Huh, didn't realize base PyTorch had an equivalent Sequential API.
The point about the better API overall still stands (notably including the actual training part, as base PyTorch requires you to implement your own loop)
Some people would say that this is an advantage of PyTorch, that it is very easy to write and play around with your own loop.
But if you don't want that, if you want to go a bit higher level w.r.t. training, there is e.g. PyTorch Lightning on top of PyTorch.
If you say the API is better in Keras, can you give any examples? They look kind of similar to me. Keras looks a bit more complicated, esp when looking at the internals (which I tend to do often, to better understand what's actually happening), which is a negative point.
Adding keras abstractions on top of pytorch seems like negative value-added to me. It only barely abstracts more the easy/mundane stuff, while creating yet another layer of indirection between ideas and machine code in the current Rube-Goldberg mess that people call modern ML.
Keras has always been "lipstick on a pig for tensorflow". Its value beyond that seems tenuous at best.
The point about the better API overall still stands (notably including the actual training part, as base PyTorch requires you to implement your own loop)