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Comment by machinekob | Hacker News Reader

I strongly agree with readability in my opinion its cause Academia people live in "bubbles" and they assume everyone knew what a domain specific terms and greek letters means so its easier to read some omega then for example learning_rate or lr.

But for us mortal who cross multiple domains its just getting extremely frustrating to read full math based notation without any extra info about notation in package/functions etc. so debugging multiple sub-packages is just getting too time consuming as you have to learn both person style of writing code, whole scientific notation and get domain knowledge before you can even touch the code.

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> Academia people live in "bubbles" and they assume everyone knew what a domain specific terms and greek letters

Naming things by their English name is not more universal than using Greek letters. It's just serving amother group of people who live in a different bubble.

Yes and no, the example that the author gives is actually a very good one:

> Many Julia APIs look like Optimiser(η=...) rather than Optimiser(learning_rate=...). This is a pretty unreadable convention.

The learning rate is a well known name that basically every one will understand, on the other hand, "η" or eta, is not even used everywhere in the literature with some papers using alpha instead.

This just looks clever, it's a pretty bad parameter name.

> The learning rate is a well known name that basically every one will understand

Absolutely! Because as we all know, everyone speaks English.

The GP's point was that greek letters are used in lots and lots of papers even written in other languages. I have read quite a few papers in Japanese that used exactly the same conventions with respect to the greek letters and latin letters used.

How many researchers in the ML/DL community don't speak English? I don't have hard numbers but I highly doubt that it's a significant proportion. What is the reach of your Japanese papers when almost no-one outside of Japan can read Japanese?

Even China, despite their best effort to de-westernize their culture still uses English in their research papers.

And if all the above wasn't enough, Julia's libraries are still all in English so if an hypothetical researcher's English is so poor that they don't know what "learning rate" is, I'd venture that they'll have trouble programming in Julia/JAX/PyTorch.

How many don't speak it as a native language? Quite a lot as most of the world uses something else as their primary language.

If you're instead asking of how many can struggle trough an english text supported by machine translators, then that's clearly almost everyone.

There's very often a significant gap between the ease with which the native and the foreign language can be used for reasoning, but surely I don't need to point that out since any bilingual person knows this.

The programming language is already in English, implying that using greek letters to map to math concepts is easier to understand for non-native is disingenuous.

It's really not. There are just a few programming language-specific keywords that you have to memorize, unlike infinite possible combinations of English words for parameters.

edit: as an example, when programming for Brazilian businesses, we generally just use a mix and match of Portuguese and English like getFinanciamento. "Get" is a technical concept while "Financiamento" is a business concept and it often doesn't make sense to translate either. Best just to leave them both in their respective domain-native language.

In case of maths, Greek IS the domain native language. Now, I wouldn't necessarily enjoy a codebase with Unicode variables for other reasons, but using Greek is best to map directly from the equations.

I am not debating the merits of writing your business logic in whatever language that you want.

Flux, the Julia framework that we are discussing, is in English. Its classes, function names, optimizers, everything is in English. Keeping parameters as Greek letters and arguing that it's easier to understand is insanity.

I am replying to a comment in which you were talking in general terms. Maybe it's insanity because typing Greek symbols in most general-purposes IDEs is hard, querying it in search engines can be tough, etc. Not because it's mixed with English names.

Classes are a programming concept, they do map to the programming domain. Even optimizers and functions probably do map to a named mathematical concept, not to a Greek letter. But prameters probably map to a specific symbol in an equation.

In Mathematica, for instance, we use Greek letters and it allows you to just type an equation in the proper visual form. So much easier to map it when you're working with the actual domain-native names and formats.

Google Translate is one click away. I can easily translate both Japanese and Chinese comments and variable names to get the gist of it. Using single hieroglyphs for it makes the entire endeavor impossible.

So, you are fine with google translating variable names but you absolutely cannot interpret symbols? Wow.

Still better to google translate the meaning of 学习率 than do the same on eta...

That's ridiculous.

> Absolutely! Because as we all know, everyone speaks English.

I understand the sentiment here, especially as English is not my native language, but for many domains, for anything close to the state of the art, English is lingua franca.

I can assure you that more people exist with B1 knowledge of english then folks that have at least minimum knowledge of all math and computer science related domains that are used for deep learning (even subset like audio/video) even if we use only using software engineers/ml engineers as reference you have so much domain knowledge needed to even consider reading notation (without proper explanation in docs).

And most of the variables in code still will be in english or other natural language so it is just easier to read english then read math notation mixed with english/other language for MOST (not all) people using underlying software.

> Naming things by their English name is not more universal than using Greek letters.

It is - the people who understand the Greek-letter notation will understand the English words but the inverse statement isn't always true.

You're entirely ignoring the size of the bubbles.

