How to pass an n-dimentional numpy array from python -> c++

[munkybutt]

I have a numpy array of numpy arrays of floats that I wish to pass to a c++ function that will read and modify the data as if it were a std::vector.
I am struggling to figure out how to do this.

What would the c++ argument type be for:
np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype=float)

This type declaration:
py::array_t<py::array_t<float>>
produces this error:
Attempt to use a non-POD or unimplemented POD type as a numpy dtype

I can't see to get this type declaration to work:
py:array

I have searched through documentation, github issues and examples I can find online but have not found anything that works or that I can make sense of, if anyone could help me with this, it would be much appreciated :)

[jiwaszki]

Can you add some reproducer? It seems quite unusual to encounter such error since pybind has a great basic out-of-the-box support for numpy.

Did you try using just replacing dtype with dtype=np.float32 and py::array with py::array_t<float>?
The thing is that dimensions are later provided inside buffer info. There is NO need to create arrays like vectors in C++. And that is probably a problem that throws an error as you try to template array with some "custom type" (in your case py::array<float>).

[munkybutt]

Thanks for the reply - sorry for the delayed response.
I got an answer on stack overflow which works, effectively using Eigen Matrices:
https://stackoverflow.com/questions/69831285/pybind11-how-to-pass-an-n-dimentional-numpy-array-from-python-c
The conversion is automatic and using the Eigen::Ref, there is no copying of data