Chapter 13
layers/swiglu — gated FFN
github.com/openfluke/welvet/layers/swiglu✅
Why it exists
Modern decoder FFNs are SiLU(gate)⊙up → down. Projections must share Dense’s quant/backend matrix.
What it is
Gate/Up/Down Dense children; DefaultFFN(dModel); WebGPU SiLU⊙ fuse on forward.
Go example
Run:
cd welvet/examples/13-swiglu && source ../env.sh && go run .package main
import (
"fmt"
"github.com/openfluke/welvet/core"
"github.com/openfluke/welvet/layers/swiglu"
)
func main() {
l, err := swiglu.New(swiglu.DefaultFFN(64))
if err != nil {
panic(err)
}
x := core.NewTensor[float32](1, 64)
_, post, err := swiglu.Forward(l, x)
fmt.Println(len(post.Data), err)
}
Output
64 <nil>