[ExecuTorch][WebGPU] Add constant_pad_nd op#20857
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20857
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[ExecuTorch][WebGPU] Add relu op (shared unary handler; sigmoid adopts make_compute_pipeline)
#20863
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Stack from ghstack (oldest at bottom):
Adds
aten.constant_pad_nd.defaultto the WebGPU backend, unblocking the DaViT window-padding path in vision models.Problem — the backend had no
constant_pad_ndhandler, so any graph that pads a tensor (e.g. DaViT's window partitioning) could not fully delegate to WebGPU and threw at runtime.Solution — a single gather/fill compute kernel: Before — no handler;
aten.constant_pad_nd.defaultunsupported at runtime. After — one thread per output element gathers the source element when its coordinates land inside the input, otherwise writes the constant fillvalue.Implementation:
vec4<u32>params (out_dims,in_dims,left); leading slots get extent 1 / pad 0, so the WGSL is rank-agnostic and always iterates 4 dims.padIntListis reversed-dim (innermost-first(left, right)pairs); the handler expands it to per-dimleft/right, then validatesout.dims[d] == in.dims[d] + left[d] + right[d]before any buffer allocation (loud-fail, no leak-on-throw).leftpad as an unsigned wrapping subtract (a negative coord wraps to a huge value and is rejected by the< in_dimsbound check); if all four coords are in-bounds it copiesinp[flat_in], else it writesvalue— a pure copy/fill, so bit-exact.valueis read viautils::scalar_or(aScalarmay serialize asIntorDouble), defaulting to0.utils::compute_dispatch_grid(workgroup size clamped to the device max, up to 256, plus a 2D spill past the 65535 workgroup-count ceiling; thestride_xoverride lets the shader decodei = gid.y*stride_x + gid.x).backends/vulkan/runtime/graph/ops/impl/Pad.cpp(same reversed-dim(before, after)pad convention andconstant_pad_ndresize logic).Constraints — fp32 only (
nbytes == numel*4guard); rank 1..4;padmust be even-length and no longer than the rank; the output element count must fitu32(<= 2^32).Co-authored-with: Claude Code.
@exported-using-ghexport
Differential Revision: D110836672
Differential Revision: D110836672