首页 > 解决方案 > 如何将 Numpy 矩阵列表映射到 Cython 中的特征矩阵向量

问题描述

我有一个要从 Python 运行的 C++ 函数。为此,我使用 Cython。我的 C++ 函数严重依赖于 Eigen 矩阵,我使用 Eigency 将其映射到 Python 的 Numpy 矩阵。

在我有一个 Numpy 矩阵列表的情况下,我无法让它工作。


什么有效(将普通 Numpy 矩阵映射到 Eigen 矩阵):

我有一个 C++ 函数,它在标题(Header.h)中看起来像:

float MyCppFunction(Eigen::Map<Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>> &inputMatrix);

在我的 CythonFile.pyx 文件中(并使用 Eigency 创建地图,如此处所述

cdef extern from "Header.h":
    cdef void _MyCppFunction "MyCppFunction"(FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor] &)

def my_python_function(np.ndarray[ndim=2, dtype=np.float32_t] my_matrix)
    return _MyCppFunction(FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor](my_matrix))

我可以使用 Cython 构建这个模块并my_python_function从 Python 成功调用。


什么不起作用(将 Numpy 矩阵列表映射到 Eigen 矩阵向量):

现在我尝试做同样的事情,但是对于矩阵列表。我不能让它工作。是)我有的:

标头 (Header.h) 中的 C++ 函数如下所示:

float MyCppFunction(std::vector<Eigen::Map<Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>> &inputMatrixList);

在我的 CythonFile.pyx 文件中,我有:

cdef extern from "Header.h":
    cdef void _MyCppFunction "MyCppFunction"(vector[FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor]] &)

def my_python_function(list my_matrix_list)
    cdef vector[FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor]] map
    
    for matrix in my_matrix_list:
        map.push_back(FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor](matrix))
        
   return _MyCppFunction(map)

不幸的是,这不会编译。

例如,当我简单地使用我想要映射到 a 的 alist时,这个概念确实可以编译和运行。但是,当我将 Numpy 矩阵列表映射到本征矩阵向量时(我在上面提到的情况),它不起作用。intstd::vector<int>


我得到的错误:

我在编译过程中遇到的错误: error C2664: 'float MyCppFunction(std::vector<Eigen::Map<Eigen::Matrix<float,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>,std::allocator<Eigen::Map<Eigen::Matrix<float,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>>> &)': cannot convert argument 1 from 'std::vector<eigency::FlattenedMap<Eigen::Matrix,float,-1,-1,1,0,0,0,-1,-1>,std::allocator<eigency::FlattenedMap<Eigen::Matrix,float,-1,-1,1,0,0,0,-1,-1>>>' to 'std::vector<Eigen::Map<Eigen::Matrix<float,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>,std::allocator<Eigen::Map<Eigen::Matrix<float,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>>> &' ./Header.h(21): note: see declaration of 'MyCppFunction'


到目前为止我的分析:

这可以按预期工作,因此:我可以将 python 分配给listC int++ std::vector<int>

这也可以按预期工作,因此:我可以将 type 的变量分配给 typeeigency::FlattenedMap<Eigen::Matrix,float,-1,-1,1,0,0,0,-1,-1>的变量Eigen::Map<Eigen::Matrix<float,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>

当我将后两个变量包装在列表/向量中时,我无法将此变量分配给 std::vector<eigency::FlattenedMap<Eigen::Matrix,float,-1,-1,1,0,0,0,-1,-1>, std::allocator<eigency::FlattenedMap<Eigen::Matrix,float,-1,-1,1,0,0,0,-1,-1>>>类型的变量std::vector<Eigen::Map<Eigen::Matrix<float,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>, std::allocator<Eigen::Map<Eigen::Matrix<float,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>>>

也许它与分配器部分有关,但我不知道,因为我不是真正的 C++ 专家。有人有解决方案将 Numpy 矩阵列表映射到 Eigen 矩阵向量吗?最好遵循与上述相同的模式,但也欢迎其他解决方案。


我要重现的源代码:

下面是我用来测试的源代码。它有一个接受普通 Eigen/Numpy 矩阵的函数,以及一个接受 Eigen/Numpy 矩阵的向量/列表的函数。

如果您注释掉向量变体的所有段落,代码就会编译。否则,我得到一个编译错误。我在编译时得到的(第一个)编译错误是:.\source_cpp_cython/cpp_source_cpp.h(16): error C2065: 'FlattenedMapWithOrder': undeclared identifier.

