[ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end)

[JulianCloudNTH]

Stack from ghstack (oldest at bottom):

• [ExecuTorch][WebGPU] 2D compute dispatch tests — prefill golden + fold unit test #20584
• [ExecuTorch][WebGPU] 2D compute dispatch — lift the 65535 per-dim cap (prefill path) #20583
• [ExecuTorch][WebGPU] Dynamic-shape integration test (allocate-at-max + per-op resize) #20582
• -> [ExecuTorch][WebGPU] Dynamic resize hook for slice_copy (dynamic start/end) #20581
• [ExecuTorch][WebGPU] Dynamic resize hook for SDPA (live seq-len S) #20580
• [ExecuTorch][WebGPU] Dynamic resize hook for view_copy #20579
• [ExecuTorch][WebGPU] Dynamic resize hooks for sigmoid and select_copy #20578
• [ExecuTorch][WebGPU] Dynamic resize hooks for add and mul #20577
• [ExecuTorch][WebGPU] Dynamic resize hook for linear_q4gsw #20576
• [ExecuTorch][WebGPU] Dynamic resize hooks for rms_norm, embedding, rope #20575
• [ExecuTorch][WebGPU] Dynamic tensor-shape resize engine core #20574
• [ExecuTorch][WebGPU] SymInt arithmetic ops (add/sub/mul/floordiv) for dynamic shapes #20573

Make slice_copy support a dynamic gather range so the RoPE-freqs slice [input_pos : input_pos + S] works under one dynamic graph.

Problem: the static slice handler read start via a scalar reader that throws on a SymInt and ignored end (output length baked AOT). The RoPE-freqs slice uses a SymInt input_pos for start and a live S for the range, so the static op could neither build nor resize for it.

Solution: read start/end as possibly-dynamic SymInts and add a resize hook that recomputes the gather offset and live output length each step.

• Before: start is a static scalar (SymInt throws); end ignored; output length fixed at the serialized max.
• After: start/end read via a SymInt-aware reader; a hook recomputes out[dim] = (end - start + step - 1) / step, rewrites out_meta/in_meta/params UBOs + the dispatch count, and sets the output cur_dims.

Implementation:

• Hook registered on the start/end value-ids when they are SymInts and on the input tensor always (inert until resized, so a static slice is byte-identical).
• Output/input TensorMeta rebuilt from live dims; dim/step stay static.
• Keep the uniforms alive via own_uniform_buffer so the hook can rewrite them.
• Mirrors Vulkan resize_slice_copy_node.

Constraints: fp32-only; dim/step static; numerics + layout unchanged; inert on a static graph.

NOTE (stacking): this diff sits on top of the in-review slice_copy op (D108793168); rebase onto it once that op lands on master.

Co-authored-with: Claude Code.

Differential Revision: D109906092

[pytorch-bot]

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[JulianCloudNTH]

@claude review and check for any areas or opportunities for modularization