5 ms·

oh this has code! great stuff. diffusion papers are famous for a lot of equations (https://twitter.com/cto_junior/status/1766518604395155830 https://twitter.com

by swyx 3y ago

oh this has code! great stuff. diffusion papers are famous for a lot of equations (https://twitter.com/cto_junior/status/1766518604395155830 https://twitter.com/cto_junior/status/1766518604395155830) but code is much more legible (and precise?) for the rest of us. all theory papers should come with reference impl code. i'd love an extension of this for the diffusion transformer, which drives Sora and other videogen models. maybe combine this post with https://jaykmody.com/blog/gpt-from-scratch/ https://jaykmody.com/blog/gpt-from-scratch/ and make the "diffusion transformer from scratch" intro

GaggiX 3y ago
>i'd love an extension of this for the diffusion transformer All you need to do is replace the U-net with a transformer encoder (remove the embeddings, and project the image patches into vectors of size n_embd), and the diffusion process can remain the same.
- swyx 3y ago
  seems too simple. isn't there also a temporal dimension you need to encode?
  - GaggiX 3y ago
    For the conditioning and t there are different possibilities, for example the unpooled text embeddings (if the model is conditioned on text) usually go in the cross-attn while the pooled text embedding plus t is used in adaLN blocks like StyleGAN (the first one), but there are many other different strategies.
godelski 3y ago
They're famous for lots of equations, but truth be told, most diffusion researchers I know have the exact same response. A lot of people repeat the same exact equations and they only are there for review purposes. On the other hand, if you want to really dig in, I'd suggest reading into works by Kingma, Gao, Ricky Tian Qi Chen, and honestly, any of Max Welling's students (Tomczak (was post doc), Hoogeboom, etc), and of course the unsung hero Aapo Hyvärinen. Here's a taste at a Kingma & Gao work that's on the lighter side but relevant to the SD3 paper. The unfortunate part is that there's a lot of reliance on knowing and understanding prior works which make these less approachable, but honestly this is a bit difficult to call a meaningful critique (it's research, not educational work aimed at public). https://arxiv.org/abs/2303.00848 https://arxiv.org/abs/2303.00848
- swyx 3y ago
  yeah fair enough :) i am unfortunately not driven enough on diffusion models yet to need to dive into those but i hope a future seeker finds your references here.
  - godelski 3y ago
    That's fine! Not everyone needs to be. I think it is just a shame we pretend. Makes research convoluted and messy. As I said the other day, we should just allow people to pursue whatever they want and lay a framework where the incentives drive the clearest explanations possible. https://news.ycombinator.com/item?id=39665427 https://news.ycombinator.com/item?id=39665427
- api 3y ago
  How long before more legible code or code-like constructs (or markup?) start to displace arcane mathematical notation? It would take quite a long time but I could see this slowly happening for analogous reasons to how the printing press favored alphabetic languages over pictorial ones. Computers teach us to read, write, and express linguistically and are now thanks to LLMs capable of working much more fluently with language. Squiggles and lots of Greek letters seem like an anachronism.
  - godelski 3y ago
    > How long before more legible code or code-like constructs (or markup?) start to displace arcane mathematical notation? My best guess is never. The problem is that math is a language itself. In fact, I'd more accurately call it a family of languages. People often confuse it for an inherent thing because most of the time we use it in applied ways for subjects like physics, and the sciences. But clearly those people have never taken abstract algebra or developed their own toy algebra (or group, ring (or rung), or field). You might say they have an _ideal_istic notion of mathematics. That said, I am absolutely sympathetic to the complexity of mathematics and there is so much that is difficult to grasp. What's worse, is that when this abstract gobbledy goop finally clicks it's so abundantly obvious that it deceives you into thinking you've known it all along. I think this contributes to the difficulty of teaching the subject because those qualified have forgotten the struggles they themselves have had (to be fair, human psychology plays a big role here too because if we only remember the struggles we'd have difficulty finding the passion and beauty). But I think our best hope is to find a unified mathematics. The obsession people have with things like set theory and category theory is that you can see this interconnectedness. You get this deep feeling that you're looking at the same things manifesting in different ways. Remember that a lot of mathematics is converting your system into another system (we might call this an isomorphic mapping) such that your problem is easier to solve in the other system (think about how we might want to go from Cartesian coordinates to polar, but now abstract that concept out more than your friend that took a few tabs of acid). You zoom out move around, and zoom back in, and maybe a few more times (but you have to keep track of your path). > Squiggles and lots of Greek letters seem like an anachronism. Do you have another suggestion? Because I don't see how code, English, or literally any other thing that can be written down is anything more meaningful than "a bunch of squiggles." There's only so many simple, and importantly, distinguishable squiggles that we can write down. Luckily we have a tool to exactly determine this ;) The shitty part of mathematics is also the best part, in that you have to embrace the abstractness of it all. But of course human brains weren't designed for this. (Yes, there are some of us trying to figure out how to get machines to think with that extreme level of abstractedness at its core. No, this is not how computers already "think.") So yeah, I empathize with you. Quite a lot. There's so much more that I want to know about this thing too. But it is often seemingly impenetrable. All I can tell you is that it just looks that way and isn't. Everyone has the capacity but finding the right way up this mountain (that I'm nowhere near Terry, and he's nowhere near the summit) can be just as hard as the climb itself. The best way is persistence though. Just remember that you don't play video games because they are easy. Sometimes you gotta just trick yourself into pushing through. And some of the best advice I can give is revisiting old topics. So much of what you think you've known actually has a tremendous amount of depth to it. Coming back with fresh eyes and a better understanding of the larger picture can help you see all the beauty in it, even if this is sometimes fleeting. I'm sorry to have vomited so much, but you know, Stockholm Syndrome is a bitch.

