自分用のメモ
以前に書いたやり方*1で入らなかったので，ここ*2を参考に手順を再構築
1. インストール
ここ*3からソースをダウンロード
boost ver.は以前に使っていた1.73.0
pythonはver.3.8を指定
$ sudo cp boost_1_73_0.tar.gz -r /opt/ $ cd /opt $ sudo tar zxvf boost_1_73_0.tar.gz $ sudo rm boost_1_73_0.tar.gz $ cd boost_1_73_0 $ sudo ./bootstrap.sh --with-libraries=python --with-python=python3 --with-python-version=3.8 $ sudo ./b2 --prefix=/opt/boost_1_73_0 install $ find /opt -name *boost_python*
$ find /opt -name *boost_numpy*
Note:
・よく分からなかったけど，以前には必要なかったオプション"--with-libraries=python --with-python=python3"が要るっぽかった．これが無いとlibboost_numpy38がビルドされない
・インストール先を"--prefix=/opt/boost_1_73_0 install"としているので/usr/libには入らない．多分，"-j8"オプションで汎用ディレクトリに入る
2. C言語ライブラリのビルド & Pythonからのコール
boost_sample.cpp
#include "boost/python/numpy.hpp"
#include <stdexcept>
#include <algorithm>
#include <iostream>
#include <fstream>
#include <random>
#include <sys/stat.h>
namespace p = boost::python;
namespace np = boost::python::numpy;
using namespace std;
np::ndarray multiply_matrix(np::ndarray a, np::ndarray b, int size)
{
int nd = a.get_nd();
if (nd != 1)
{
throw std::runtime_error("a must be 1-dimensional");
}
if (a.get_dtype() != np::dtype::get_builtin<double>())
{
throw std::runtime_error("a must be float64 array");
}
double *A = reinterpret_cast<double *>(a.get_data());
nd = b.get_nd();
if (nd != 1)
{
throw std::runtime_error("b must be 1-dimensional");
}
if (b.get_dtype() != np::dtype::get_builtin<double>())
throw std::runtime_error("b must be float64 array");
double *B = reinterpret_cast<double *>(b.get_data());
vector<double> ma;
for(int i = 0; i < size; i++)
{
for(int j = 0; j < size; j++)
{
double tmp = 0.0;
for(int k = 0; k < size; k++)
{
tmp += A[i*size + k]*B[k*size + j];
}
ma.push_back(tmp);
}
}
Py_intptr_t shape[2] = {size, size};
np::ndarray result = np::zeros(2, shape, np::dtype::get_builtin<double>());
std::copy(ma.begin(), ma.end(), reinterpret_cast<double*>(result.get_data()));
return result;
}
double rand_uniform(double min, double max)
{
double width = max - min;
std::random_device rnd;
std::mt19937 mt(rnd());
std::uniform_int_distribution<> rand10000(0, 10000*width);
int randi = rand10000(mt);
double val = min + (float)randi/10000.0;
return val;
}
int main(int argc, char* argv[])
{
cout << "Hellow" << endl;
Py_Initialize();
np::initialize();
double a[5*5];
double b[5*5];
int m_size = 5*5;
for(int i = 0; i < 5; i++)
{
for(int j = 0; j < 5; j++)
{
a[i*5 + j] = rand_uniform(-1.0, 1.0); //random.uniform(-10.0, 10.0)
b[i*5 + j] = rand_uniform(-1.0, 1.0); //random.uniform(-10.0, 10.0)
}
}
cout << "input a:" << endl;
cout << a[0] << "," << a[1] << "," << a[2] << "," << a[3] << "," << a[4] << endl;
cout << a[5] << "," << a[6] << "," << a[7] << "," << a[8] << "," << a[9] << endl;
cout << a[10] << "," << a[11] << "," << a[12] << "," << a[13] << "," << a[14] << endl;
cout << a[15] << "," << a[16] << "," << a[17] << "," << a[18] << "," << a[19] << endl;
cout << a[20] << "," << a[21] << "," << a[22] << "," << a[23] << "," << a[24] << endl;
cout << "input b:" << endl;
cout << b[0] << "," << b[1] << "," << b[2] << "," << b[3] << "," << b[4] << endl;
cout << b[5] << "," << b[6] << "," << b[7] << "," << b[8] << "," << b[9] << endl;
cout << b[10] << "," << b[11] << "," << b[12] << "," << b[13] << "," << b[14] << endl;
