Fully agree with Adrian. TF 2.0 isn't just a library that does GPU-accelerated computation, it's a ML platform and ecosystem spanning dozens of pieces, covering an incredible diversity of use cases. The scope and depth differ so much from PyTorch that you can't compare the two.https://twitter.com/PyImageSearch/status/1178999156909776896 …
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One of the biggest complaints I heard about TF 1.x and Keras was that it made it hard to for researchers to implement custom layers/losses/additional functionality. I think the combo of TF 2.0 and Keras addresses those complaints and makes it easier for both researchers & devs.
Absolutely, the main source of friction in 1.x was having two API silos, high-level Keras on one side and low-level TF on the other side, that weren't well integrated. One of the key innovations in TF 2.0 is to bridge this gap completely. Thread:https://twitter.com/fchollet/status/1178738070381678595 …
