Add dynamic quantization support to gemlite layout#2327
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2327
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (2 Unrelated Failures)As of commit a94c9cf with merge base dd22777 ( BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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I think by "static" you meant weight only? |
jerryzh168
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Jun 6, 2025
Signed-off-by: mobicham <hicham@mobiuslabs.com>
jerryzh168
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Jun 6, 2025
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Anything else to have this merged? Thank you! |
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we can merge now, the test failures does not look related |
liangel-02
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Aug 25, 2025
* fix get_plain() with FMA mode * update * fix in_features/out_feature meta-data mismatch * update gemlite slice test * add packing_bitwidth support * add packing_bitwidth support and cleanup * update default gemlite layout * cleanup * fix symmetric use-case and relax _same_meta_data * _copy() meta data * fix (4,) in autoquant * Add dynamic mode in gemlite layout * mode explanation Signed-off-by: mobicham <hicham@mobiuslabs.com> * use weights_only instead of static --------- Signed-off-by: mobicham <hicham@mobiuslabs.com>
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This PR adds dynamic quantization support to the GemLite layout. The new config param is
mode:mode="weight_only"- no activation quantization (default).mode="dynamic"- uses int8 dynamic quantization for A8W8 and fp8 for A8Wn.