cout << b[15] << "," << b[16] << "," << b[17] << "," << b[18] << "," << b[19] << endl;
cout << b[20] << "," << b[21] << "," << b[22] << "," << b[23] << "," << b[24] << endl;
p::tuple shape = p::make_tuple(m_size);
p::tuple stride = p::make_tuple(sizeof(double));
np::dtype dt = np::dtype::get_builtin<double>();
np::ndarray a_np = np::from_data(&a[0], dt, shape, stride, p::object());
np::ndarray b_np = np::from_data(&b[0], dt, shape, stride, p::object());
np::ndarray result_np = multiply_matrix(a_np, b_np, 5);
double *result = reinterpret_cast<double *>(result_np.get_data());
cout << "result:" << endl;
cout << result[0] << "," << result[1] << "," << result[2] << "," << result[3] << "," << result[4] << endl;
cout << result[5] << "," << result[6] << "," << result[7] << "," << result[8] << "," << result[9] << endl;
cout << result[10] << "," << result[11] << "," << result[12] << "," << result[13] << "," << result[14] << endl;
cout << result[15] << "," << result[16] << "," << result[17] << "," << result[18] << "," << result[19] << endl;
cout << result[20] << "," << result[21] << "," << result[22] << "," << result[23] << "," << result[24] << endl;
return 0;
}
BOOST_PYTHON_MODULE(libsample) {
Py_Initialize();
np::initialize();
p::def("multiply_matrix", multiply_matrix);
}
・mainとrand_uniformはデバッグ用
・”using namespace std”は普段使わないけど面倒かったので...
CMakeLists.txt
project(sample)
cmake_minimum_required(VERSION 3.0)
set(BOOST_ROOT /opt/boost_1_73_0)
### C++11
add_compile_options(-std=c++11)
### pkgconfig (for pkg_check_modules)
find_package(PkgConfig REQUIRED)
### Python includes
pkg_check_modules(PYTHON3 python3 REQUIRED)
include_directories(${PYTHON3_INCLUDE_DIRS})
### Boost includes
include_directories(${BOOST_ROOT}/include)
link_directories(${BOOST_ROOT}/lib)
### Build
add_library(sample SHARED boost_sample.cpp)
set_target_properties(sample PROPERTIES SUFFIX ".so")
target_link_libraries(sample boost_numpy38 boost_python38)
boost_sample_call.py
import numpy as np
import libsample as s
import random
if __name__ == "__main__":
a = np.zeros([5, 5])
b = np.zeros([5, 5])
for i in range(5):
for j in range(5):
a[i, j] = random.uniform(-10.0, 10.0)
b[i, j] = random.uniform(-10.0, 10.0)
print(np.matmul(a, b))
result = s.multiply_matrix(a.reshape([5*5]), b.reshape(5*5), 5)
print(result)
ビルドして実行
$ mkdir build $ cd build $ cmake .. $ make $ cd .. $ cp build/*.so ./ $ python3 boost_sample_call.py
3. C言語ソースのデバッグ
~/.bashrc
export LD_LIBRARY_PATH="/opt/boost_1_73_0/lib:$PATH"
task.json
{
"tasks": [
{
"type": "shell",
"label": "C/C++: g++-9 build active file",
"command": "/usr/bin/g++-9",
"args": [
"-fdiagnostics-color=always",
"-g",
"${file}",
"-o",
"${fileDirname}/${fileBasenameNoExtension}",
"-std=c++11",
"-I/opt/boost_1_73_0/include",
"-I/usr/include/python3.8",
"-I/usr/include/x86_64-linux-gnu/python3.8",
"-L/usr/bin",
"-lpython3.8",
"-L/opt/boost_1_73_0/lib",
"-lboost_numpy38",
"-lboost_python38"
],
"options": {
"cwd": "${fileDirname}"
},
"problemMatcher": [
"$gcc"
],
"group": {
"kind": "build",
"isDefault": true
},
"detail": "Task generated by Debugger."
}
],
"version": "2.0.0"
}
・typeをcppbuild→shellにすること
・"-L/opt/boost_1_73_0/lib"で実際に入ったパスを指定すれば，/usr/libにライブラリが入らなくても問題ない
以上
