Debugging is a lot easier in PyTorch. Although you can debug the compiled graph in Tensorflow, from experience, the local state might not be the same in debug

Debugging is a lot easier in PyTorch. Although you can debug the compiled graph in Tensorflow, from experience, the local state might not be the same in debug mode as in compiled mode. Also, I've encountered strange performance regression issues with the newest Docker releases of Tensorflow, with 10x slow-downs compared to previous minor releases. And the docker version was always slower than the local version. Something something Nvidia & CUDA I guess. I had not performance differences with PyTorch when using docker. It should be said that Tensorflow was generally 10 to 20% faster for similar models. But that could be down to my ineptitude.