ag_linear: Create a dense layer with learnable parameters

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Create a dense layer with learnable parameters

Description

Returns a closure-based layer. Because ag_param uses environment semantics, the optimizer updates W and b in-place, and forward() always uses the latest weights.

Usage

ag_linear(in_features, out_features, activation = NULL)

Arguments

in_features	Input dimension
out_features	Output dimension
activation	"relu", "sigmoid", "tanh", "softmax", or NULL

Value

List with W, b, forward(x), params()

Examples

layer <- ag_linear(4L, 8L, activation = "relu")
x     <- ag_tensor(matrix(runif(4 * 16), 4, 16))
out   <- layer$forward(x)

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