coder.ai.enableParameterUpdate

Enables run-time update of network parameters

Since R2025a

Syntax

updatedNet = coder.ai.enableParameterUpdate(net)

Description

updatedNet = coder.ai.enableParameterUpdate(net) enables updating learnables at run time, without the need to regenerate code. For more information, see Update Network Parameters at Run Time.

MATLAB ignores the coder.ai.enableParameterUpdate directive outside of code generation.

Examples

Update Network Parameters

This example shows how to create an entry-point function named mPredict that continuously updates the learnables of a deep learning network.

The function:

1. Loads the trained network into a persistent dlnetwork object named dlnet by using the coder.loadDeepLearningNetwork function. A persistent variable allows you to preserve the updated learnables for subsequent function calls.

2. Enables run-time update of learnables by using the coder.ai.enableParameterUpdate function. You must enable the learnables update of the dlnetwork object before updating the learnable parameters.

3. Updates the learnable parameters with the variable newLearnables.

4. Calls the predict method to predict the responses by using the updated network.

function dlOut = mPredict(dlIn, newLearnables, matfile)
%#codegen

persistent dlnet

if isempty(dlnet)
  dlnet = coder.loadDeepLearningNetwork(matfile);
end

% Enables learnables update
dlnet = coder.ai.enableParameterUpdate(dlnet);

% Update learnables
dlnet.Learnables = newLearnables;

dlOut = dlnet.predict(dlIn);
end

Input Arguments

net — Input network

dlnetwork object

Input network, specified as a dlnetwork object.

Output Arguments

updatedNet — Updated network

dlnetwork object

Updated network, specified as a dlnetwork object.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Version History

Introduced in R2025a