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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: #13452 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/288/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/288/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/287/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/288/orig
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pytorch-bot bot commented Aug 16, 2025

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/13466

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

❌ 1 New Failure, 1 Pending, 1 Unrelated Failure

As of commit c2f9db2 with merge base cf669e3 (image):

NEW FAILURE - The following job has failed:

BROKEN TRUNK - The following job failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

  • pull / test-binary-size-linux-gcc / linux-job (gh) (trunk failure)
    /pytorch/executorch/kernels/portable/cpu/op_stack.cpp:129:26: error: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘ssize_t’ {aka ‘long int’} [-Werror=sign-compare]

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@meta-cla meta-cla bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Aug 16, 2025
Base automatically changed from gh/SS-JIA/287/orig to main August 16, 2025 04:14
Pull Request resolved: #13452

## Motivation

Be able to test Vulkan lowering via optimum-executorch.

## Context

Very similar to the below PR, Int4 weight only quantization is currently enabled in Vulkan via a custom source transform quantizer that replaces linear layers with a custom linear layer that calls a custom weight only quantized linear op.

This diff aims to make it so that no Vulkan specific source transforms need to be applied by adding a fusion pattern for weight only quantized linear.


## Changes

* Introduce a fusable graph pattern for weight only quantized linear
* Add fusion logic for weight only quantized linear in the fuse patterns pass
* Add `4w` qmode to the export llama script
ghstack-source-id: 303387280

Differential Revision: [D80293302](https://our.internmc.facebook.com/intern/diff/D80293302/)
@SS-JIA SS-JIA force-pushed the gh/SS-JIA/288/orig branch from 5182515 to c2f9db2 Compare August 16, 2025 13:25
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@SS-JIA SS-JIA merged commit 2f4b704 into main Aug 16, 2025
102 of 104 checks passed
@SS-JIA SS-JIA deleted the gh/SS-JIA/288/orig branch August 16, 2025 14:25
agrima1304 pushed a commit to agrima1304/executorch that referenced this pull request Aug 26, 2025
## Motivation

Be able to test Vulkan lowering via optimum-executorch.

## Context

Very similar to the below PR, Int4 weight only quantization is currently enabled in Vulkan via a custom source transform quantizer that replaces linear layers with a custom linear layer that calls a custom weight only quantized linear op.

This diff aims to make it so that no Vulkan specific source transforms need to be applied by adding a fusion pattern for weight only quantized linear.


## Changes

* Introduce a fusable graph pattern for weight only quantized linear
* Add fusion logic for weight only quantized linear in the fuse patterns pass
* Add `4w` qmode to the export llama script

Differential Revision: [D80293302](https://our.internmc.facebook.com/intern/diff/D80293302/)

[ghstack-poisoned]
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