[ET-VK] Support different input layouts in q8ta_binary operator#17578
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SS-JIA merged 1 commit intogh/SS-JIA/436/origfrom Feb 20, 2026
Merged
[ET-VK] Support different input layouts in q8ta_binary operator#17578SS-JIA merged 1 commit intogh/SS-JIA/436/origfrom
SS-JIA merged 1 commit intogh/SS-JIA/436/origfrom
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Previously, the q8ta_binary operator required both inputs to use the same memory layout. This was enforced by using a single `in_layout` specialization constant for both input buffers. However, some models may have inputs with different layouts (e.g., 4W4C and 4C1W) that share the same packed dimension and block size, which should be compatible for binary operations. This change introduces a separate `other_layout` specialization constant for the second input, allowing the shader to correctly load from input_b using its actual layout while input_a continues to use `in_layout`. The C++ side now passes both layout hashes as separate specialization constants to the shader. Differential Revision: [D93768638](https://our.internmc.facebook.com/intern/diff/D93768638/) ghstack-source-id: 342806076 Pull Request resolved: #17563
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/17578
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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: #17563 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/437/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/437/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/436/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/437/orig
Differential Revision: D93768638
@diff-train-skip-merge