I am fairly new to cython, and I was attempting to wrap a templated vector class defined as
template < typename T, uint N >
struct Vector{}
and I am having a difficult time learning about how cython uses templates, especially those with an int as an argument. I read in the docs that ints are not yet supported as template parameters. How do I do this properly?
For the curious, the Cython wiki shows how to write a templated class in Cython:
cdef extern from "<vector>" namespace "std":
cdef cppclass vector[T]:
...
Furthermore, multiple template parameters are defined as a list.
To answer the OP's question, one would use cdef struct Vector[T, N].
I found an easy solution!
In a C++ header file, you can just declare a typedef, for example
typedef Vector<float,3>; Vector3f;
In your cython file you can just declare that and now you can use all the functions and operators within the class.
cdef extern from "Vector.h" namespace "ns":
cdef cppclass Vector3f:
Now, I had an additional issue, and that is with "specialized" functions, in my case a specialization for a Vector with 3 params.
template<typename T1, typename T2>
inline Vector<T1, 3 >Cross(const Vector <T1, 3 > & v1, const Vector<T2, 3> & v2)
To use this in cython, just declare it outside the class, in my case
cdef extern from "Vector.h" namespace "ns":
cdef cppclass Vector3f:
...
Vector3f Cross(Vector3f v1,Vector3f v2)
Related
I am trying to wrap a simple C++ class that uses shared pointers and a very simple inheritance. I have a class Point that is a base class and SphericalPoint is it's child class. I have a vector of shared pointers of Points. I want the vector to hold the child class objects in it i.e. Spherical Points. There can be many child classes of Point and Spherical Point is only shown here for representation. When I do this I get the following compilation error -
point.pyx:18:13: Object of type 'shared_ptr[Point]' has no attribute 'setCoordinate1'
Error compiling Cython file:
point = shared_ptr[Point](new SphericalPoint())
cdef double latitude, longitude
latitude = 0.
longitude = 0.
point.setCoordinate1(latitude)
point.setCoordinate2(longitude)
point.pyx:19:13: Object of type 'shared_ptr[Point]' has no attribute 'setCoordinate2'
Initially when googling for this I thought the cause of the problem maybe because I do not have the keyword public in the Cython code but when I do add the keyword public I get a whole bunch of other errors. In the following link Wrapping C++ with Cython there is no example that shows public in the .pxd file.
Here is a MVCE that reproduces the problem. How can I fix this error ? Cython version is 0.29.7
Point.h
class Point {
private:
double coordinate1,coordinate2;
public:
virtual double getCoordinate1();
virtual double getCoordinate2();
virtual void setCoordinate1(double coordinate1);
virtual void setCoordinate2(double coordinate2);
};
class SphericalPoint : public Point
{
private:
double longitude,latitude;
public:
double getCoordinate1();
double getCoordinate2();
void setCoordinate1(double latitude);
void setCoordinate2(double longitude);
};
and this is my point.pxd file
cdef extern from "Point.h":
cdef cppclass Point:
Point() except +
double getCoordinate1()
double getCoordinate2()
void setCoordinate1(double coordinate1)
void setCoordinate2(double coordinate2)
cdef cppclass SphericalPoint(Point):
SphericalPoint() except +
double getCoordinate1()
double getCoordinate2()
void setCoordinate1(double coordinate1)
void setCoordinate2(double coordinate2)
And my point.pyx file
from libcpp.memory cimport shared_ptr
from libcpp.vector cimport vector
from point cimport Point
cdef class PyA:
cdef vector[shared_ptr[Point]]* points
def __cinit__(self):
self.points = new vector[shared_ptr[Point]]()
def buildPoints(self):
cdef shared_ptr[Point] point
point = shared_ptr[Point](new SphericalPoint())
cdef double latitude, longitude
point.setCoordinate1(latitude)
point.setCoordinate2(longitude)
UPDATE
I just moved the instantiation of the child classes to it's own separate method because it is not really part of cinit. But I still get the same compilation errors. I am also wondering whether the instantiation of the subclass SphericalPoint is the cause of the problem i.e.
point = shared_ptr[Point](new SphericalPoint())
Is this the recommended way ?
Cython can work this out for regular pointer types and generate c++ code with ->, however it isn't able to work this out for types that implement a pointer interface with operator overloading.
