I am building library to execute deep learning models with limited memory. This library has custom implementations of standard routines(forward_pass, etc) written in C++. I have attempted to extend the files as explained from this tutorial. However, I have been having issues with dependencies between the library and Pytorch. As an alternate approach, I’m trying to utilize the library precompiled. I know that Pytorch uses the cuDNN library for CUDA. Is it possible to replicate that process for a custom library? I hope that shed some light on my question.
Thank you for your help!