I need some of the implementation of python in c++. Because of complexity in c++, I could not able to figure out how to achieve it in a simply and fastest way.
Note: I can implement in c++ using Eigen linear algebra library, because of time limit, I can not do this now.
So my question is, will it be possible to achieve the same implementation, especially, numpy part in the following link voxelization implementation using numpy in tensorflow c++ API or can I implement using tensorflow python and create a computational graph for the above implementation and link the output of per-processing graph to model graph as an input to use on hardware?
Use case of above question:
I have a neural network model for object detection using lidar point cloud. In the model author is doing the per-processing of data outside the graph. Since I need to provide the end model in C++, I thought of implementing the per-processing step in tensorflow C++ API. But after doing some research online, I got to know tensorflow c++ api does not support all the linear algebra operations yet like in tensorflow python API(one of my colleague told me this).
Any suggestions are most welcome.
Thanks in advance