Write Triton LayerNorm Kernel
OfficialNumerically-stable Triton LayerNorm kernel.
Authortensormux
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Implements a numerically stable, fused LayerNorm kernel in Triton with optional RMSNorm support for fast, single-pass normalization across rows, including stable mean/variance computation and optional affine gamma/beta application.
Core Features & Use Cases
- Fused LayerNorm (mean subtraction + std normalization) across rows with vectorized tile processing.
- RMSNorm variant (no mean subtraction) with learnable gamma/beta and optional training path.
- Backward pass readiness: outputs mean and rstd for gradient computation and supports masking for non-divisible hidden dimensions in inputs.
Quick Start
Load the Triton kernel and run it on a (N, H) input with gamma and beta, verifying numeric stability against a reference LayerNorm.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
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Please help me install this Skill: Name: Write Triton LayerNorm Kernel Download link: https://github.com/tensormux/kernel-skills/archive/main.zip#write-triton-layernorm-kernel Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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