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Python vs. Rust for Neural Networks

ngoldbaum.github.io

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Re: Python vs. Rust for Neural Networks

#41

Post by skohan »

kuzehanka wrote: post #20
tanilama wrote: post #12

Nobody writing NN in Python, they are just describing it. For NN or DL in general, the correctness doesn't really lie too much on the code quality level, like ownership Rust people love to talk about. It is more about Numeric stability under/overflow and such. Choice of programming language offers limited help here. I don't think Rust has a killer app for ML/DL community to offer as of now, the focus is vastly differ…

I've had a few Rust lovers come and mention this project to me recently. None of them had any data science or ML experience. None of them knew that Python is just used to define the high level architecture. At the same time, comparatively tedious languages like Rust will never attract data science practitioners. They don't care about the kind of safety it brings, they don't care about improving performance in a compo…

This is why I think Swift is a much better choice to replace or at least compliment Python than Rust. It has a modern, powerful type system and all the quality of life advantages which come with it, but it manages this with a lot more usability than Rust.

A well written swift framework almost becomes a DSL for the problem domain, which is a great property for a data science tool to have.

Re: Python vs. Rust for Neural Networks

#42

Post by wokwokwok »

kuzehanka wrote: post #38
wokwokwok wrote: post #36

Earlier quoted context omitted.

> They don't care about the kind of safety it brings, they don't care about improving performance in a component that's idle 99% of the time. https://www.fast.ai/2019/03/06/fastai-swift/ : > Because Swift for TensorFlow is the first serious effort I’ve seen to incorporate differentiable programming deep in to the heart of a widely used language that is designed from the ground up for performance. > But Python is not…

...But fast.ai is a Python library. Partially written in swift. Validating the original point that nothing will replace python for DL applications any time soon but middleware will continue to be implemented in c++/rust/swift/whatever you fancy. S4TF isn't the first and certainly not the last end to end non-python DL stack. It might be worth highlighting as an example if it ever reaches mindshare above the noise floo…

> Our hope is that we’ll be able to use Swift to write every layer of the deep learning stack, from the highest level network abstractions all the way down to the lowest level RNN cell implementation. There would be many benefits to doing this...

Well, the tldr: you’re wrong.

The more approachable reading: python isn’t going anywhere, but people are looking at other things for more than just low level implementations with a python wrapper.

...it’s early days yet, who knows where things will go... but maybe do a bit more reading and have an open mind?

There’s more to life than python.

Re: Python vs. Rust for Neural Networks

#43

Post by timClicks »

I think it's quite impressive actually that someone can pick up Rust and manage to out-perform Numpy in their first project. BLAS implementations are decades-long exercises in optimization.

In my own experience, Rust has been excellent for the more boring side of data science - churning through TBs of input data.

Re: Python vs. Rust for Neural Networks

#44

Post by fulafel »

tanilama wrote: post #12

Nobody writing NN in Python, they are just describing it. For NN or DL in general, the correctness doesn't really lie too much on the code quality level, like ownership Rust people love to talk about. It is more about Numeric stability under/overflow and such. Choice of programming language offers limited help here. I don't think Rust has a killer app for ML/DL community to offer as of now, the focus is vastly differ…

Numerical stability sounds like floating point artifacts are a problem, could a specification/verification language with more exact arithmetic semantics help?

Re: Python vs. Rust for Neural Networks

#45

Post by sharpneli »

fulafel wrote: post #44
tanilama wrote: post #12

Nobody writing NN in Python, they are just describing it. For NN or DL in general, the correctness doesn't really lie too much on the code quality level, like ownership Rust people love to talk about. It is more about Numeric stability under/overflow and such. Choice of programming language offers limited help here. I don't think Rust has a killer app for ML/DL community to offer as of now, the focus is vastly differ…

Numerical stability sounds like floating point artifacts are a problem, could a specification/verification language with more exact arithmetic semantics help?

Its not about floating point artifacts. Especially as full IEEE floats are completely deterministic and have exact semantics.

It’s something more fundamental. Similar issues happens elsewhere in numerical computation. See https://en.m.wikipedia.org/wiki/Numerical_stability

Re: Python vs. Rust for Neural Networks

#46

Post by skohan »

melling wrote: post #29
wokwokwok wrote: post #27

Earlier quoted context omitted.

