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Add fp16 qb4w scalar kernels

Open GregoryComer opened this issue 1 year ago • 4 comments

Summary: Add qb4w scalar 1x2, 1x4, 1x8, 2x2, 2x4, 2x8, and 4x4 kernels to XNNPACK. Add test coverage in ExecuTorch op-level linear test coverage for 4-bit blockwise weights / fp16.

Differential Revision: D57335871

GregoryComer avatar May 15 '24 20:05 GregoryComer

:link: Helpful Links

:test_tube: See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/3626

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

:white_check_mark: No Failures

As of commit 055cde2fabd57e021b0fc2b229f15129d25fa75d with merge base 47a29a13f4f2574b6787be03249633d5531b795a (image): :green_heart: Looks good so far! There are no failures yet. :green_heart:

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pytorch-bot[bot] avatar May 15 '24 20:05 pytorch-bot[bot]

This pull request was exported from Phabricator. Differential Revision: D57335871

facebook-github-bot avatar May 15 '24 20:05 facebook-github-bot

This pull request was exported from Phabricator. Differential Revision: D57335871

facebook-github-bot avatar May 15 '24 21:05 facebook-github-bot

This pull request was exported from Phabricator. Differential Revision: D57335871

facebook-github-bot avatar May 17 '24 23:05 facebook-github-bot

Thanks!

digantdesai avatar May 20 '24 20:05 digantdesai

This pull request was exported from Phabricator. Differential Revision: D57335871

facebook-github-bot avatar May 20 '24 21:05 facebook-github-bot

This pull request has been merged in pytorch/executorch@4b7c6db5d284d7bcca9b5a6db45758517fa1031d.

facebook-github-bot avatar May 20 '24 23:05 facebook-github-bot