huggingface / huggingface/diffusers

Winograd Convolution & other Speed Is All You Need optimizations

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Beschreibung

**Is your feature request related to a problem? Please describe.**
Right now, Stable Diffusion, and other diffusers models are really optimized, but a recent preprint from Google researchers found that Winograd Convolutions could reduce latency more than using FlashAttention.
The paper in question: https://arxiv.org/pdf/2304.11267.pdf

**Describe the solution you'd like**
I opened this feature request to let discussions and users share their implementation of the paper.
It would be interesting to see how well it works, and if it would be possible to integrate it to diffusers library.

**Additional context**
Right now, I didn't found any code implementation of the paper. If anybody see something, do not hesitate to share!

Beitragsleitfaden

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Rechercherichtung

Read the linked paper on Winograd Convolutions and review the diffusers library to determine where such optimization could fit. Look for an existing implementation to evaluate; done would require a working implementation, latency measurements, and a clear decision about integration into diffusers.

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Bewertung

Tech-Stack
python, pytorch
Bereich
machine-learning, performance
Issue-Typ
Feature
Schwierigkeit
5/5
Geschätzter Aufwand
Über eine Woche
Aktivitätsstatus
Veraltet
Klarheit
Muss geklärt werden
Anfängerfreundlichkeit
20/100

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