Instead you should use cython.operator.dereference.
from cython.operator cimport dereference
# ...
dereference(point).setCoordinate1(instance)
There's one thing I don't fully understand about the "nogil" applied to a cdef extern like this:
cdef extern from "pthread.h" nogil:
ctypedef struct pthread_mutex_t:
pass
cdef int pthread_mutex_init(pthread_mutex_t *, void *)
cdef int pthread_mutex_destroy(pthread_mutex_t *)
It isn't clear to me about the effect of that nogil, and I cannot find anything in the Cython's documentation about it. My interpetation is that the functions declared inside have the nogil implicitly. Am I right? And what about the struct?
Thanks for any info.
From Cython docs on binding with C code
The nogil function annotation declares that it is safe to call the
function without the GIL.
In your example, this means that the functions pthread_mutex_init and pthread_mutex_destroy are allowed in a with nogil block. In the absence of an explicit with nogil block, the GIL remains in place: it necessary but not sufficient to declare the function as done in the example.
Plain C variables can be used in the nogil blocks but you are responsible for the thread-safety.
I have a C++ function that accepts a callback, like this:
void func(std::function<void(A, B)> callback) { ... }
I want to call this function from Cython by giving it a closure, i.e. something I would have done with a lambda if I was calling it from C++. If this was a C function, it would have some extra void* arguments:
typedef void(*callback_t)(int, int, void*);
void func(callback_t callback, void *user_data) {
callback(1, 2, user_data);
}
and then I would just pass PyObject* as user_data (there is a more detailed example here).
Is there way to do this more in C++ way, without having to resort to explicit user_data?
What I believe you're aiming to do is pass a callable Python object to something accepting a std::function. You need to do create a bit of C++ code to make it happen, but it's reasonably straightforward.
Starting by defining "accepts_std_function.hpp" as simply as possible to provide an illustrative example:
#include <functional>
#include <string>
inline void call_some_std_func(std::function<void(int,const std::string&)> callback) {
callback(5,std::string("hello"));
}
The trick is then to create a wrapper class that holds a PyObject* and defines operator(). Defining operator() allows it to be converted to a std::function. Most of the class is just refcounting. "py_obj_wrapper.hpp":
#include <Python.h>
#include <string>
#include "call_obj.h" // cython helper file
class PyObjWrapper {
public:
// constructors and destructors mostly do reference counting
PyObjWrapper(PyObject* o): held(o) {
Py_XINCREF(o);
}
PyObjWrapper(const PyObjWrapper& rhs): PyObjWrapper(rhs.held) { // C++11 onwards only
}
PyObjWrapper(PyObjWrapper&& rhs): held(rhs.held) {
rhs.held = 0;
}
// need no-arg constructor to stack allocate in Cython
PyObjWrapper(): PyObjWrapper(nullptr) {
}
~PyObjWrapper() {
Py_XDECREF(held);
}
PyObjWrapper& operator=(const PyObjWrapper& rhs) {
PyObjWrapper tmp = rhs;
return (*this = std::move(tmp));
}
PyObjWrapper& operator=(PyObjWrapper&& rhs) {
held = rhs.held;
rhs.held = 0;
return *this;
}
void operator()(int a, const std::string& b) {
if (held) { // nullptr check
call_obj(held,a,b); // note, no way of checking for errors until you return to Python
}
}
private:
PyObject* held;
};
This file uses a very short Cython file to do the conversions from C++ types to Python types. "call_obj.pyx":
from libcpp.string cimport string
cdef public void call_obj(obj, int a, const string& b):
obj(a,b)
You then just need to create the Cython code wraps these types. Compile this module and call test_func to run this. ("simple_version.pyx":)
cdef extern from "py_obj_wrapper.hpp":
cdef cppclass PyObjWrapper:
PyObjWrapper()
PyObjWrapper(object) # define a constructor that takes a Python object
# note - doesn't match c++ signature - that's fine!
cdef extern from "accepts_std_func.hpp":
void call_some_std_func(PyObjWrapper) except +
# here I lie about the signature
# because C++ does an automatic conversion to function pointer
# for classes that define operator(), but Cython doesn't know that
def example(a,b):
print(a,b)
def test_call():
cdef PyObjWrapper f = PyObjWrapper(example)
call_some_std_func(f)
The above version works but is somewhat limited in that if you want to do this with a different std::function specialization you need to rewrite some of it (and the conversion from C++ to Python types doesn't naturally lend itself to a template implementation). One easy way round this is to use the Boost Python library object class, which has a templated operator(). This comes at the cost of introducing an extra library dependency.
