Adding PyTorch XLA support for sdxl inference #5273
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… with instructions for xla
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patrickvonplaten
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Hey @ssusie, Nice addition, generally I'm ok with having this addition. However, could you maybe add |
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. |
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Thanks for the feedback Patrick. Added the dependency in |
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@ssusie could you run |
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Thanks everyone for the review and comments. I ran the make style and added changes to the pr. |
| speedup, we need to call the pipe again on the input with the same length | ||
| as the original prompt to reuse the optimized graph and get the performance |
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Does the prompt length really matters here, as embeddings always have the same shape?
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Thanks for the great question. With the current setup we need the same length for the input for XLA, otherwise it will recompile the whole graph. We can potentially cut the graph with xm.mark_step after embeddings are calculated, but it is not address in this PR.
src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl.py
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Thanks for the reviews and comments. Is there anything else to change or address or can this be merged? |
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Let's merge it - great job @ssusie! We don't have tests here yet, but I think this is fine to begin with :-) |
* Added mark_step for sdxl to run with pytorch xla. Also updated README with instructions for xla * adding soft dependency on torch_xla * fix some styling --------- Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* Added mark_step for sdxl to run with pytorch xla. Also updated README with instructions for xla * adding soft dependency on torch_xla * fix some styling --------- Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
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What does this PR do?
Enables users run sdxl inference in PyTorch XLA. README_sdxl.md guide is also updated.
@patrickvonplaten @sayakpaul
Thanks.