Does anyone else have to maintain backend PyTorch based services? Is it just me or is it a complete mess?

Members of my team have spent literal months tracking down memory leaks, the performance of these services are always sub-par to Tensorflow based ones and the less said about the atrocious memory/cpu usage the better.

What's the advantage of using PyTorch when you have things like Tensorflow Serving ready to productionize any model with ease?