First defining the header "boost_wrapper.hpp" to simplify the conversion from PyObject* to boost::python::object
#include <boost/python/object.hpp>
inline boost::python::object get_as_bpo(PyObject* o) {
return boost::python::object(boost::python::handle<>(boost::python::borrowed(o)));
}
You then just need to Cython code to wrap this class ("boost_version.pyx"). Again, call test_func
cdef extern from "boost_wrapper.hpp":
cdef cppclass bpo "boost::python::object":
# manually set name (it'll conflict with "object" otherwise
bpo()
bpo get_as_bpo(object)
cdef extern from "accepts_std_func.hpp":
void call_some_std_func(bpo) except + # again, lie about signature
def example(a,b):
print(a,b)
def test_call():
cdef bpo f = get_as_bpo(example)
call_some_std_func(f)
A "setup.py"
from distutils.core import setup, Extension
from Cython.Build import cythonize
extensions = [
Extension(
"simple_version", # the extension name
sources=["simple_version.pyx", "call_obj.pyx" ],
language="c++", # generate and compile C++ code
),
Extension(
"boost_version", # the extension name
sources=["boost_version.pyx"],
libraries=['boost_python'],
language="c++", # generate and compile C++ code
)
]
setup(ext_modules = cythonize(extensions))
(A final option is to use ctypes to generate a C function pointer from a Python callable. See Using function pointers to methods of classes without the gil (bottom half of answer) and http://osdir.com/ml/python-cython-devel/2009-10/msg00202.html. I'm not going to go into detail about this here.)
I am trying to wrap some C++ code into Cython and I came up with some trouble trying to pass a method from a class as an argument to a function.
I do not know if it makes it more clear, but class A represents a statistical model (so myAMethod uses not only the arguments passed but many instance variables) and B has different methods for minimizing the function passed.
In C++ I have something of this style:
class A
{
public:
double myAMethod(double*)
};
class B
{
public:
double myBMethod(A&, double (A::*f) (double*)
}
So what I am trying to do is to use instances of both A and B in Cython code. I had no trouble wrapping the classes, but when I try to use myBMethod, I don't know how to pass a pointer of the kind A::*myAMethod
If I do this:
myBMethod(ptrToAObj[0], &ptrToAObj.myAMethod),
then Cython compiles this code to [...] &ptrToAObj->myAMethod [...], and I get the message one would expect from g++:
"ISO C++ forbids taking the address of a bound member function to form a pointer to member function."
But if I try to point straight to the class method, and do myBMethod(ptrToAObj[0], A.myAMethod), then Cython won't compile and say that
myAMethod is not a static member from A.
And that's pretty much all I was able to advance. I could work at C++ level and avoid any of these anoyances, but if I were able to use instances of A and B in Python (via Cython) interactively, it would help me in speedig my development pace.
Any help will be really appreciated, and I apologize if this question as been already answered and/or is available in a referece - I search SO, Cython reference and Smith's "Cython" book and I did not found this theme adressed.
Thanks in advance!
I have a partial (if horrendous) solution. I'm prepared to believe there's a better way, but I don't know it.
In cpp_bit.hpp:
class A {
public:
double myAMethod(double*) { return 0.0; }
};
typedef double (A::*A_f_ptr)(double *);
class B {
public:
double myBMethod(A& a, A_f_ptr f) {
double x = 0.1;
return (a.*f)(&x);
}
};
A_f_ptr getAMethod() {
return &A::myAMethod;
}
I've given the functions very basic implementations, just so I can check for really obvious crashes. I've also created a function pointer which returns a pointer to myAMethod. You'll need to do this for every method you want to wrap.
In py_bit.pyx
# distutils: language = c++
from cython.operator import dereference
cdef extern from "cpp_bit.hpp":
cdef cppclass A:
double myAMethod(double*)
cdef cppclass A_f_ptr:
pass
cdef cppclass B:
double myBMethod(A&, A_f_ptr)
cdef A_f_ptr getAMethod()
cdef class PyA:
cdef A* thisptr
def __cinit__(self):
self.thisptr = new A()
def __dealloc__(self):
del self.thisptr
cpdef myAMethod(self,double[:] o):
return self.thisptr.myAMethod(&o[0])
cdef class PyB:
cdef B* thisptr
def __cinit__(self):
self.thisptr = new B()
def __dealloc__(self):
del self.thisptr
cpdef myBMethod(self,PyA a):
return self.thisptr.myBMethod(dereference(a.thisptr),getAMethod())
I couldn't figure out how to typedef a member function pointer in Cython, so instead I created an empty cppclass with the same name. This works because cython just seems to use it for type-checking and nothing more, and since it includes cpp_bit.hpp (where it's defined) you can use it no problem.
