Still pretty terrible compared to PyTorch _unless_ you need deployment to device, in which case it's basically the only game in town. Or at least the only _viable_ game.

Case in point: people are still trying to figure out on their github how to apply global weight decay when training a model, and to get a "correct" resize for segmentation you have to fall back to the legacy 1.x API and specify align_corners=true there. These bugs existed for many years, and nobody gives a damn. That said if your choice is between 1.x and 2.0, 2.0 is much easier to work with, especially if you use something other than TF (e.g. PyTorch) for data pipeline and augmentation. You can hook that up pretty seamlessly if you train in eager mode.