GRU Layer - Gated recurrent unit (GRU) layer for recurrent neural network (RNN) - Simulink (original) (raw)

Gated recurrent unit (GRU) layer for recurrent neural network (RNN)

Since R2025a

Libraries:
Deep Learning Toolbox / Deep Learning Layers / Sequence Layers

Description

The GRU Layer block represents a recurrent neural network (RNN) layer that learns dependencies between time steps in time-series and sequence data in theCT format (two dimensions corresponding to channels and time steps, in that order).

The exportNetworkToSimulink function generates this block to represent agruLayer object.

Limitations

• The Layer parameter does not acceptgruLayer objects that have theHasStateInputs or HasStateOutputs properties set to 1 (true).

Ports

Input

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Input data. The data must have two dimensions corresponding to channels and time steps, in that order, or one dimension corresponding to channels.

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

Output

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The result of applying the GRU operation to the input data. The output data has two dimensions corresponding to channels and time steps, in that order.

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

Parameters

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

Main

Specify the name of a workspace variable that contains agruLayer object from a trained network. TheGRU Layer block configures itself by using the properties of the object and calculates the block output by using the learnable parameters of the object.

Programmatic Use

Data format for the input data. The options use the same notation as the fmt argument of thedlarray object, except layer blocks do not support the Batch (B) dimension and instead assume an observation number of1.

Programmatic Use

Whether to use stateful prediction, specified as a boolean. Iftrue, the block maintains the hidden state between time steps. If false, the block performs stateless prediction by resetting the hidden states to their initial values at the beginning of each time step. Use stateless prediction for frame-based processing where Simulink step time represents frame period and the network processes multiple samples at each time step. For more information, seeSample- and Frame-Based Concepts (DSP System Toolbox).

Programmatic Use

Data Types

If the object that you pass as the value of the Layer parameter uses the tanh state activation function or thesigmoid gate activation function, then the block uses the approximation method that you specify to compute the layer output.

For more information about the CORDIC approximation method, see cordictanh (Fixed-Point Designer).

Programmatic Use

Lower value of the output range that the software checks.

The software uses the minimum to perform:

• Parameter range checking (see Specify Minimum and Maximum Values for Block Parameters (Simulink)) for some blocks.
• Simulation range checking (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.

Dependencies

To enable this parameter, set Output data type to a value other than Inherit: Inherit via internal rule.

Programmatic Use

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

Upper value of the output range that the software checks.

The software uses the maximum value to perform:

• Parameter range checking (see Specify Minimum and Maximum Values for Block Parameters (Simulink)) for some blocks.
• Simulation range checking (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.

Dependencies

To enable this parameter, set Output data type to a value other than Inherit: Inherit via internal rule.

Programmatic Use

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

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 choose Inherit: Inherit via internal rule, Simulink sets the output data type to the same type as the hidden state.

Programmatic Use

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

Select this parameter to prevent the fixed-point tools 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.

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.

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 asint8 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 defaultoff 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.

The block casts the value of the InputWeights property of the object that you specify with the Layer parameter to this data type. The type can be inherited, specified directly, or expressed as a data type object such as Simulink.NumericType.

Programmatic Use

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

The block casts the value of the RecurrentWeights property of the object that you specify with the Layer parameter to this data type. The type can be inherited, specified directly, or expressed as a data type object such as Simulink.NumericType.

Programmatic Use

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

The block casts the value of the Bias property of the object that you specify with the Layer parameter to this data type.The type can be inherited, specified directly, or expressed as a data type object such as Simulink.NumericType.

Programmatic Use

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

The block casts the value of the HiddenState property of the object that you specify with theLayer parameter to this data type.The type can be inherited, specified directly, or expressed as a data type object such as Simulink.NumericType.

This parameter affects only the initial hidden state, _h_0. To cast later hidden state values, use theHidden state parameter. For more information, see Gated Recurrent Unit Layer.

Programmatic Use

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

Choose the data type for the output of the subsystemForIteratorSubsystem/HiddenState inside theGRU Layer block. 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, Simulink chooses a data type to balance numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware.

For a time step t, the subsystem computes the hidden state h t as

, where ⊙ denotes the Hadamard product (element-wise multiplication of vectors). For more information, see Gated Recurrent Unit Layer.

Programmatic Use

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

Choose the data type for the output of the Product block InputWeightsMatrixMultiply/W*x inside theGRU Layer block. 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, Simulink chooses a data type to balance numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware.

For a time step t, the Product block computes the product of the input weights (W) and the input at the time step (x t). For more information, see Gated Recurrent Unit Layer.

Programmatic Use

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

Choose the data type for the output of the Matrix Multiply blocks inside these subsystems inside theGRU Layer block.

• ForIteratorSubsystem/ResetGateMode/ResetGateMode_after-multiplication/R*h terms
• ForIteratorSubsystem/ResetGateMode/ResetGateMode_before-multiplication/R*h terms
• ForIteratorSubsystem/ResetGateMode/ResetGateMode_recurrent-bias-after-multiplication/R*h terms

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, Simulink chooses a data type to balance numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware.

For a time step t, the Product block computes the product of the recurrent weights (R) and the hidden state at the previous time step (h _t_-1). For more information, see Gated Recurrent Unit Layer.

Programmatic Use

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

Execution

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.

Extended Capabilities

Version History

Introduced in R2025a