---
title: "rmsNorm"
sidebar_label: "rmsNorm"
description: "Kotlin binding reference: rmsNorm."
---

<!-- Generated by tools/api_reference/generate_api_docs.py. Do not edit. -->

//[clika-runtime](../../../index.md)/[io.clika.runtime](../index.md)/[Ops](index.md)/[rmsNorm](rmsNorm.md)

# rmsNorm

[common]\
fun [rmsNorm](rmsNorm.md)(input: [Tensor](../Tensor/index.md), normalizedShape: [LongArray](https://kotlinlang.org/api/core/kotlin-stdlib/kotlin/-long-array/index.html), weight: [Tensor](../Tensor/index.md)? = null, bias: [Tensor](../Tensor/index.md)? = null, eps: [Double](https://kotlinlang.org/api/core/kotlin-stdlib/kotlin/-double/index.html)? = null, activation: [Activation](../Activation/index.md)? = null): [Tensor](../Tensor/index.md)

`rmsNorm(input: Tensor, normalizedShape: LongArray, weight: Tensor? = null, bias: Tensor? = null, eps: Double? = null, activation: Activation? = null)`: the `rms_norm` operator. Root-mean-square normalization over the trailing `normalized_shape` dims (no mean subtraction). The transformer-style norm: statistics are the mean SQUARE only, per position over the trailing dims. Optional fused `activation` applies to the post-affine value (gated kinds are not accepted).