ggml_layer_batch_norm: Add Batch Normalization Layer

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Add Batch Normalization Layer

Description

Applies normalization: RMS-normalizes the input, then scales by gamma and shifts by beta (both learnable). Uses ggml_rms_norm which supports backward pass for training.

Usage

ggml_layer_batch_norm(model, eps = 1e-05, name = NULL, trainable = TRUE)

Arguments

model	A ggml_sequential_model object
eps	Small constant for numerical stability (default 1e-5)
name	Optional character name for the layer.
trainable	Logical; whether the layer weights are updated during training.

Value

The model object with the batch_norm layer appended (invisibly).

Examples

model <- ggml_model_sequential() |>
  ggml_layer_dense(128, input_shape = 784) |>
  ggml_layer_batch_norm() |>
  ggml_layer_dense(10, activation = "softmax")

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