functionToLayerGraph

(To be removed) Convert deep learning model function to a layer graph

functionToLayerGraph will be removed in a future release. Construct layer graphs manually instead. (since R2023a) For a list of layers, see List of Deep Learning Layers. For information about developing custom layers, see Define Custom Deep Learning Layers.

Syntax

lgraph = functionToLayerGraph(fun,x)

lgraph = functionToLayerGraph(fun,x,Name,Value)

Description

lgraph = functionToLayerGraph(fun,x) returns a layer graph based on the deep learning array function fun. functionToLayerGraph converts only those operations in fun that operate on dlarray objects among the inputs in x. To include extra parameters or data in fun, see the topic Parameterizing Functions or the example Create Layer Graph from Function.

functionToLayerGraph evaluates fun(x) and traces the execution to derive an equivalent layer graph, to the extent possible. The steps in fun(x) that functionToLayerGraph can trace are both based on dlarray arguments and are supported calls for dlarray. See List of Functions with dlarray Support. For unsupported functions, functionToLayerGraph creates a PlaceholderLayer.

lgraph = functionToLayerGraph(fun,x,Name,Value) specifies options using one or more name-value pair arguments in addition to the input arguments in the previous syntax.

Examples

Create Layer Graph from Function

The simplemodel function at the end of this example creates fully connected outputs followed by a softmax operation. To create a layer graph from this function based on dlarray data, create input arrays as dlarray objects, and create a function handle to the simplemodel function including the data.

rng default % For reproducibility
X1 = dlarray(rand(10),'CB');
X2 = dlarray(zeros(10,1),'CB');
fun = @(x)simplemodel(x,X1,X2);

Call functionToLayerGraph using a dlarray for the input data X.

X = dlarray(ones(10,1),'CB');
lgraph = functionToLayerGraph(fun,X)

lgraph = 
  LayerGraph with properties:

         Layers: [2x1 nnet.cnn.layer.Layer]
    Connections: [1x2 table]
     InputNames: {1x0 cell}
    OutputNames: {1x0 cell}

Examine the resulting layers in lgraph.

disp(lgraph.Layers)

  2x1 Layer array with layers:

     1   'fc_1'   Fully Connected   10 fully connected layer
     2   'sm_1'   Softmax           softmax

function y = simplemodel(x,w,b)
y = fullyconnect(x,w,b);
y = softmax(y);
end

Input Arguments

fun — Function to convert

function handle

Function to convert, specified as a function handle.

Example: @relu

Data Types: function_handle

x — Data for function

any data type

Data for the function, specified as any data type. Only dlarray data is traced and converted to a layer graph.

Example: dlarray(zeros(12*50,23))

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical | char | string | struct | table | cell | function_handle | categorical | datetime | duration | calendarDuration | fi

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: 'GenerateLayer','placeholder-layer'

GenerateLayer — Type of layer to generate for unsupported operations

'custom-layer' (default) | 'placeholder-layer'

Type of layer to generate for unsupported operations in fun, specified as 'custom-layer' or 'placeholder-layer'.

When an operation in fun does not correspond to a layer in Deep Learning Toolbox™, the software generates a layer to represent that functionality. The 'GenerateLayer' option specifies the type of layer as follows.

• 'custom-layer' — The software generates a custom layer that performs the operation.

• 'placeholder-layer' — The software generates a PlaceholderLayer object. To create a working network in this case, see Define Custom Deep Learning Layers or Define Model as Function.

Example: 'GenerateLayer','placeholder-layer'

CustomLayerPrefix — Prefix for generated custom layers

'customLayer' (default) | char vector

Prefix for generate custom layers, specified as a char vector.

This option applies only when the 'GenerateLayer' option is 'custom-layer'. The name of each generated custom layer starts with the specified prefix.

Example: 'CustomLayerPrefix','myGeneratedLayer'

Output Arguments

lgraph — Layer graph

LayerGraph object

Layer graph, returned as a LayerGraph object.

Limitations

functionToLayerGraph does not support these deep learning operations:

• gru

• lstm

If you use functionToLayerGraph with a function that contains these operations, then the resulting layer graph contains placeholder layers.

Version History

Introduced in R2019b

R2023a: To be removed

functionToLayerGraph will be removed in a future release. Construct layer graphs manually instead. For a list of layers, see List of Deep Learning Layers. For information about developing custom layers, see Define Custom Deep Learning Layers.