ggml_layer_dense: Add Dense (Fully Connected) Layer

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Add Dense (Fully Connected) Layer

Description

Add Dense (Fully Connected) Layer

Usage

ggml_layer_dense(
  model,
  units,
  activation = NULL,
  input_shape = NULL,
  name = NULL,
  trainable = TRUE
)

Arguments

model	A ggml_sequential_model object
units	Number of output units
activation	Activation function name: "relu", "sigmoid", "tanh", "softmax", or NULL
input_shape	Integer or integer vector specifying the input shape (only needed for the first layer)
name	Optional character name for the layer.
trainable	Logical; whether the layer weights are updated during training.

Value

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

Examples

model <- ggml_model_sequential() |>
  ggml_layer_conv_2d(32, c(3,3), activation = "relu",
                     input_shape = c(28, 28, 1)) |>
  ggml_layer_flatten() |>
  ggml_layer_dense(128, activation = "relu")

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