its been my observation that most researchers/DS prefer PyTorch because it lets them hack in python and most production software engineers will prefer models be written TF because of effortless portability and performance of TF Graphs.
I work on a team that does the latter and lately DS have been handing off PyTorch models that we cant scale or make performant because Torchscript doesnt really work with any realistic code complexity and authors include all sorts of random python libraries. So we can't load models in C++ or get them under 50ms.
So the framework divide very much feels like dynamic vs statically typed languages. People that dont have real production demands love dynamic languages for the productivity.
I work on a team that does the latter and lately DS have been handing off PyTorch models that we cant scale or make performant because Torchscript doesnt really work with any realistic code complexity and authors include all sorts of random python libraries. So we can't load models in C++ or get them under 50ms.
So the framework divide very much feels like dynamic vs statically typed languages. People that dont have real production demands love dynamic languages for the productivity.