ggml_group_norm: Group Normalization (Graph)

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Group Normalization (Graph)

Description

Creates a graph node for group normalization. Normalizes along ne0*ne1*n_groups dimensions. Used in Stable Diffusion and other image generation models.

Usage

ggml_group_norm(ctx, a, n_groups, eps = 1e-05)

Arguments

ctx	GGML context
a	Input tensor
n_groups	Number of groups to divide channels into
eps	Epsilon for numerical stability (default 1e-5)

Value

Tensor representing the group norm operation

Examples

ctx <- ggml_init(16 * 1024 * 1024)
# 4 channels, 2 groups (2 channels per group)
a <- ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 4, 8)
ggml_set_f32(a, rnorm(32))
result <- ggml_group_norm(ctx, a, n_groups = 2)
graph <- ggml_build_forward_expand(ctx, result)
ggml_graph_compute(ctx, graph)
ggml_free(ctx)

ggmlR documentation built on July 14, 2026, 1:08 a.m.