[CoreML EP] Add Sin and Cos unary ops

[maxwbuckley]

Summary

Lower ONNX Sin and Cos to the CoreML ML Program sin / cos elementwise ops
via the existing UnaryOpBuilder, registered in the op builder factory. Like
Erf / Round / Exp, these have no NeuralNetwork lowering
(UnaryFunctionLayerParams has no sin/cos), so IsOpSupportedImpl rejects them on
the NeuralNetwork format.

Why

Sin / Cos form the sinusoidal timestep embedding of diffusion UNets. Supporting
them keeps that prologue on CoreML instead of splitting the graph — a tiny
Stable-Diffusion UNet goes from 2 CoreML partitions → 1, zero graph breaks with
this change alone.

This PR is independent of the rest of the series (it touches only the unary
builder) and can be reviewed/merged in any order.

Tests (coreml_basic_test.cc)

• SinCos_MLProgram — a Sin + Cos graph runs fully on CoreML and matches the CPU
  reference.
• SinCosNeuralNetworkNotSupported — the same graph falls back to CPU on the
  NeuralNetwork format.

Doc: coreml_supported_mlprogram_ops.md lists Sin and Cos.

Series — CoreML EP coverage for transformer / diffusion graphs

• [CoreML EP] Support bool Cast in ML Program #28595 — Support bool Cast in ML Program (prerequisite)
• [CoreML EP] Add Sin and Cos unary ops #28596 — Add Sin and Cos unary ops (this PR — independent)
• [CoreML EP] Add Where and And builders #28597 — Add Where and And builders (depends on [CoreML EP] Support bool Cast in ML Program #28595)
• [CoreML EP] Add GatherND builder #28598 — Add GatherND builder (depends on [CoreML EP] Support bool Cast in ML Program #28595)

Together with #28278 (scalar-Gather), the series takes BERT / GPT-2 / ViT /
diffusion-UNet graphs — tiny and full-size — from 2 CoreML partitions to 1, with
zero graph breaks.