huggingface / huggingface/diffusers

Winograd Convolution & other Speed Is All You Need optimizations

Aperta
#3,227 4 commenti 0 reazioni 0 assegnatari Vedi su GitHub
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Lingua principale
Python
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PR unite (30g)
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Descrizione

**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!

Guida per i contributori

Apri la guida per i contributori

Direzione di ricerca

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.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
python, pytorch
Ambito
machine-learning, performance
Tipo di issue
Funzionalità
Difficoltà
5/5
Tempo stimato
Più di una settimana
Stato di attività
Ferma
Chiarezza
Da chiarire
Idoneità per principianti
20/100

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