[ET-VK][qconv] Add q8ta_conv2d_transposed operator#18034
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SS-JIA merged 2 commits intogh/SS-JIA/462/origfrom Mar 10, 2026
Merged
[ET-VK][qconv] Add q8ta_conv2d_transposed operator#18034SS-JIA merged 2 commits intogh/SS-JIA/462/origfrom
SS-JIA merged 2 commits intogh/SS-JIA/462/origfrom
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Pull Request resolved: #18016 Implement quantized transposed 2D convolution for the Vulkan backend, enabling int8 transposed convolutions used in decoder/upsampling networks. The GLSL shader iterates over all kernel positions and derives valid input positions via (output + padding - kernel) / stride. Invalid positions use input_zp_packed so the precomputed weight_sums zero-point correction remains consistent. Reuses the existing q8ta_conv2d weight packing and workgroup size selection since, after the pattern matcher reshapes transposed weights from (IC, OC, KH, KW) to (OC, KH*KW*IC), the layout is identical to regular conv2d. Supports hardware int8 dot product with software fallback, grouped convolutions, optional bias and ReLU activation. Only dilation=1 is supported (matching the ATen conv_transpose2d constraint). This diff was authored with Claude. ghstack-source-id: 349646651 @exported-using-ghexport Differential Revision: [D95807070](https://our.internmc.facebook.com/intern/diff/D95807070/)
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/18034
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Pull Request resolved: #18017 Some quantized linear projections (e.g. in EdgeTAM's SpatialPerceiver / mask decoder) decompose as aten.bmm instead of aten.mm. Add aten.bmm.default as an anchor node in the quantized linear pattern detector so these nodes can be fused into custom quantized linear ops. Reject bmm nodes with batch dim > 1 since the custom ops assume a single batch. ghstack-source-id: 349646654 @exported-using-ghexport Differential Revision: [D95807072](https://our.internmc.facebook.com/intern/diff/D95807072/)
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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: #18016 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/463/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/463/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/462/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/463/orig
Differential Revision: D95807070
@diff-train-skip-merge