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Tensorflow sucks

nicodjimenez.github.io

61–70 of 133 posts

Re: Tensorflow sucks

#61

An appropriate quote: "If you can't intelligently argue for both sides of an issue, you don't understand the issue well enough to argue for either." There are many people for whom the declarative paradigm is a huge plus. I would say there are at least 2 major approaches in running fast neural networks: 1. Figure out the common big components and make fast versions of those. 2. Figure out the common small components a…

I took the article to be the counterpoint to the uninhibited praise of TF. In that light, I don't think it was meant as a balanced assessment of the whole product, but had a narrow scope of simply pointing out a handful of flaws that he thinks isn't discussed enough.

It's the same feeling when you hate a movie that everyone gives five stars: you might agree with some aspects of the praise (or even most of it), but that's not what you're going to be talking about. You'll talk about how and why it sucks compared to better movies.

I'd guess he could make a strong pro-TF argument if desired, but that just wasn't the point of this post.

Re: Tensorflow sucks

#62
post #57

Earlier quoted context omitted.

Nonsense, Pytorch is great in production. I use it for Mathpix (mathpix.com) which processes 20 million images per month.

About 8 images per second? How does that prove that Pytorch is great in production? I am not saying that Pytorch is bad in production but I fail to see how your metric of 8 images per second proves anything.

While you're absolutely right that vanity metrics prove nothing, it does prove that you can choose Pytorch for a production environment with a decent amount of traffic and be happy with your choice.

Re: Tensorflow sucks

#63
Like he tacks on at the end of the article, the reason most care about TensorFlow is because of TensorBoard making most of this a moot point. People would code while being hung upside down as long as they still get TensorBoard.

Re: Tensorflow sucks

#64
post #6

> Pytorch’s interface is objectively much better than Tensorflow’s Ummm. No. 'Objectively' is utter nonsense. For an objective view we would need to define "better" first and measure both interfaces performance. I think it is preference. I prefer the Tensorflow interface and don't mind it's declarative style. However, if one wants to criticize something one could start with the static nature of Tensorflow (which you…

In my experience (computer vision, deep learning) PyTorch is substantially faster as well, especially in data augmentation where it’s not just a thin layer over cudnn. That said, you’re right. There’s no way I’d deploy it to production.

> There’s no way I’d deploy it to production.

I've seen this stated by a few people, but never justified. What are some reasons for not deploying PyTorch in production?

Re: Tensorflow sucks

#65

Earlier quoted context omitted.

>An appropriate quote: "If you can't intelligently argue for both sides of an issue, you don't understand the issue well enough to argue for either." Cannibalism rules!

Lmao not sure why this was down-voted. Utterly destroyed your quotation, and gave me a giggle.

It didn't "utterly destroy" the quotation. It's pretty easy to argue the virtues of cannibalism, it's just that for modern day society they do not trump the downsides.

For example, cannibalism has successfully prevented death by starvation (e.g. the Donner Party), and it reduces the need for disposing of the dead. It's an application of reduce-reuse-recycle. Some species of other animals practice it as part of their normal lives (praying mantis as part of mating, lions as a social mechanic).

The very obvious counterpoints are that it's completely counter to modern cultural morality and it's been shown to increase likelihood of transferring brain parasites in humans.

The fact that you didn't even approach the other side and immediately concluded that he "destroyed the quotation" kinda shows that you aren't making the slightest effort to understand opposing viewpoints.

Re: Tensorflow sucks

#66
There are a few categories that I think TensorFlow is notably strong in. Namely:

1. Deployment. 2. Coverage of the library / built-in functionality. 3. Device management.

For more details, I wrote a comparison of PyTorch and TensorFlow (mostly from a programmability perspective) a couple months back. Interested readers may find it helpful. https://awni.github.io/pytorch-tensorflow/

Re: Tensorflow sucks

#67
I'm probably being overly cynical, but this is (indistinguishable from) a "growth-hack" submarine article by the author to promote their tool. There is hardly any substantiation to support the assertions. Tucked right at the end:

> If you want a beautiful monitoring solution for your machine learning project that includes advanced model comparison features, check out Losswise. I developed it to allow machine learning developers such as myself to decouple tracking their model’s performance from whatever machine learning library they use

Re: Tensorflow sucks

#68
post #41

I think the author raises a good point about Google envy. TensorFlow is not the most intuitive or flexible library out there, and it is very over-engineered if you're not doing large-scale distributed training. The main reason why everyone talks it up so much is because Google heavily marketed it from the outset, and everyone automatically assumes Google == Virtuoso Software Design because they couldn't make it throu…

Or maybe it is built by a company that is doing large-scale distributed training, and they open sourced it not to cater to every need, but to help others trying to do the same thing they are. Companies are under no obligation to make sure their open source is well suited for others use cases.

Re: Tensorflow sucks

#70
I'm not a comp-sci grad and I worked at Google for a bit after a startup I was at was acquired. I didn't proceed far after that 2 years due to the need to commute and/or relocate but I had a clear path into full time work without much else. Although I was granted a bit of a pass, I believe anyone can work at Google given they are 1) slightly above average and have learned every base that they run into in reasonable depth 2) motivated enough to try to interview at least a couple times including extensive "refreshing." Not many people pass the interview the first time so it's a +6 month play. Maybe longer. They look at progress from one interview to the next. Google is a big organization full of lots of people and not many of them are strictly that far above average. Maybe the Dunning Kruger effect may be shifting what I think of myself and the average developer there a bit but it's not unrealistic for any developer to think they can work there. It just takes interest and effort.
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