Enum GraphAttn 

pub enum GraphAttn<'a> {
    Full {
        wq: GraphW<'a>,
        wk: GraphW<'a>,
        wv: GraphW<'a>,
        wo: GraphW<'a>,
        q_norm: Option<&'a [f32]>,
        k_norm: Option<&'a [f32]>,
        bias: Option<(&'a [f32], &'a [f32], &'a [f32])>,
        output_gate: bool,
        cpu_k: &'a [Vec<f32>],
        cpu_v: &'a [Vec<f32>],
    },
    Gdn {

        qkv: GraphW<'a>,
        z: GraphW<'a>,
        a: GraphW<'a>,
        b: GraphW<'a>,
        out: GraphW<'a>,
        conv1d: &'a [f32],
        a_log: &'a [f32],
        dt_bias: &'a [f32],
        norm: &'a [f32],
        nv: usize,
        nk: usize,
        dk: usize,
        dv: usize,
        kk: usize,
    
},
}

A layer’s token-mixing op: standard attention or a GDN (linear-attention) block. The surrounding norms + SwiGLU FFN are common to both.

Variants

Full

Fields

wq: GraphW<'a>

wk: GraphW<'a>

wv: GraphW<'a>

wo: GraphW<'a>

q_norm: Option<&'a [f32]>

k_norm: Option<&'a [f32]>

bias: Option<(&'a [f32], &'a [f32], &'a [f32])>

(bq, bk, bv) attention biases (Qwen2). None ⇒ no bias.

output_gate: bool

Qwen3.5 gated attention: wq emits 2·nh·hd (q||gate per head), the attention output is scaled by sigmoid(gate) before the O projection.

cpu_k: &'a [Vec<f32>]

cpu_v: &'a [Vec<f32>]

Gdn

Fields

qkv: GraphW<'a>

z: GraphW<'a>

a: GraphW<'a>

b: GraphW<'a>

out: GraphW<'a>

conv1d: &'a [f32]

a_log: &'a [f32]

dt_bias: &'a [f32]

norm: &'a [f32]

nv: usize

nk: usize

dk: usize

dv: usize

kk: usize