[ibab]

Do you also write your own automatic differentiation tools? Using libraries like TF and PyTorch makes sense if you use neural networks because they provide automatic differentiation (who wants to write out their gradients by hand?) and standard neural network components.

Edit: If your algorithm is not using neural networks, then libraries like TF may or may not be a good fit, it depends on the algorithm. Writing custom low-level code can still make sense in those cases.

[improbable22]

People do write their own AD tools... in a day, sometimes!

http://blog.rogerluo.me/2018/10/23/write-an-ad-in-one-day/

http://blog.rogerluo.me/2019/07/27/yassad/

Although the endpoint is likely to be a better understanding of the choices made by a mature implementation, and of the work involved in fixing up edge cases.