[ExecuTorch][Vulkan] Add et_vk.q4gsw_requant kernel (STE re-quant to W_4X8)#21100
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…W_4X8) Pull Request resolved: #20945 **Adds the Vulkan `et_vk.q4gsw_requant` kernel** — straight-through re-quant of fp32 latent weights into the frozen-scale 4-bit codes, for on-device weight training. Writes the codes directly in the forward's W_4X8 layout so no per-step re-pack is needed. **Problem:** `et_vk.q4gsw_requant` is registered in the shared Vulkan partitioner but Vulkan had no runtime kernel. **Solution:** a GLSL kernel that quantizes `round(latent / scale)` clamped to `[-8, 7]` and packs the codes in the W_4X8 block layout the forward reads, reusing the exact byte-pair convention of `glsl/pack_q4_linear_weight__w_4x8.glsl` (even-N low nibble, odd-N high; one ivec4 per 4K x 8N block at `(k4, n8)`; OOB upper tile = the bias-zero `0x88888888`). A zero scale yields code 8 (no divide-by-zero), matching the eager reference. Key changes: - `glsl/q4gsw_requant.{glsl,yaml}` — buffer x float; 2D dispatch over `(k4, n8)`. - `impl/QuantizedLinearRequant.cpp` — prepacks the constant scales; output is the W_4X8 int buffer `[K4 * N4_padded * 2]`; `group_size` spec constant; dispatch-grid guard. **Design note (for review):** per the layout decision, requant writes W_4X8 to match the Vulkan forward. Today the forward and backward each prepack their own flat `[N, K/2]` weight internally, so nothing yet consumes an externally-produced W_4X8 buffer — closing the training loop needs a forward path that reads a mutable pre-packed weight (the weight-lifecycle follow-up). The op's AOT meta in `custom_ops_lib.py` still describes the flat `[N, K/2]` output and should be reconciled with this W_4X8 output. **Constraints:** buffer storage, fp32 latent/scales; `N % 4 == 0`, `K % 4 == 0`, `group_size % 4 == 0`. ghstack-source-id: 405059118 @exported-using-ghexport Differential Revision: [D111797527](https://our.internmc.facebook.com/intern/diff/D111797527/)
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21100
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Pull Request resolved: #20946 **Correctness tests for the Vulkan `et_vk.q4gsw_requant` kernel** (stacked above the op diff). **Coverage:** the golden codes are computed with ATen (`round`/`clamp`, zero-scale -> code 8), mirroring `quant_nibble`, then packed into the expected W_4X8 int buffer with a small bit-packing reference (data-reshaping only, no hand-rolled math). The kernel output is compared int-for-int against that buffer, which locks the exact byte layout the forward reads. The latent is built as `code * scale` so `round()` is unambiguous (no `.5` tie-break divergence). Cases: - `test_tile_aligned` — single group, tile-aligned N/K. - `test_grouped` — multiple quantization groups along K. - `test_odd_n4` — `N % 8 != 0` (odd N4 -> padded stride + bias-zero OOB tile). - `test_zero_scale` — a zero scale must yield code 8, not a divide-by-zero. Also wires `q4gsw_requant_test` into `targets.bzl` + `CMakeLists.txt`. ghstack-source-id: 405059122 @exported-using-ghexport Differential Revision: [D111797526](https://our.internmc.facebook.com/intern/diff/D111797526/)
Pull Request resolved: #21005 Replace the hand-maintained explicit `WEBGPU_SRCS` op-handler list with `file(GLOB WEBGPU_OP_SRCS CONFIGURE_DEPENDS runtime/ops/*/*.cpp)` so adding a new op no longer requires editing this file (addresses review feedback). The five `runtime/*.cpp` sources and `runtime/ops/OperatorRegistry.cpp` (which sits directly under `ops/`, not a per-op subdir) stay explicit. `CONFIGURE_DEPENDS` re-globs at build time when op sources are added or removed. The glob resolves to exactly the 40 op handlers the explicit list enumerated (verified set-equal) — no op added or dropped, and static-init registration is order-independent under `--whole-archive`. Co-authored-with: Claude Code. ghstack-source-id: 405059133 @exported-using-ghexport Differential Revision: [D112482039](https://our.internmc.facebook.com/intern/diff/D112482039/)
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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: #20945 by @JCNTH
^ 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/JCNTH/84/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/84/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/83/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/84/orig
@diff-train-skip-merge
cc @SS-JIA @manuelcandales @digantdesai @cbilgin