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. Q:

C++ – How to export a struct containing derived class to python

I would like to export a struct from C++ to python. I have a c++ class which contains the following struct and class member variables.
struct ExampleClass
{
int varA;
int varB;
};

class DerivedExampleClass : public ExampleClass
{
int varC;
};

I would like to export the c++ class to python. I have tried the following
import exampleclass.ExampleClass as Example
import exampleclass.DerivedExampleClass as DerivedExample

but this does not work in python.
Is there a way to do this or is the python class interface not compatible with c++ derived classes?
UPDATE:
All answers work as far as it goes, however, I found that the python documentation does not describe the inheritance relationships between the classes when constructing a python class from C++ classes. For example, when attempting to expose a base class from a given example class in the first example, it did not work. When attempting to expose a base class from a given example class in the second example, it worked.
The following code was the one which did not work in the first example.
ExampleClass pClass;
int varA = 1;
int varB = 2

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Crack of Bdp hosteleria for macQ:

linking a CUDA.cu file to an executable

I have an executable (used to train a machine learning classifier) and a CUDA.cu file that needs to be called from it. I am trying to call an existing function f in the.cu file from the executable (both are in the same directory). I am using nvcc to compile the.cu file but I am not sure what is the appropriate calling statement.
I have tried these but neither has worked.
cuModuleSource(“updateMode.cu”, 0, 0, 0);
cuModuleLoad(“updateMode.cu”);

I have also tried to use the declaration as
extern “C”
{
__global__ void f(int *);
}

Any help on this would be much appreciated.

A:

You can make this work by putting your.cu file in the same directory as the executable. Then in the executable’s main code, call the function like this:
int main(void)
{
// Call whatever global function f() is defined in updateMode.cu
f(0);
return 0;
}

However, your.cu file will have to be compiled with -gpuDevicePath for the CUDA runtime to find the GPU on which it is running.
You can make this compile-time determination with this:
nvcc -x cu -Xcompiler -fPIC -g -I/somepath/include/maybe? -I/somepath/include/maybe2? -I/somepath/include/maybe3? -c -o updateMode.cu updateMode.cu

and use -gpuDevicePath on the compilation line for the executable. This will effectively compile the.cu file on the GPU itself.

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