Diffusion models #52
Replies: 6 comments 5 replies
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Furthermore, zuko essentially expanded the utilization of flows in sbi dramatically. I imagine such a library could also seperate the diffusion method from the research area in a positive way: e.g. more diffusion-based sbi algorithms.
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Hi @francois-rozet, I think such a library would be a fantastic idea and there are a lot of people (myself included) who would benefit from it. I would definitely recommend not to include the functionality in Zuko. Zuko has a lot of complexity on its own, using lazy transformations and so on. I don't see much benefit in including other classes of models and adding complexity. I would think that most users would have specific research use cases where they would have to write custom models for their specific use case. Having primitives to build on would be a big help. Perhaps also including sample implementations that point to the dedicated papers. I would be more than willing to help write such a library. Thanks for getting in touch and your work, |
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Hi everyone! I love the idea! Zuko definitely makes the use of normalizing flows straightforward for many applications. Having the same kind of API for diffusion models would be amazing! I would definitely use it and would be happy to help! I especially like the idea of centralizing the different algorithms and features: i think there is a great potential of such a library becoming the standard tool for score based methods. I think we are getting to a point where there is a better understanding of such models and people want to start building on the baseline architectures, adding features, different samplers and schedulers, etc. So yes, a new diffusion library would be great! For me integrating it to zuko doesn’t make any sense though. |
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I see this a bit late, sorry! I use to define over and over again my diffusion models in the same way, with sometimes small variations. I could definitely be a nice way to have everything packed in a clean library like zuko. I agree with the others that a proper library, detached to zuko is a good idea to allow specific structure tailored to diffusion models as you suggest. We can come back later to specific implementation-related topics, but I'm more of the team of having a unified and simple representation for diffusion models that could be specified to a task afterwards. So, about point 2, linking implementation to papers is obviously needed but under a simple unified implementation in my pov (to keep the user's experience straightforward). |
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Hi all, @francois-rozet thanks for starting this discussion! I agree with what was said already. It's a great idea and a separate library would make sense. At |
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Thank you everyone for your answers. There is definitely interest for a diffusion models library 🤯 In the coming weeks, I will setup a repo in the probabilists organization and write a first draft for the interface. I invite you to open issues/discussions/PRs to discuss about anything (API, features, docs, ...). Concerning the name of the project, I was thinking Azula would be fitting as she is the sister of Zuko 🔥 Tell me what you think! |
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I am considering creating a small library for diffusion/score-based generative models. The idea would be to have a very simple, composable and extendable interface. For example, it would define the
Denoiser
,Scheduler
andSampler
primitives (similar to the code in francois-rozet/diffusion-priors but in PyTorch).I have several questions for Zuko's community:
cc: @glouppe, @gerome-andry, @JuliaLinhart, @bkmi, @michaeldeistler, @janfb, @simonschnake
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