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Add 2, 3, 4, 5 bit custom ops #828
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/828
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 0fd7957 with merge base e1039ab (): This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This pull request was exported from Phabricator. Differential Revision: D62248716 |
m = 1 | ||
n = 4096 | ||
k = 4096 | ||
nbit = 4 | ||
n_layers = 10 | ||
nbit = 5 |
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wondering is this uint5 or int5?
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The 5bit kernel has quantized range [-16, 15].
This pull request was exported from Phabricator. Differential Revision: D62248716 |
Summary: Pull Request resolved: pytorch#828 Refactors some of the custom op example code to add support for more kernel variants. Reviewed By: digantdesai Differential Revision: D62248716
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This pull request was exported from Phabricator. Differential Revision: D62248716 |
Summary: Pull Request resolved: pytorch#828 Refactors some of the custom op example code to add support for more kernel variants. Reviewed By: digantdesai Differential Revision: D62248716
2ced261
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7af35e6
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Summary: Pull Request resolved: pytorch#828 Refactors some of the custom op example code to add support for more kernel variants. Reviewed By: digantdesai Differential Revision: D62248716
7af35e6
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0fd7957
Compare
Differential Revision: D62248716 Pull Request resolved: #828
Summary: Refactors some of the custom op example code to add support for more kernel variants.
Reviewed By: digantdesai
Differential Revision: D62248716