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Only disallow DeepSpeed Zero-3 for auto bs finder #31731
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I don't think the failing tests are on my end 😅 |
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
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Update: Zero-2 works, so it's Zero-3 that we have issues with. I've pinged the DeepSpeed team for help, but this gets us most of the way there :) |
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Essentially zero-3 does some pretty intense monkey patching into their |
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LGTM - thanks!
Re small models @ydshieh is the best person to ask :)
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Hi @muellerzr !
We have a script to create tiny models for testing purpose, however:
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Thanks @ydshieh, I'll think today on how I can maybe write a test for this then on a small enough model/large enough BS that this can work no matter the GPU and still is efficient and add a test in. Worst case we may not be able to |
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This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread. Please note that issues that do not follow the contributing guidelines are likely to be ignored. |
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Haven't forgotten about this, test will be made this afternoon and then we can merge :) (I'll hit zero3 support soon enough ish) |
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Doing this today & merging, got away from me |
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Let me know when you want a review @muellerzr |
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Thanks @LysandreJik. For now this works fine, Wing noted there's an issue with packing which can be investigated later. |
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Ok, clean! Thanks @muellerzr
* Only disallow DeepSpeed * Clean * DeepSpeed! * Add a test for deepspeed
What does this PR do?
Looking into re-enabling the auto bs finder for FSDP and DeepSpeed. Did a small scale test with FSDP and found that training works fine. Will move onto DeepSpeed soon but here is an interim.
At the worst users can raise an issue here (a new one) with what specifically breaks with FSDP. But my attempts to break it based on FSDP have yet to fail (as FSDP doesn't care about batch sizes actually!)
I don't enjoy not having a test here, in my tests I was using
tinyllamaon 48GB (2x4090). What's the general guidelines for using non-custom models in this case? Do we make test models of size N?tinyllamais a 1.1B Llama model, so I can probably write a chunk test with a model that size if we need to/should. Just curious if we have any methods of dynamically creating models ofnsize for testing purposes (I know we do so in accelerate)Before submitting
Pull Request section?
to it if that's the case.
documentation guidelines, and
here are tips on formatting docstrings.
Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.
@amyeroberts @SunMarc