[ExecuTorch][WebGPU] Add split_with_sizes_copy op - #21281
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Pull Request resolved: #20995 **Add `aten.split_with_sizes_copy.default` to the WebGPU backend** — the split on YOLO's Detect head (separating the concatenated box / objectness / class predictions). **Problem**: The WebGPU delegate had no `split_with_sizes_copy`, so YOLO object-detection could not fully delegate to the GPU. **Solution**: Split `self` along `dim` into N contiguous chunks. Each chunk is a step-1 slice from the running offset, reusing the `slice.wgsl` gather kernel — one dispatch per output. Outputs arrive as a serialized ValueList. Each chunk writes its own distinct output buffer and reads only the shared input, so there is no cross-dispatch read-after-write hazard. **Implementation**: - `runtime/ops/split_with_sizes/SplitWithSizes.cpp` registering `aten.split_with_sizes_copy.default`; reuses `slice_wgsl.h` (no new shader). Uses `utils::make_compute_pipeline` (auto-derived bind-group layout) rather than hand-rolling the layout / pipeline / bind group. - Mirrors the Vulkan `split_with_sizes_copy` delegate. - CMake `WEBGPU_SRCS` entry. **Constraints**: fp32-only; `dim` normalized + range-checked; `outputs == sizes` count enforced (fail-loud). Reuses the `slice` op's `slice_wgsl.h`, so this diff stacks above `slice` and must land after it. No change to existing ops. ghstack-source-id: 405949786 @exported-using-ghexport Differential Revision: [D112417284](https://our.internmc.facebook.com/intern/diff/D112417284/)
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21281
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Pull Request resolved: #20996 **Op-test suite for `aten.split_with_sizes_copy.default`** (stacked on the split_with_sizes_copy op diff). Adds `test/ops/test_split_with_sizes_copy.py` (`SplitWithSizesModule` — `torch.split` by a size list) + a `@register_op_test("split_with_sizes_copy")` suite in `test/op_tests/cases.py` (3 cases: a 3-way channel split, a dim-0 split, and a last-dim split). Multi-output: the framework compares chunk 0 (out_index 0) while each case exercises all N per-chunk dispatches. `copy` is bit-exact, so the golden is float32. ghstack-source-id: 405949787 @exported-using-ghexport Differential Revision: [D112417279](https://our.internmc.facebook.com/intern/diff/D112417279/)
…ipeline Pull Request resolved: #20868 Route `add`, `mul`, `index`, `permute`, `select`, `slice`, `update_cache`, `rms_norm`, and `embedding_q4gsw` through the shared `utils::make_compute_pipeline` helper (which uses `layout:"auto"`), replacing each op's hand-written `WGPUBindGroupLayoutEntry[]` + pipeline-layout + bind-group boilerplate (~50-110 lines each) with a single helper call. The driver now derives the bind-group layout from the shader's statically-used bindings. Byte-behavior is preserved: identical binding indices/types/buffers/sizes, dispatch workgroup counts, resize hooks, and validations; override constants (`wg_size`) passed via the helper's `constants` param. Extends the Diff 1 layout:"auto" adoption to the trivial single-dispatch ops. ghstack-source-id: 405949795 @exported-using-ghexport Differential Revision: [D110836665](https://our.internmc.facebook.com/intern/diff/D110836665/)
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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: #20995 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/99/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/99/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/JCNTH/98/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/JCNTH/99/orig
@diff-train-skip-merge