[ET-VK] AOT logic for quantized conv2d #14669
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14669
Note: Links to docs will display an error until the docs builds have been completed. ⏳ No Failures, 113 PendingAs of commit 8686e98 with merge base 2b20016 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Pull Request resolved: #14648 ### Changes As title; this diff adds the necessary export logic required to enable fusing quantized convolution patterns into the custom ops introduced in the below diff. ghstack-source-id: 312809808 @exported-using-ghexport Differential Revision: [D83437826](https://our.internmc.facebook.com/intern/diff/D83437826/)
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This PR was created by the merge bot to help merge the original PR into the main branch.
ghstack PR number: #14648 by @SS-JIA
^ Please use this as the source of truth for the PR details, comments, and reviews
ghstack PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/333/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/333/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/332/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/333/orig
Differential Revision: D83437826
@diff-train-skip-merge