count_parameters: Count the Number of Trainable Parameters in an MLP...

In metANN: Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems

Count the Number of Trainable Parameters in an MLP Architecture

Description

Computes the total number of weights and bias terms required by a multilayer perceptron architecture.

Usage

count_parameters(architecture, input_dim = NULL)

Arguments

architecture	An object created by mlp_architecture().
input_dim	Optional positive integer specifying the number of input features. If NULL, architecture$input_dim is used.

Value

A positive integer giving the total number of parameters.

Examples

arch <- mlp_architecture(
  input_dim = 4,
  layers = list(
    dense_layer(5, activation = "relu"),
    dense_layer(1, activation = "linear")
  )
)
count_parameters(arch)

metANN documentation built on May 16, 2026, 1:06 a.m.