Chapter 14
layers/rmsnorm
github.com/openfluke/welvet/layers/rmsnorm✅
Why it exists
Llama-style blocks normalize by RMS, not mean+var. Needs native fwd/bwd and WebGPU shaders.
What it is
Per-token RMS + γ on weights.Store; WebGPU fwd+bwd; SIMD DotTile stats + host scale.
Go example
Run:
cd welvet/examples/14-rmsnorm && source ../env.sh && go run .package main
import (
"fmt"
"github.com/openfluke/welvet/core"
"github.com/openfluke/welvet/layers/rmsnorm"
"github.com/openfluke/welvet/quant"
)
func main() {
gamma := []float32{1, 1, 1, 1}
l, err := rmsnorm.NewConfigured(rmsnorm.Config{Dim: 4}, core.DTypeFloat32, quant.FormatNone, gamma)
if err != nil {
panic(err)
}
x := core.NewTensor[float32](1, 4)
_, y, err := rmsnorm.Forward(l, x)
fmt.Println(y.Data, err)
}
Output
[0 0 0 0] <nil>