by swyx 3y ago

GaggiX 3y ago

>i'd love an extension of this for the diffusion transformer All you need to do is replace the U-net with a transformer encoder (remove the embeddings, and project the image patches into vectors of size n_embd), and the diffusion process can remain the same.

swyx 3y ago
seems too simple. isn't there also a temporal dimension you need to encode?
- GaggiX 3y ago
  For the conditioning and t there are different possibilities, for example the unpooled text embeddings (if the model is conditioned on text) usually go in the cross-attn while the pooled text embedding plus t is used in adaLN blocks like StyleGAN (the first one), but there are many other different strategies.

godelski 3y ago

They're famous for lots of equations, but truth be told, most diffusion researchers I know have the exact same response. A lot of people repeat the same exact equations and they only are there for review purposes. On the other hand, if you want to really dig in, I'd suggest reading into works by Kingma, Gao, Ricky Tian Qi Chen, and honestly, any of Max Welling's students (Tomczak (was post doc), Hoogeboom, etc), and of course the unsung hero Aapo Hyvärinen. Here's a taste at a Kingma & Gao work that's on the lighter side but relevant to the SD3 paper. The unfortunate part is that there's a lot of reliance on knowing and understanding prior works which make these less approachable, but honestly this is a bit difficult to call a meaningful critique (it's research, not educational work aimed at public). https://arxiv.org/abs/2303.00848 https://arxiv.org/abs/2303.00848

swyx 3y ago
yeah fair enough :) i am unfortunately not driven enough on diffusion models yet to need to dive into those but i hope a future seeker finds your references here.
- godelski 3y ago
  That's fine! Not everyone needs to be. I think it is just a shame we pretend. Makes research convoluted and messy. As I said the other day, we should just allow people to pursue whatever they want and lay a framework where the incentives drive the clearest explanations possible. https://news.ycombinator.com/item?id=39665427 https://news.ycombinator.com/item?id=39665427
api 3y ago
How long before more legible code or code-like constructs (or markup?) start to displace arcane mathematical notation? It would take quite a long time but I could see this slowly happening for analogous reasons to how the printing press favored alphabetic languages over pictorial ones. Computers teach us to read, write, and express linguistically and are now thanks to LLMs capable of working much more fluently with language. Squiggles and lots of Greek letters seem like an anachronism.
- godelski 3y ago
  > How long before more legible code or code-like constructs (or markup?) start to displace arcane mathematical notation? My best guess is never. The problem is that math is a language itself. In fact, I'd more accurately call it a family of languages. People often confuse it for an inherent thing because most of the time we use it in applied ways for subjects like physics, and the sciences. But clearly those people have never taken abstract algebra or developed their own toy algebra (or group, ring (or rung), or field). You might say they have an _ideal_istic notion of mathematics. That said, I am absolutely sympathetic to the complexity of mathematics and there is so much that is difficult to grasp. What's worse, is that when this abstract gobbledy goop finally clicks it's so abundantly obvious that it deceives you into thinking you've known it all along. I think this contributes to the difficulty of teaching the subject because those qualified have forgotten the struggles they themselves have had (to be fair, human psychology plays a big role here too because if we only remember the struggles we'd have difficulty finding the passion and beauty). But I think our best hope is to find a unified mathematics. The obsession people have with things like set theory and category theory is that you can see this interconnectedness. You get this deep feeling that you're looking at the same things manifesting in different ways. Remember that a lot of mathematics is converting your system into another system (we might call this an isomorphic mapping) such that your problem is easier to solve in the other system (think about how we might want to go from Cartesian coordinates to polar, but now abstract that concept out more than your friend that took a few tabs of acid). You zoom out move around, and zoom back in, and maybe a few more times (but you have to keep track of your path). > Squiggles and lots of Greek letters seem like an anachronism. Do you have another suggestion? Because I don't see how code, English, or literally any other thing that can be written down is anything more meaningful than "a bunch of squiggles." There's only so many simple, and importantly, distinguishable squiggles that we can write down. Luckily we have a tool to exactly determine this ;) The shitty part of mathematics is also the best part, in that you have to embrace the abstractness of it all. But of course human brains weren't designed for this. (Yes, there are some of us trying to figure out how to get machines to think with that extreme level of abstractedness at its core. No, this is not how computers already "think.") So yeah, I empathize with you. Quite a lot. There's so much more that I want to know about this thing too. But it is often seemingly impenetrable. All I can tell you is that it just looks that way and isn't. Everyone has the capacity but finding the right way up this mountain (that I'm nowhere near Terry, and he's nowhere near the summit) can be just as hard as the climb itself. The best way is persistence though. Just remember that you don't play video games because they are easy. Sometimes you gotta just trick yourself into pushing through. And some of the best advice I can give is revisiting old topics. So much of what you think you've known actually has a tremendous amount of depth to it. Coming back with fresh eyes and a better understanding of the larger picture can help you see all the beauty in it, even if this is sometimes fleeting. I'm sorry to have vomited so much, but you know, Stockholm Syndrome is a bitch.