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Better registration support for a wide range of third-party hardware #20349
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Examples here: https://github.com/uniartisan/RWKV-PEFT/blob/device-enhance/train.py#L499 There are a lot of things to be checked, I will try to do it later and make it more clear in documentation |
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #20349 +/- ##
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- Coverage 87% 86% -1%
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Files 268 268
Lines 23449 23528 +79
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- Hits 20389 20285 -104
- Misses 3060 3243 +183 |
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Thank you for the interesting PR! I added a few comments.
hey @uniartisan are you willing to finish this one up? It would be a welcome contribution |
sorry for my late reply. I will solve them tomorrow! |
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will you add DirectML? |
What I've added is the code for plug-in registration, which means you can register Direct ML by yourself. Just write a few simple function 🤓 |
Thank you @uniartisan! |
This pull request has been automatically marked as stale because it has not had recent activity. It will be closed in 7 days if no further activity occurs. If you need further help see our docs: https://lightning.ai/docs/pytorch/latest/generated/CONTRIBUTING.html#pull-request or ask the assistance of a core contributor here or on Discord. Thank you for your contributions. |
What does this PR do?
Thank you to the lightning team for providing such an easy-to-use, clearly designed library.
The pr draft hopes to provide better registration support for a wide range of third-party hardware, and the pr is designed to integrate third-party hardware with minimal intrusive changes, including intel XPU, Huawei Ascend NPU, Cambrian, Moorethreads, and more.
Fixes #<issue_number>
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📚 Documentation preview 📚: https://pytorch-lightning--20349.org.readthedocs.build/en/20349/