I agree, and from my math/APL bubble, let me have my succinct symbols. I invoke the famous Iverson 1979 Turing Award Lecture, "Notation as a Tool for Thought" [1]. If you are in ML and do math to some degree, learn the symbols; it's more than just about succinctness.

[1] https://www.eecg.utoronto.ca/~jzhu/csc326/readings/iverson.p...

I understand both camps but I believe, these are superficial problems. It's like worrying about the comfort of seat in the operating room of a nuclear plant.

Exactly. I actually find Julia's ecosystem (not the language) way more approachable than Python's.

In Python, most libraries are big monoliths. Whereas in Julia, libraries are small and composable. Furthermore, it's the same language all the way down.

Python's libraries are superb, but the learning curve to develop (not to use them) is really steep.

I don't understand. What do you mean by "learning curve to develop" an existing Python library?

I imagine it has to do with the fact that lots of python libraries are mostly c/c++ or fortran, while Julia packages are usually just Julia.

Python's story for package development is a mess compared to Julia. If you know what you're doing you can make a new Julia package in the general registry with unit tests, CI, and code coverage in about 30 minutes.

To contribute to an existing repository, you can ]dev the package to download the git repository, @edit a function to open the source in an editor, and push the changes to a PR in about 10 minutes. This makes it much easier for package users to turn into package developers.

I've contributed to a bunch of Julia libraries that if I still used python, I wouldn't have contributed to the equivalent python library because contributing to Julia packages is at least an order of magnitude easier.

superficial you say. How about I name these in chinese in my package?

Sure, just try to properly document what it does. There are some characters that are easily confused at first glance even for native speakers, so be sure to use some common sense.

You're annoyed to the point of overreaction I'd say. I assume julia's devs use symbols that are culturally set already. Not just random glyphs for no good reason.

I've seen this in math, I come the dev land around java peak, where it was a holy trait to write runComputationThatIsMaybeSafeOverArguments(...), because that's where they though information was. In math they lived in the opposite side of things.. names were few and concision was more important. Also structural thinking made names really unimportant, mostly redundancy and waste of time, the domain and properties were.

I may be wrong though.

And if you ever do want to edit the code, you have to know the name of every non-ASCII symbol the codebase uses if you want to type out those same symbols without copying and pasting them. If you're not familiar with the material, entering a character like ξ can be a real challenge, and is actually more keystrokes than just typing "xi".

Difference is 1 keystroke: you type \xi. Why is that a "real challenge"?

What editors does this work in?

Juno, Jupyter support it out-of-the-box. With plug-ins: VS Code (unicode-latex), Atom (latex-completions), Emacs (which has TeX input), Vim (latex-unicoder), ...

Any editor, on Linux, if you have your keyboard set up to type Greek letters and the Unicode symbols that you use frequently. I can do it directly in the comment box: ξ

The challenge comes from a person like me, who doesn't know off the top of my head which Greek letter ξ is. So for each of these symbols I'd have to google them and learn it, or have some notepad where I can copy paste the needed symbol

So you don't know the Greek alphabet, but write high-performance computing code involving non-trivial math? (Julia's main use case is HPC)

The author example is using the greek letter "eta" instead of spelling out "learning_rate", this is a pretty damning example.

What? Did you not read the parent of this thread?

> strongly agree with readability in my opinion its cause Academia people live in "bubbles" and they assume everyone knew what a domain specific terms and greek letters means

In any case, I program HPC stuff myself with pytorch and no - I don't know the Greek alphabet and probably don't understand "non trivial math". The assumption that these people can't contribute is pretty off-putting honestly. More engineers would join such efforts if there wasn't so much gatekeeping.

So you think there's a cabal of "gatekeeper" scientists who are trying to hold the hordes of capable (yet somehow unfamiliar with the corresponding mathematical literature) engineers from making useful contributions to their libraries, because they use the conventional notation from the scientific literature?

They should instead tread carefully and dispose of all Greek letters in their code to ensure you are not put off, because that's the real reason that stops you from making useful contributions?

> So you think there's a cabal of "gatekeeper" scientists

No. I suggested I myself have seen gatekeeping and referenced your comment as example. Make of that what you will, but don't extrapolate it to a conspiracy theory I didn't suggest.

You should probably take the time to learn the names of the Greek letters. There are only 24 of them and they're even related to the English ones. It's not a huge time investment, and it's probably worth it if you work in engineering.

Sure, and that works great with rg and grep.

For me it’s one keystroke, with the dead-Greek modifier key.

I’ll do it right here, by typing <G-x>: ξ

How do you go from reading ξ to saying "oh I need to press <G-x>" ?

Because I recognized the Greek letter that we usually represent in English as “xi”. In fact I wasn’t sure, but I guessed x, and it turned out to be right. For each letter there’s usually one obvious latin-alphabet equivalent.

I bet you know right away how to type α and β.

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