All I've done is left the task of getting the member function pointer to c++ (in getAMethod, which I call). I don't think it's entirely satisfactory, but it looks workable, and is only a short extra c++ function for every member function you want to access. You could play with where you put it to encapsulate it more cleanly.
An alternative, untested approach: (Edit: further thought suggests this might be very tricky! Attempt this at your own risk!)
Personally, I'd be tempted to change the c++ interface so that myBMethod is defined as
double myBMethod(std::function<double (double*)>)
(since presumably you always call it with the A instance it's passed with). Then use lambda functions in c++(11!) to wrap the A instance and function together
b.myBMethod([&](double* d){ return a.myAMethod(d) };
It may then take a bit of hugely complicated Cython wrapping that I haven't yet considered, but it should be possible to convert a simple double (double*) function pointer to the c++ function object, and so use it more directly.
It's also possible that your actual design is more complicated in ways I haven't considered, and this approach isn't flexible enough anyway.
I'm trying to wrap a C++ library in which the logic is implemented as templatized functors in .hpp files, and I'm struggling to find the right way to expose the C++ functors as Cython/Python functions. How are functors like the one below supposed to be wrapped in Cython?
I believe this should be possible, at least for template classes and functions, according to the Cython 0.20 docs.
Note: I think I've figured out how to wrap normal C++ functions—the problem occurs when I'm trying to wrap a templatized functor, i.e. a template struct that overloads the () operator (making it act like a function when a data type is fixed).
Disclaimer: I'm a total novice in C++ and very new to Cython so apologies if I'm making obvious mistakes here.
The functor I'm trying to wrap:
#include <vector>
#include "EMD_DEFS.hpp"
#include "flow_utils.hpp"
template<typename NUM_T, FLOW_TYPE_T FLOW_TYPE= NO_FLOW>
struct emd_hat_gd_metric {
NUM_T operator()(const std::vector<NUM_T>& P, const std::vector<NUM_T>& Q,
const std::vector< std::vector<NUM_T> >& C,
NUM_T extra_mass_penalty= -1,
std::vector< std::vector<NUM_T> >* F= NULL);
};
My wrapper.pyx file:
# distutils: language = c++
from libcpp.vector cimport vector
cdef extern from "lib/emd_hat.hpp":
# Apparently `cppclass` is necessary here even though
# `emd_hat_gd_metric` is not a class...?
cdef cppclass emd_hat_gd_metric[NUM_T]:
NUM_T operator()(vector[NUM_T]& P,
vector[NUM_T]& Q,
vector[vector[NUM_T]]& C) except +
cdef class EMD:
cdef emd_hat_gd_metric *__thisptr
def __cinit__(self):
self.__thisptr = new emd_hat_gd_metric()
def __dealloc__(self):
del self.__thisptr
def calculate(self, P, Q, C):
# What goes here? How do I call the functor as a function?
return self.__thisptr(P, Q, C)
The above just gives a Calling non-function type 'emd_hat_gd_metric[NUM_T]' error when I try to compile it with cython --cplus wrapper.pyx.
Here's the full library I'm trying to wrap.
End goal: to be able to call emd_hat_gd_metric as a Cython/Python function, with arguments being NumPy arrays.
I couldn't find a real solution, but here's a workaround (that requires modifying the C++ code): just instantiate the template function with the data type you need in the C++ header, then declare that function normally in your .pyx file.
It's a little unwieldy if you need many different data types, but I only needed double. It would also be nicer if it wasn't necessary to modify the external library… but it works.
In the C++ some_library.hpp file:
Instantiate the functor with the data type you need (say, double):
template<typename T>
struct some_template_functor {
T operator()(T x);
};
// Add this:
some_template_functor<double> some_template_functor_double;
In the Cython .pyx file:
Declare the function normally (no need for cppclass):
cdef extern from "path/to/some_library.hpp":
cdef double some_template_functor_double(double x)
Then you can call some_template_functor_double from within Cython.