Kernels:

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marcsun13

/

ggml-norm

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ggml-norm

The fused RMS norm from llama.cpp (kernel_rms_norm_mul_f32) as a single kernel — normalisation and the weight multiply in one dispatch, where eager torch spells the same thing as five. A decode step runs one of these per norm per layer, so the difference is launch overhead rather than arithmetic.

weight is taken as the kernel will use it: a model whose weight is zero-centered passes 1 + w, not w. The RMSNormZeroCentered layer does that folding itself, once.

Usage

import torch
from kernels import get_kernel

norm = get_kernel("marcsun13/ggml-norm", version=1)

x = torch.randn(1, 2048, device="mps")
weight = torch.randn(2048, device="mps")

out = norm.rms_norm(x, weight, 1e-6)  # (1, 2048)