Module gdn 

Qwen-style Gated Delta Net (GDN) — linear-attention / SSM recurrent primitive for hybrid arches (qwen35, qwen35moe, qwen3next, …).

Distinct from Kimi KDA (kda.rs): GDN uses a fused QKV projection, a single depthwise ssm_conv1d over the concatenated QKV channels, per-head ssm_alpha / ssm_beta gates, and decay exp(softplus(α + ssm_dt) · ssm_a) (GGUF ssm_a is typically -exp(A_log)). KDA is not a drop-in for this graph.

GGUF tensor name mapping (per layer L)

Role	GGUF name
Fused Q‖K‖V	blk.{L}.attn_qkv.weight
Output / z gate	blk.{L}.attn_gate.weight
Depthwise causal conv	blk.{L}.ssm_conv1d.weight
Decay bias	blk.{L}.ssm_dt.bias (alt: ssm_dt)
Decay scale	blk.{L}.ssm_a
Input gate β	blk.{L}.ssm_beta.weight
Forget raw α	blk.{L}.ssm_alpha.weight
Output RMSNorm	blk.{L}.ssm_norm.weight
Output projection	blk.{L}.ssm_out.weight

Legacy qwen3next may pack β/α into ssm_ba or fuse QKV+z into ssm_in; this module implements the split qwen35 layout only.

GGUF weight load skeleton: crate::hybrid_gguf_loader. Serve still fail-closed — factory HybridEngine::reject.

Structs

GdnConfig

Tiny-config dims for the Qwen35-style GDN step (equal K/V heads).

GdnState

Fixed-size recurrent + short-conv state (unlike growing KV).

GdnWeights

Weights matching the qwen35 GGUF layout (see module docs).

Functions

gdn_forward_token

One decode step. Assumes num_k_heads == num_v_heads and head_k_dim == head_v_dim == cfg.head_dim.