[ExecuTorch][WebGPU] Add upsample_nearest2d op

[JCNTH]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] apply_rotary_emb_hf op tests #20876
• [ExecuTorch][WebGPU] et_vk.apply_rotary_emb_hf: HuggingFace rotate-half RoPE runtime op (unblocks Qwen3) #20875
• [ExecuTorch][WebGPU] et_vk conv2d im2col-GEMM tests #20874
• [ExecuTorch][WebGPU] et_vk conv2d: route standard (groups==1) conv through an im2col tiled GEMM (1.1-2.4x) #20873
• [ExecuTorch][WebGPU] et_vk.sdpa channel-attention tests #20872
• [ExecuTorch][WebGPU] et_vk.sdpa: shape-route QK to a per-entry kernel for channel attention (15-30x faster) #20871
• [ExecuTorch][WebGPU] Migrate quantized_linear to make_compute_pipeline #20870
• [ExecuTorch][WebGPU] Migrate multi-dispatch ops to make_compute_pipeline #20869
• [ExecuTorch][WebGPU] Migrate 9 ops to make_compute_pipeline (layout:"auto") #20868
• [ExecuTorch][WebGPU] Adopt WebGPU layout:"auto" in make_compute_pipeline #20867
• [ExecuTorch][WebGPU] slice_copy native golden test #20866
• [ExecuTorch][WebGPU] slice_copy Double-arg scalar handling + view_copy/alias glue #20865
• [ExecuTorch][WebGPU] relu op tests #20864
• [ExecuTorch][WebGPU] Add relu op (shared unary handler; sigmoid adopts make_compute_pipeline) #20863
• [ExecuTorch][WebGPU] max_pool2d op tests #20862
• [ExecuTorch][WebGPU] Add max_pool2d op #20861
• [ExecuTorch][WebGPU] upsample_nearest2d op tests #20860
• -> [ExecuTorch][WebGPU] Add upsample_nearest2d op #20859
• [ExecuTorch][WebGPU] constant_pad_nd op tests #20858
• [ExecuTorch][WebGPU] Add constant_pad_nd op #20857
• [ExecuTorch][WebGPU] addmm op tests #20856
• [ExecuTorch][WebGPU] Add optimized addmm op #20855
• [ExecuTorch][WebGPU] embedding op tests #20854
• [ExecuTorch][WebGPU] Add embedding op #20853
• [ExecuTorch][WebGPU] SDPA op tests #20852
• [ExecuTorch][WebGPU] Add optimized SDPA op #20851
• [ExecuTorch][WebGPU] conv2d op tests #20850
• [ExecuTorch][WebGPU] Add optimized conv2d op #20849
• [ExecuTorch][WebGPU] linear_fp32 op tests #20848
• [ExecuTorch][WebGPU] Add optimized linear_fp32 op #20847
• [ExecuTorch][WebGPU] layer_norm op tests #20846
• [ExecuTorch][WebGPU] Add optimized layer_norm op #20845
• [ExecuTorch][WebGPU] gelu op tests #20844
• [ExecuTorch][WebGPU] Add optimized gelu op #20843
• [ExecuTorch][WebGPU] Shared pipeline + dispatch-grid + vec4-align helpers (op-suite foundation) #20842

Adds aten.upsample_nearest2d.vec to the WebGPU backend, enabling the SAM2/SAM3 pixel-decoder / FPN nearest-neighbour upsample path.

Problem — nearest-neighbour 2D upsample (F.interpolate(..., mode="nearest")) had no WebGPU kernel, blocking the FPN 2x upsample chain in the SAM2/SAM3 pixel decoder.

Solution — Before — no handler; aten.upsample_nearest2d.vec unsupported. After — one thread per output element (n, c, oh, ow) maps back to its nearest source pixel and copies it.

Implementation:

• The kernel computes the source index with ATen's legacy nearest formula ih = floor(oh*IH/OH), iw = floor(ow*IW/OW) (integer division), then copies inp[((n*C+c)*IH+ih)*IW+iw] — a plain NCHW row-major gather, bit-exact.
• OH/OW are taken from the output tensor's own dims (not re-derived from the size/scale args), and the handler validates that N/C match between input and output.
• Adaptive 1D->2D dispatch via utils::compute_dispatch_grid (workgroup size clamped to the device max, up to 256, plus a 2D spill past the 65535 ceiling; stride_x decode).
• Divergence from Vulkan (intentional): this does NOT mirror Vulkan backends/vulkan/runtime/graph/ops/impl/Upsample.cpp, which computes the source index with the half-pixel-center reciprocal-scale formula. Half-pixel-center is correct for bilinear but wrong for non-exact nearest; the ATen nearest_neighbor_compute_source_index (UpSample.h) floor(oh*IH/OH) form is the one that matches PyTorch's mode="nearest". The two agree on exact-integer ratios (e.g. 2x) but diverge on non-integer ratios (e.g. 5->8), which the op-test's non_2x_ratio case pins down.

Constraints — fp32 only; 4D NCHW input and output; nearest mode only; non-zero spatial dims; the output element count must fit u32.

Co-authored-with: Claude Code.

Differential Revision: D110836668

[pytorch-bot]

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As of commit 9075bf2 with merge base aceeb40 ():

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👉 Rebase onto the `viable/strict` branch to avoid these failures

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