splitLayer - Split layer - MATLAB (original) (raw)

Description

Use dlhdl.layer.splitLayer objects to create a split layer. You can use split layers to divide a layer output into equal parts along the channel dimension of the image.

Creation

Syntax

Description

`layer` = dlhdl.layer.splitLayer(`Name`,[numOutputGroups](#mw%5F870c1b87-0977-464f-abf5-eb9630c4e5d4)) creates a split layer, sets the Name property, and splits the output of the layer into equal parts specified by the numOutputGroups argument along the channel dimension of the image.

example

Input Arguments

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Number of groups to split layer output into, specified as a positive integer.

Example: 2

Properties

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Layer

Data Types: char | string

This property is read-only.

Number of inputs to the layer, stored as 1. This layer accepts a single input only.

Data Types: double

This property is read-only.

Input names, stored as {'in'}. This layer accepts a single input only.

Data Types: cell

This property is read-only.

Number of outputs from the layer, returned as positive integer. Specify the number of outputs using numOutputGroups.

This property is read-only.

Output names of the layer, returned as a string array or a cell array of character vectors.

If numOutputGroups is 1, then the software sets OutputNames to {'out'}. IfnumOutputGroups is greater than 1, then the software sets OutputNames to{'out1',...,'outM'}, where M is the number of outputs.

Examples

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Create a split layer with the name split.

s = dlhdl.layer.splitLayer("split",2)

s =

splitLayer with properties:

       Name: 'split'
 NumOutputs: 2
OutputNames: {'out1'  'out2'}

Learnable Parameters No properties.

State Parameters No properties.

Show all properties

Include the split layer in a Layer array.

imageSize = [20 20 16]; layers = [ imageInputLayer(imageSize,"Name","imageinput","Normalization","none") convolution2dLayer(3,16,"Padding","same") dlhdl.layer.splitLayer("split",2) maxPooling2dLayer(3,'Padding','same','Name','pool')]

layers =

4×1 Layer array with layers:

 1   'imageinput'   Image Input                20×20×16 images
 2   ''             2-D Convolution            16 3×3 convolutions with stride [1  1] and padding 'same'
 3   'split'        dnnfpga.layer.splitLayer   dnnfpga.layer.splitLayer
 4   'pool'         2-D Max Pooling            3×3 max pooling with stride [1  1] and padding 'same'

Version History

Introduced in R2025a