ReLU Layer

R2026b

Rectified linear unit (ReLU) layer

Since R2024b

• 

ReLU 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 / Activation Layers

Description

The ReLU Layer block applies the rectified linear unit (ReLU) activation operation on layer input. ReLU activation performs a nonlinear threshold operation where any input value less than zero is set to zero.

This operation is equivalent to:

$$\text{ReLU}(x)=\{\begin{array}{cc}x,& x>0\\ 0,& x\le 0\end{array}$$

The exportNetworkToSimulink function generates this block to represent a reluLayer object. Because it applies an element-wise operation, this block supports input data of any format and outputs data that has the same dimensions and format as the input.

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

Port_1 — Input data

scalar | vector | matrix

The data on which to perform the nonlinear threshold operation.

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

Output

Port_1 — Output data

scalar | vector | matrix

The result of performing the nonlinear threshold operation on the input matrix. Values less than zero in the input matrix become zero.

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.

Data Types

Output minimum — Minimum output value for range checking

[] (default) | scalar

Minimum value of the output range that the software checks.

The software uses the minimum value to perform:

• Parameter range checking for some blocks. For more information, see Specify Minimum and Maximum Values for Block Parameters (Simulink).

• Simulation range checking. For more information, see Specify Signal Ranges (Simulink) and Enable Simulation Range Checking (Simulink).

• Automatic scaling of fixed-point data types.

• Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes, such as SIL or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Tips

Output minimum does not saturate or clip the actual output signal. Use the Saturation (Simulink) block instead.

Programmatic Use

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

Parameter:	OutMin
Values:	'[]' (default) | scalar in quotes

Output maximum — Maximum output value for range checking

[] (default) | scalar

Maximum value of the output range that the software checks.

The software uses the maximum value to perform:

• Parameter range checking for some blocks. For more information, see Specify Minimum and Maximum Values for Block Parameters (Simulink).

• Simulation range checking. For more information, see Specify Signal Ranges (Simulink) and Enable Simulation Range Checking (Simulink).

• Automatic scaling of fixed-point data types.

• Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes, such as SIL or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Tips

Output maximum does not saturate or clip the actual output signal. Use the Saturation (Simulink) block instead.

Programmatic Use

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

Parameter:	OutMax
Values:	'[]' (default) | scalar in quotes

Output data type — Data type of output

Inherit: Same as first input (default) | Inherit: Keep MSB | Inherit: Keep LSB | Inherit: Inherit via back propagation | Inherit: Inherit via internal ruleInherit: Same as first input | <data type expression>

Choose the data type for the output. The type can be inherited, specified directly, or expressed as a data type object such as Simulink.NumericType. When you select Inherit: Inherit via internal rule, the software chooses a data type to balance numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware.

Before R2026a: The default value is Inherit: Inherit via internal rule.

Programmatic Use

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

Parameter:	OutDataTypeStr
Values:	'Inherit: Same as first input' (default) | 'Inherit: Keep MSB' | 'Inherit: Keep LSB' | 'Inherit: Inherit via back propagation' | 'Inherit: Inherit via internal rule' | <data type expression>

Lock output data type setting against changes by the fixed-point tools — Option to prevent Fixed-Point Tool from overriding output data type

off (default) | on

Select this parameter to prevent Fixed-Point Tool from overriding the Output data type you specify on the block. For more information, see Use Lock Output Data Type Setting (Fixed-Point Designer).

Programmatic Use

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

Parameter:	LockScale
Values:	'off' (default) | 'on'

Integer rounding mode — Rounding mode for fixed-point operations

Floor (default) | Ceiling | Convergent | Nearest | Round | Simplest | Zero

Specify the rounding mode for fixed-point operations. For more information, see Rounding Modes (Fixed-Point Designer).

Block parameters always round to the nearest representable value. To control the rounding of a block parameter, enter an expression using a MATLAB rounding function in the mask field.

Programmatic Use

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

Parameter:	RndMeth
Values:	'Floor' (default) | 'Ceiling' | 'Convergent' | 'Nearest' | 'Round' | 'Simplest' | 'Zero'

Saturate on integer overflow — Method of overflow action

off (default) | on

Specify whether integer overflows saturate or wrap.

• on — Overflows saturate to either the minimum or maximum value that the data type can represent.

• off — Overflows wrap to the appropriate value that the data type can represent.

For example, the maximum value that the signed 8-bit integer int8 can represent is 127. Any block operation result greater than the maximum value causes overflow of the 8-bit integer.

• With this parameter selected, the block output saturates at 127. Similarly, the block output saturates at a minimum output value of –128.

• With this parameter cleared, the software interprets the overflow-causing value as int8, which can produce an unintended result. For example, a block result of 130 (binary 1000 0010) expressed as int8 is –126.

Tips

• Set this parameter to on when your model has a possible overflow and you want explicit saturation protection in the generated code.

• To optimize the efficiency of your generated code, keep the default off setting for this parameter. Using the default setting also helps you avoid overspecifying how the block handles out-of-range signals. For more information, see Troubleshoot Signal Range Errors (Simulink).

• When you select this parameter, saturation applies to every internal operation on the block, not just the output or the result.

• In general, the code generation process can detect when overflow is not possible. In this case, the code generator does not produce saturation code.

Programmatic Use

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

Parameter:	SaturateOnIntegerOverflow
Values:	'off' (default) | 'on'

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.

"dlactivationlib/ReLU Layer"

Example: add_block("dlactivationlib/ReLU Layer","myModel/myBlock",MakeNameUnique="on")

For information about programmatic access to individual block parameters, see the Programmatic Use section of parameter descriptions on this page.

Extended Capabilities

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

Version History

Introduced in R2024b