Llama.cpp updates GDN normalization to match flash-linear-attention's l2norm.

The official source reports this update: b10829: models : fix GDN normalization from max to rsqrt. models : fix GDN normalization from max to rsqrt ( #28068 ) models: use flash-linear-attention's l2norm for gated delta net q/k The GDN q/k normalization is defined by flash-linear-attention as l2norm(x) = x * rsqrt(sum(x*x) + eps) with eps inside the root. Every GDN call site in the tree uses ggml_l2_norm instead, which is x / max(sqrt(sum(x*x)), eps), i.e. torch.nn.functional.normalize - its CUDA kernel cites that page. The clamp never engages at these magnitudes, so in practice llama.cpp normalizes with no epsilon at all where the reference has one inside the root.