我在 Windows 上使用 Microsoft Visual Studio 编译器 (MSVC) 2019。如果相关,我还使用 Eigen 版本 3.4.0-rc1。

cython_source.pyx

# distutils: language = c++
# distutils: sources = source_cpp_cython/cpp_source_cpp.cpp


from eigency.core cimport *  # Docs: https://pypi.org/project/eigency/1.4/
from libcpp.vector cimport vector
import numpy as np

cimport numpy
cdef extern from "source_cpp_cython/cpp_source_cpp.h":
    cdef float _MyCppFunction "MyCppFunction"(
                FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor] &
                )

    cdef float _MyCppFunctionVector "MyCppFunctionVector"(
                vector[FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor]] &
                )


def my_python_function(np.ndarray[ndim=2, dtype=np.float32_t] my_matrix):
    cdef FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor] my_matrix_cpp

    my_matrix_cpp = FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor](my_matrix)

    return _MyCppFunction(my_matrix_cpp)


def my_python_function_vector(list my_matrix_list):
    cdef vector[FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor]] matrix_map_vec
    cdef FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor] my_matrix_cpp

    for my_matrix in my_matrix_list:
        my_matrix_cpp = FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor](my_matrix)
        matrix_map_vec.push_back(my_matrix_cpp)

    return _MyCppFunctionVector(matrix_map_vec)

cpp_source_cpp.h

#pragma once
#include <Eigen/Dense>
#include <Eigen/Core>

#include <vector>
#include <numpy/ndarraytypes.h>
#include <complex>
typedef ::std::complex< double > __pyx_t_double_complex;
typedef ::std::complex< float > __pyx_t_float_complex;
#include "eigency_cpp.h"

float MyCppFunction(
    const Eigen::Map<Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>& inputMatrix
    );

float MyCppFunctionVector(
    const std::vector<FlattenedMapWithOrder<Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>>& inputMatrixList
    );

cpp_source_cpp.cpp

#include "cpp_source_cpp.h"

float MyCppFunction(
    const Eigen::Map<Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>& inputMatrix
    )
{
//    std::vector<FlattenedMapWithOrder<Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>> test;
    return 5.0;
}

float MyCppFunctionVector(
    const std::vector<FlattenedMapWithOrder<Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>>& inputMatrixList
    )
{
    //Convert FlattenedMap to Eigen-Map.
    std::vector<Eigen::Map<Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>> convertedMatrixList(
                                                                                                            inputMatrixList.begin(), inputMatrixList.end() );
    return 6.0;
}

我的 cython 设置文件setup_cython_module.py中的相关段落是:

# Some constants
SOURCE_FOLDER_NAME = "source_cpp_cython"
OUTPUT_FOLDER_NAME = "cython_module"

# Build extensions list
extensions = [
    Extension(f"{OUTPUT_FOLDER_NAME}.{OUTPUT_FOLDER_NAME}",
              [f"{SOURCE_FOLDER_NAME}/cython_source.pyx"],
              include_dirs=["."] + [f"{SOURCE_FOLDER_NAME}"]
                           + [f"{SOURCE_FOLDER_NAME}\Eigen"] + eigency.get_includes(include_eigen=False)
                           + [numpy.get_include()],
              language='c++',
              # extra_compile_args=['/MT'],  # To let the Microsoft compiler use a specific lib for threading required by OpenCV.
              )
    ]

# Build cython package
dist = setup(
    name=f"{OUTPUT_FOLDER_NAME}",
    version="1.0",
    ext_modules=cythonize(extensions, language_level="3"),  # , gdb_debug=True),
    packages=[f"{OUTPUT_FOLDER_NAME}"]
    )

Cython 的完整日志输出:

Created output directory:  D:\Default_Folders\Documents\Development\RepoStefan\CythonTest\cython_module