> comparatively tedious languages like Rust will never attract data science practitioners. Well, fast.ai is using swift now. ... I think it's fair to say 'never say never'. You're probably right, rust isn't really the sweet spot for this stuff, but its also a case that python has some down sides that are pretty severe, and well acknowledged.

I wouldn’t call Swift a tedious language. With type inference, immutability, etc, Swift is far from tedious: http://www.h4labs.com/dev/ios/swift_cookbook.html?topic=stri... http://www.h4labs.com/dev/ios/swift_cookbook.html?topic=dict... It’s not quite as nice as Python but it’s an enjoyable language.

Python is easy to get started with, but once a project grows to any meaningful size, I would rather have a compiler which is giving me more correctness guarantees than Python is capable of.

IMO Swift strikes the best balance between strictness and productivity of any language I've worked with.

Re: Python vs. Rust for Neural Networks

#47

Post by wokwokwok »

chillee wrote: post #40
wokwokwok wrote: post #27

Earlier quoted context omitted.

> comparatively tedious languages like Rust will never attract data science practitioners. Well, fast.ai is using swift now. ... I think it's fair to say 'never say never'. You're probably right, rust isn't really the sweet spot for this stuff, but its also a case that python has some down sides that are pretty severe, and well acknowledged.

Just because fast.ai has some investment in Swift does not mean that S4TF has attracted mind share. The bulk of fast.ai is still taught on Pytorch.

The parent comment literally said data science practitioners don't care about speed or safety because the GPU is where all the real work happens; that's false, I've provided an example of it being false from a respected party. What do you want me to say?

eh, I give up. Believe whatever you want to believe.

Re: Python vs. Rust for Neural Networks

#48

Post by skohan »

antisemiotic wrote: post #35
frutiger wrote: post #33

Earlier quoted context omitted.

Rust has those too, GGGP still considered it tedious.

I think the tedious part would be the borrow checker. Also, Rust doesn't have top-level type inference (by design).

Yeah there is some tedium in general with Rust syntax. Semicolons, for example, feel old fashioned, and there's a lot of verbosity in things like unwrapping. It's a fine language and I like working with it, but there's a lot of details involved in Rust development which don't make sense for data scientists to worry about.

Re: Python vs. Rust for Neural Networks

#49

Post by gridlockd »

atoav wrote: post #21
tanilama wrote: post #12

Nobody writing NN in Python, they are just describing it. For NN or DL in general, the correctness doesn't really lie too much on the code quality level, like ownership Rust people love to talk about. It is more about Numeric stability under/overflow and such. Choice of programming language offers limited help here. I don't think Rust has a killer app for ML/DL community to offer as of now, the focus is vastly differ…

As somebody who programs in both Python and Rust (and likes both languages) I think Rust's place would be parts of the code that have to be fast, and that you want to get right. Calling Python code from Rust or Rust from Python is totally doable, and there is in my view no reason why you shouldn't use both in the use cases that suit them. And the speed part is serious. Some guy once asked for the fastest tokenizer in…

Calling C (or C++) code from Python is not only totally doable, it's what all the popular libraries do. Furthermore, most ML stuff runs on the GPU, which also is C-like code.

Hence, Rust offers no performance benefit that isn't already there. It really only offers safety and modern language features, at the cost of being tedious to use.

Re: Python vs. Rust for Neural Networks

#50

Post by disgruntledphd2 »

kuzehanka wrote: post #34
pjmlp wrote: post #31

Earlier quoted context omitted.

Rust might not be it. But AOT/JIT compiled languages that can naturally talk to the GPGPU, without 2nd language syndrome, like Julia, Swift, Java and .NET will certainly be more attractive to data science practitioners. I can already envision those life science guys that migrate to VB.NET when they have outgrown their Excel/VBA code, to start playing with ML.NET.

Python already gets JIT compiled to CUDA[1] and there's an entire funded ecosystem built around python+gpgpu called RAPIDS[2] which is the future of the ML space by most indicators. I don't see any other language even making a dent in the Python ecosystem without some kind of new killer feature that can't be quickly replicated in Python. [1] https://numba.pydata.org [2] https://rapids.ai

Thank you for the cite to rapids.ai, that looks extremely interesting :)
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