Glad i could help(in some way lol)💯

https://github.com/jakeret/tf_unet

https://github.com/KUASWoodyLIN/TF2-UNet

As far as i know, if you create your own class inheriting from tf.keras, then that class can use .fit function. Eg class unet(tf.keras) Model_definition_as_per_arch model = unet() model.fit(data)

So you have the control to use your own model, and use keras's easy training loop as well.

Also, what do you mean by non model.fit? And why?

You can see abhishek thakur's video on the implementation of unet architecture. He explains it very well step by step. edit: i didnt see you wanted tf2.0. If i get some resources, will fwd it to you.