Dropout Layer

R2026b

Dropout layer

Since R2024b

• 

Dropout Layer block

To add a block to a model, double-click the canvas and start typing the block name. Then, select the block from the list.

Libraries:
Deep Learning Toolbox / Deep Learning Layers / Utility Layers

Description

The Dropout Layer block represents a dropout layer in a deep learning network. At training time, a dropout layer randomly sets input elements to zero with a given probability. At prediction time, the output of a dropout layer is equal to its input.

The exportNetworkToSimulink function generates this block to represent a dropoutLayer object. Because deep learning layer blocks can be used only for prediction, this block has no effect.

Examples

Export Neural Network to Simulink as Layer Blocks

Export a trained neural network to Simulink^® as layer blocks.

For most workflows, you do not need to create neural networks in Simulink. Instead, import or train a neural network in MATLAB^® and export it to Simulink.

Suppose that you have a trained neural network net specified as a dlnetwork object. Export the network to Simulink using the exportNetworkToSimulink function.

mdlInfo = exportNetworkToSimulink(net)

The exported Simulink model represents the neural network as a subsystem. To view the layer blocks, open the subsystem. This example shows the first few blocks of a neural network.

To view and edit the layer block parameters, open the corresponding layer block mask. This example shows the parameters for the ReLU block.

Using the layer block parameters, you can configure aspects like data types and execution options like sample times.

Ports

Input

In — Input matrix

scalar | vector | matrix

Input data.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fixed point

Output

Out — Output matrix

scalar | vector | matrix

Output data that is equal to the input data.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fixed point

Parameters

To edit block parameters interactively, use the Property Inspector. From the Simulink Toolstrip, on the Simulation tab, in the Prepare gallery, select Property Inspector.

Execution

Sample time — Option to specify sample time

-1 (default) | scalar

Specify the discrete interval between sample time hits or specify another type of sample time, such as continuous (0) or inherited (-1). For more options, see Types of Sample Time (Simulink).

By default, the block inherits its sample time based on the context of the block within the model.

Programmatic Use

To set the block parameter value programmatically, use the set_param (Simulink) function.

Parameter: SampleTime

Data Types: char

Values: '-1' | scalar

Default: '-1'

Programmatic Use: Add Block

To add the block programmatically, use the add_block function with one of these library block paths as the source.

"dlutilitylib/Dropout Layer"

Example: add_block("dlutilitylib/Dropout Layer","myModel/myBlock",MakeNameUnique="on")

Extended Capabilities

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

Version History

Introduced in R2024b