-verbose --disable-nls --disable-shared --disable-win32-registry --with-tune=haswell --enable-threads=posix --enable-libgomp
Thread model: posix
gcc version 8.2.0 (GCC)
我也在为位于“C:\ProgramFiles(x86)\MicrosoftVisualStudio17\BuildTools\VC\Redist\MSVC.16.27012\onecore\x64\Microsoft 中的 vcruntime140.dll 使用 Build Tools for Visual Studio 2017。 VC141.CRT”(我将其复制并粘贴到“C:\MinGW\lib”)。我还将“C:\Anaconda3\Lib\distutils\cygwinccompiler.py”中的所有字符串"gcc"更改为"g++"(我没有 用 gcc 改变变量名。
关键词:
"pybind11"; "Boost"; "C++ and Python"; "boost::multiprecision::cpp_int"
我成功了:
#include <boost/multiprecision/cpp_int.hpp>
#include <iomanip>
#include <pybind11/pybind11.h>
#include <sstream>
using cpp_int = boost::multiprecision::cpp_int;
namespace py = pybind11;
namespace pybind11
{
namespace detail
{
template <>
struct type_caster<cpp_int> {
/**
* This macro establishes the name 'cpp_int' in
* function signatures and declares a local variable
* 'value' of type cpp_int
*/
PYBIND11_TYPE_CASTER(cpp_int, _("cpp_int"));
/**
* Conversion part 1 (Python->C++): convert a PyObject into a cpp_int
* instance or return false upon failure. The second argument
* indicates whether implicit conversions should be applied.
*/
bool load(handle src, bool)
{
// Convert into base 16 string (PyNumber_ToBase prepend '0x')
PyObject* tmp = PyNumber_ToBase(src.ptr(), 16);
if (!tmp) return false;
std::string s = py::cast<std::string>(tmp);
value = cpp_int{s}; // explicit cast from string to cpp_int,
// don't need a base here because
// `PyNumber_ToBase` already prepended '0x'
Py_DECREF(tmp);
/* Ensure return code was OK (to avoid out-of-range errors etc) */
return !PyErr_Occurred();
}
/**
* Conversion part 2 (C++ -> Python): convert an cpp_int instance into
* a Python object. The second and third arguments are used to
* indicate the return value policy and parent object (for
* ``return_value_policy::reference_internal``) and are generally
* ignored by implicit casters.
*/
static handle cast(const cpp_int& src, return_value_policy, handle)
{
// Convert cpp_int to base 16 string
std::ostringstream oss;
oss << std::hex << src;
return PyLong_FromString(oss.str().c_str(), nullptr, 16);
}
};
} // namespace detail
} // namespace pybind11
py::int_ fact(int i)
{
cpp_int prod = 1;
while (i-- > 1) prod *= i + 1;
return py::cast(prod);
}
PYBIND11_MODULE(python_example, m)
{
m.def("fact", &fact, R"pbdoc(
Returns the factorial of a number.
)pbdoc");
}
可能不是最快的方法,因为它先将 cpp_int
转换为临时的 16 进制字符串,然后再将此字符串转换为 Python 整数。