8000 [Ez][BE] Make implicit subpackage explicit by shink · Pull Request #153613 · pytorch/pytorch · GitHub
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[Ez][BE] Make implicit subpackage explicit #153613

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@shink shink commented May 15, 2025 •
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Part of: #153546
Follow up: #153347

I run the following command to find all implicit namespace packages:

ruff check . --select INP001 | grep __init__.py

cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov

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pytorch-bot bot commented May 15, 2025 •
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/153613

Note: Links to docs will display an error until the docs builds have been completed.

❌ 1 New Failure

As of commit e97bbf1 with merge base e79790e (image):

NEW FAILURE - The following job has failed:

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@shink shink changed the title [Ez][BE] Make implicit subpackage explicit: torch/_inductor/codegen/cuda/cutlass_lib_extensions and torch/ao/quantization/experimental [Ez][BE] Make implicit subpackage explicit May 15, 2025
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looks like there are failures

@jerryzh168 jerryzh168 added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label May 16, 2025
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shink commented May 19, 2025

Thanks for review! Have fixed.

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@shink Please fix the Python docs for the package

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shink commented May 28, 2025

@pytorchbot rebase -b main

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@pytorchbot started a rebase job onto refs/remotes/origin/main. Check the current status here

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Successfully rebased fix/implicit-subpackage onto refs/remotes/origin/main, please pull locally before adding more changes (for example, via git checkout fix/implicit-subpackage && git pull --rebase)

@pytorchmergebot pytorchmergebot force-pushed the fix/implicit-subpackage branch from 8128475 to e97bbf1 Compare May 28, 2025 01:18
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module: inductor open source release notes: AO frontend release notes: quantization release notes category triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module
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