Qwen 3.5 MoE: Add Metal source transformations

[manuelcandales]

Adds metal_source_transformations.py with module replacements for Metal:

• FusedMoEExperts -> MetalMoEExperts (two metal::gather_qmv calls with
  SiLU gating, replacing torch.ops.triton.fused_moe)
• GatedDeltaNet -> metal::gated_delta_rule custom op (replaces both the
  T=1 native path and T>1 Triton kernel)
• FullAttention -> removes turboquant codepath, keeps standard SDPA
• SparseMoE -> removes .float() cast on expert_weights

Also includes quantize_experts_metal() which quantizes expert weights to
MLX affine INT4 format (unsigned uint4 with scale + bias per group),
compatible with the Metal gather_qmv kernel.

Authored with Claude.

[manuelcandales]

Stack from ghstack (oldest at bottom):

• Qwen 3.5 MoE Metal: Use max-sized prefill example for dynamic inputs #18956
• Qwen 3.5 MoE: Add Metal build target #18881
• Qwen 3.5 MoE: Add --backend metal export path #18880
• -> Qwen 3.5 MoE: Add Metal source transformations #18879
• Metal backend: Add gated delta rule kernel for linear attention #18878
• Metal backend: Add gather_qmv kernel for MoE expert-indexed quantized matmul #18877
• Metal backend: Add topk fallback kernel via MPSGraph #18876
• Metal backend: Add SDPA head_dim=256 support #18875
• Metal backend: Add INT32 and BOOL dtype support #18874

[pytorch-bot]

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[metascroy]

For future work, maybe we should fuse the q/k expansion into the kernel

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