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Comment by LeanderK | Hacker News Reader

> Tensorflow 2.0 will be a major milestone for the most popular machine learning framework: lots of changes are coming, and all with the aim of making ML accessible to everyone. These changes, however, requires for the old users to completely re-learn how to use the framework

I never felt like I was not re-learning tensorflow! A constant series of breackage, deprecations, new apis etc.

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Not to mention terrible documentation.

I think that’s a property of Google though, because there’s never been a google service for which I’ve read the documentation and not been like “I do not understand what’s going on at all” for a non-trivial amount of time.

And all their examples for Python are just like “run this magic-code-ridden python file, congrats you did the tutorial”.

Ok this is very useful to read, I also felt like that lately and I just thought I was an idiot. Now maybe we are just two idiots, or the documentation could use work.

Hello. Third idiot checking in.

Fourth idiot here!

Well, you should not start with TF documentation if you don't know how basic deep learning models work. Start with online courses

I wasn't talking about deep learning at all. I think most google technical docs suffer of a little bit of "and now draw the rest of the Owl" style.

I have a degree in maths and stats, I'm familiar with the underlying theory, it's not the deep learning part I'm struggling with, it's every bit of Google documentation about how their actual software does things that is incredibly confusing.

I thought I was the only one! Like, I must not be getting what those smart programmers are doing.

The breaking changes are quite well known, see Angular 1.x ~> 2.x, which is arguably a huge reason (but not the only one) why React took a big chunk of their market.

You should probably employ machine learning with TensorFlow to automatically update your broken code and remove usage of deprecated APIs.

priceless.

I feel it's a bit unfair to criticise changes in a product at the leading edge of the most dynamic field of software. It's also slightly ungrateful for such a valuable addition to OSS–and I say that even though I tend to consider this argument overused.

But mostly I don't believe such criticism has much of chance of changing anything: The creators are already the most qualified you could have working on it, and it's unlikely they intentionally made mistakes in the early rounds of API design. Maybe it would have helped to spend a few more weeks on specifications rather than coding but, again, I wouldn't feel very comfortable second-guessing Google's project management.

I think the most likely outcome if such complaints start to pile up would be future projects just remaining proprietary, either longer, of completely.

I really don't think so. Google doesn't make keeping up with tensorflow hard because of all the wonderful innovations, but because of needless breakage. Moving of packages, renaming things. It regularly breaks not-so-old code.

Also, I don't think I am ungreatful. It's a serious criticism of a software i use almost daily. I really don't consider tensorflow to be great or even some kind of software, but for some tasks it's the only option.

Also, google profits a lot from releasing tensorflow into the wild.

But, all in all, tensorflow 2.0 seems like a step in the right direction.

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