Implementation differences in LSTM layers-- Tensorflow vs Pytorch

Tensorflow and Pytorch are the two most widely used libraries in deep learning. Both these libraries have different approaches when it comes to implementing neural networks. Both these libraries started with major differences. Usually, TF was more preferred for developing production-ready models due to its better optimizations, and Pytorch was preferred for research works due to its more "pythonic" syntax and eager execution. But with Torchscript and TF 2.0, the gap between the two libraries has shrunk.