A guy from Google Brain came over to a Capital One meetup and talked at length about the `autograph` module; check it out! I remember they did some neat things with extending Python's operator overloading in order to generate Tensorflow graph code.

Couldn't find anything about it, but does anyone know if it supports Python 3.7 yet? Just messed around with TF yesterday on a Windows dev box, and the version downgrade shuffle was annoying.

Are the changes between ~1.13 and 2.0 finalized yet? Last I checked they were still in flux, outside of a few blog posts which state that config defaults changed: https://medium.com/tensorflow/whats-coming-in-tensorflow-2-0...

Biggest change for me is it seems like there's more of an incentive to use tf.keras instead of external Keras, for simplicity.

Can someone summarize the changes between 1.13 and 2.0? Given the major version increment, I'd assume there's a major paradigm shift.

Is the source code available for this 2.0 preview? I'd like to look at whatever changes there are in the C++ API.

What's interesting about Google is, they can have open source products that are hated a big % of devs (Angular) and something that doesn't have that problem (Tensorflow).

I wonder what's the underlying issue behind this disparity. Wonder if it the teams themselves behind those products...

Maybe it's the software itself and nothing associated with it. When something is 'Google' it's not automatically good or bad.

A lot responses challenging your Angular-is-hated claim, but I'd like to challenge your other one.

Tensorflow is not necessarily the most loved framework, despite it being in python, and being around for years now. This is in stark contrast to the way TF was marketed and hyped up, as the f/w that's going to take over the world of DL. That clearly didn't happen.

I think torch/pytorch is more popular (but don't quote me on that). And there are about half-a-dozen more competing with these two.

Putting two and two together, Angular and TF likely have more similarities than differences when it comes to community response.

I think "hated" is a too strong a word here. They're releasing software that they use themselves and I think there are hits and misses in large part based upon how closely your own processes and what you're trying to accomplish match up with what Google is trying to do.

I'm no fan of Angular but that's a bit harsh.

Surely it's just the difference between a product for mass consumption and a niche one.

Old opinions strongly held. I think Angular 1 left a bad taste in peoples mouths and that gets carried over in perpetuity. Take php for example, I'm sure you can find plenty of devs who haven't touched php in 10+ years but will still say they despise it.

Angular is hated? Angular is my only way out of Javascript fatigue, it just works.

you might not be aware but there is a lot of unhappiness with TensorFlow in the community. For example, I hear many comments about how complex it is, how hard the basic API is to use, how many random parts it's acquired. Most of those people point at Torch, and in fact tensorflow is adopting some of Torch's approaches for this reason.

It will be interesting to see if tensorflow retains a fairly high level of popularity over time. The 1->2 transition is a big risk for them because so many people are on TF 1, there's a ton of intrusive changes.

There’s some frustration with tensorflow too. It often feels like there are a dozen different, somewhat incompatible ways to do 90% of something.

In the academia people prefer PyTorch over TensorFlow.