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What do you think of Keras in this space ? Because TF 2.0 is entirely keras based.

https://medium.com/tensorflow/standardizing-on-keras-guidanc...




This is one thing that confuses me. Why Keras is still a separate brand? Why everything isn't under just tensorflow namespace instead of having to do tf.keras all the time. I really wish tf just had one API and just one thing to learn.


Keras is a high level API that can use multiple backends. So it makes sense for them to remain separated.


I haven't used TF much lately, but the last time I looked at TF2 it felt like they are making it harder to build low level api models.


I doubt it, it's more likely that they are creating higher level abstractions atop the lower level ones and are advertising/documenting the higher level ones


Keras is part of the problem for me. It is rather rigid and it's hard to get around. Works super well for the regular use case. On the other hand, when you want to start doing custom stuff, it's hell.




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