running build_ext
building 'cython_module.cython_module' extension
C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30037\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -IC:\ProgramData\Miniconda3\envs\cenv38rl\lib\site-packages\eigency -I. -Isource_cpp_cython -Isource_cpp_cython\Eigen -IC:\ProgramData\Miniconda3\envs\cenv38rl\lib\site-packages\numpy\core\include -IC:\ProgramData\Miniconda3\envs\cenv38rl\include -IC:\ProgramData\Miniconda3\envs\cenv38rl\include "-IC:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30037\ATLMFC\include" "-IC:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30037\include" "-IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.19041.0\ucrt" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.19041.0\shared" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.19041.0\um" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.19041.0\winrt" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.19041.0\cppwinrt" /EHsc /Tpsource_cpp_cython/cython_source.cpp /Fobuild\temp.win-amd64-3.8\Release\source_cpp_cython/cython_source.obj /MT
cl : Command line warning D9025 : overriding '/MD' with '/MT'
cython_source.cpp
C:\ProgramData\Miniconda3\envs\cenv38rl\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(14) : Warning Msg: Using deprecated NumPy API, disable it with #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
.\source_cpp_cython/cpp_source_cpp.h(17): error C2065: 'FlattenedMapWithOrder': undeclared identifier
.\source_cpp_cython/cpp_source_cpp.h(17): error C2275: 'Eigen::Matrix<float,-1,-1,1,-1,-1>': illegal use of this type as an expression
.\source_cpp_cython/cpp_source_cpp.h(17): note: see declaration of 'Eigen::Matrix<float,-1,-1,1,-1,-1>'
.\source_cpp_cython/cpp_source_cpp.h(17): error C2974: 'std::vector': invalid template argument for '_Ty', type expected
C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30037\include\vector(443): note: see declaration of 'std::vector'
.\source_cpp_cython/cpp_source_cpp.h(17): error C2976: 'std::vector': too few template arguments
C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30037\include\vector(443): note: see declaration of 'std::vector'
.\source_cpp_cython/cpp_source_cpp.h(17): error C2143: syntax error: missing ')' before '>'
.\source_cpp_cython/cpp_source_cpp.h(17): error C2059: syntax error: '>'
.\source_cpp_cython/cpp_source_cpp.h(18): error C2059: syntax error: ')'
source_cpp_cython/cython_source.cpp(1964): error C2664: 'float MyCppFunctionVector(const std::vector)': cannot convert argument 1 from 'std::vector<eigency::FlattenedMap<Eigen::Matrix,float,-1,-1,1,0,0,0,-1,-1>,std::allocator<eigency::FlattenedMap<Eigen::Matrix,float,-1,-1,1,0,0,0,-1,-1>>>' to 'const std::vector'
source_cpp_cython/cython_source.cpp(1964): note: No user-defined-conversion operator available that can perform this conversion, or the operator cannot be called
.\source_cpp_cython/cpp_source_cpp.h(16): note: see declaration of 'MyCppFunctionVector'
error: command 'C:\\Program Files (x86)\\Microsoft Visual Studio\\2019\\Community\\VC\\Tools\\MSVC\\14.29.30037\\bin\\HostX86\\x64\\cl.exe' failed with exit status 2

Process finished with exit code 1

非常感谢你!

标签: pythonc++numpycythoneigen3

解决方案


感谢@ead,我找到了解决方案。

FlattenedMapWithOrder具有实现,因此可以将其分配给Eigen::Matrix. 但是,std::vector不具有此类功能,并且由于std::vector<FlattenedMapWithOrder>std::vector<Eigen::Matrix>属于不同类型,因此它们不能相互分配。更多关于这里的信息。FlattenedMapWithOrder上面提到的实现在这里

为了解决这个问题,从 Cython 调用的 C++ 代码中的函数只需将匹配类型作为输入参数:std::vector<FlattenedMapWithOrder>. 为此,C++ 代码需要知道 type 的定义FlattenedMapWithOrder

为此,您需要#include "eigency_cpp.h". 不幸的是,此标头不是自包含的。因此,(感谢@ead)我添加了以下几行:

#include <numpy/ndarraytypes.h>
#include <complex>
typedef ::std::complex< double > __pyx_t_double_complex;
typedef ::std::complex< float > __pyx_t_float_complex;
#include "eigency_cpp.h"

使用它,我可以在我的 C++ 代码中声明这个函数:

void MyCppFunctionVector(
    const std::vector<eigency::FlattenedMap<Eigen::Matrix, float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>& inputMatrixList,
    std::vector<eigency::FlattenedMap<Eigen::Matrix, float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>& outputMatrixList
    );

我的 *.pxy 文件如下所示:

cdef extern from "source_cpp_cython/cpp_source_cpp.h":
    cdef void _MyCppFunctionVector "MyCppFunctionVector"(
                vector[FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor]] &,
                vector[FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor]] &
                )
                
                
def my_python_function_vector(
        list my_matrix_list_input,
        list my_matrix_list_output
    ):
    cdef vector[FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor]] matrix_map_vec_input
    cdef FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor] my_matrix_input_cpp
    cdef vector[FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor]] matrix_map_vec_output
    cdef FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor] my_matrix_output_cpp

    # Convert input matrix to C++ type.
    for my_matrix_input in my_matrix_list_input:
        my_matrix_input_cpp = FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor](my_matrix_input)
        matrix_map_vec_input.push_back(my_matrix_input_cpp)

    for my_matrix_output in my_matrix_list_output:
        my_matrix_output_cpp = FlattenedMapWithOrder[Matrix, float, Dynamic, Dynamic, RowMajor](my_matrix_output)
        matrix_map_vec_output.push_back(my_matrix_output_cpp)

    # Call the C++ function.
    _MyCppFunctionVector(matrix_map_vec_input, matrix_map_vec_output)
    return my_matrix_list_output                
    

就是这样。


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