LSTM Projected Layer

Long short-term memory (LSTM) projected layer for recurrent neural network (RNN)

Since R2024b

• 

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

Description

The LSTM Projected Layer block represents a recurrent neural network (RNN) layer that learns long-term dependencies between time steps in time-series and sequence data in the CT format (two dimensions corresponding to channels and time steps, in that order) by using projected learnable weights.

To compress a deep learning network, you can use projected layers. A projected layer is a type of deep learning layer that enables compression by reducing the number of stored learnable parameters. The layer introduces learnable projector matrices Q, replaces multiplications of the form $$Wx$$, where W is a learnable matrix, with the multiplication $$WQ{Q}^{\top }x$$, and stores Q and $$W\prime =WQ$$ instead of storing W. Projecting x into a lower dimensional space using Q typically requires less memory to store the learnable parameters and can have similarly strong prediction accuracy.

Reducing the number of learnable parameters by projecting an LSTM layer rather than reducing the number of hidden units of the LSTM layer maintains the output size of the layer and, in turn, the sizes of the downstream layers, which can result in better prediction accuracy.

The exportNetworkToSimulink function generates this block to represent an lstmProjectedLayer object.

Limitations

• The Layer parameter does not accept lstmProjectedLayer objects that have the HasStateInputs or HasStateOutputs properties set to 1 (true).

Ports

Input

Port_1 — Input data

2-dimensional array

Input data. The data must have 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

Output

Port_1 — Output data

2-dimensional array

The result of convolving 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

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

Main

Layer — Corresponding layer object

layer (default) | lstmProjectedLayer object

Specify the name of a workspace variable that contains an lstmProjectedLayer object from a trained network. The LSTM Projected 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

Block Parameter: Layer

Type: workspace variable

Values: lstmProjectedLayer object

Default: 'layer'

Data format — Format of input data

CT (default)

Data format for the input data. The options use the same notation as the fmt argument of the dlarray object, except layer blocks do not support the Batch (B) dimension and instead assume an observation number of 1.

Programmatic Use

Block Parameter: DataFormat

Type: character vector

Values: 'CT'

Default: 'CT'

Stateful prediction — Whether to use stateful prediction

on (default) | off

Whether to use stateful prediction, specified as a boolean. If true, the block maintains the cell state and hidden state between time steps. If false, the block performs stateless prediction by resetting cell states and 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, see Sample- and Frame-Based Concepts (DSP System Toolbox).

Programmatic Use

Block Parameter: StatefulPrediction

Type: character vector

Values: 'on' | 'off'

Default: 'on'

Data Types

Activation approximation method — Approximation method for computing activation function output

None (default) | CORDIC | Lookup

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

Approximation Method	Data Types Supported	When to Use This Method
None (default)	Floating-point	You are processing only floating-point data.
CORDIC	Floating-point (double and single) and fixed-point with a Bias value of 0 and a Slope value of a power of 2	You are processing fixed-point data and want to deploy to FPGA hardware.
Lookup	Floating-point and fixed-point	You are processing fixed-point data and want to generate C/C++ code.

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

Programmatic Use

Block Parameter: ApproximationMethod

Type: character vector

Values: 'None' | 'CORDIC' | 'Lookup'

Default: 'None'

Output minimum — Minimum output value for range checking

[] (default) | scalar

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.

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

Output maximum — Maximum output value for range checking

[] (default) | scalar

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.

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

Output data type — Data type of output

Inherit: Inherit via internal rule (default) | <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 choose 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.

Programmatic Use

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

Parameter:	OutDataTypeStr
Values:	'Inherit: Inherit via internal rule' (default) | <data type expression>

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

off (default) | on

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.

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 into 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 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 this 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

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

• Consider clearing this parameter when you want to optimize efficiency of your generated code. Clearing this parameter also helps you to avoid overspecifying how a 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 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'

Input weights — Data type of input weights

Inherit: Inherit via back propagation (default) | Inherit: Inherit from 'Constant value' | <data type expression>

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.

Parameter:	InputWeightsDataTypeStr
Values:	'Inherit: Inherit via back propagation' (default) | 'Inherit: Inherit from 'Constant value'' | <data type expression>

Recurrent weights — Data type of recurrent weights

Inherit: Inherit via back propagation (default) | Inherit: Inherit from 'Constant value' | <data type expression>

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.

Parameter:	RecurrentWeightsDataTypeStr
Values:	'Inherit: Inherit via back propagation' (default) | 'Inherit: Inherit from 'Constant value'' | <data type expression>

Bias — Data type of bias

Inherit: Inherit via back propagation (default) | Inherit: Inherit from 'Constant value' | <data type expression>

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.

Parameter:	BiasDataTypeStr
Values:	'Inherit: Inherit via back propagation' (default) | 'Inherit: Inherit from 'Constant value'' | <data type expression>

Input projector weights — Data type of input projector weights

Inherit: Inherit via back propagation (default) | Inherit: Inherit from 'Constant value' | <data type expression>

The block casts the value of the InputProjector 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.

For more information, see LSTM Projected Layer.

Programmatic Use

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

Parameter:	InputProjectorWeightsDataTypeStr
Values:	'Inherit: Inherit via back propagation' (default) | 'Inherit: Inherit from 'Constant value'' | <data type expression>

Output projector weights — Data type of output projector weights

Inherit: Inherit via back propagation (default) | Inherit: Inherit from 'Constant value' | <data type expression>

The block casts the value of the OutputProjector 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.

For more information, see LSTM Projected Layer.

Programmatic Use

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

Parameter:	OutputProjectorWeightsDataTypeStr
Values:	'Inherit: Inherit via back propagation' (default) | 'Inherit: Inherit from 'Constant value'' | <data type expression>

Initial cell state — Data type of initial cell state

Inherit: Inherit via back propagation (default) | Inherit: Inherit from 'Constant value' | <data type expression>

The block casts the value of the CellState 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.

This parameter affects only the initial cell state, c₀. To cast later cell state values, use the Cell state parameter. For more information, see Long Short-Term Memory Layer

Programmatic Use

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

Parameter:	TODODataTypeStr
Values:	'Inherit: Inherit via back propagation' (default) | 'Inherit: Inherit from 'Constant value'' | <data type expression>

Cell state — Data type of cell state

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

Choose the data type for the output of the Sum block ForIteratorSubsystem/LSTMProjectedCore/CellAdd inside the LSTM Projected Layer block. 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 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 Sum block computes the cell state c_t as c_t=f_t⊙c_t-1+i_t⊙g_t, where i, f, and g denote the input gate, forget gate, and cell candidate gate, respectively, and ⊙ denotes the Hadamard product (element-wise multiplication of vectors). For more information, see Long Short-Term Memory Layer.

Programmatic Use

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

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

Initial hidden state — Data type of initial hidden state

Inherit: Inherit via back propagation (default) | Inherit: Inherit from 'Constant value' | <data type expression>

The block casts the value of the HiddenState 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.

This parameter affects only the initial hidden state, h₀. To cast later hidden state values, use the Hidden state parameter. For more information, see Long Short-Term Memory Layer

Programmatic Use

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

Parameter:	InitialHiddenStateDataTypeStr
Values:	'Inherit: Inherit via back propagation' (default) | 'Inherit: Inherit from 'Constant value'' | <data type expression>

Hidden state — Data type of hidden state

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

Choose the data type for the output of the Product block ForIteratorSubsystem/LSTMProjectedCore/HiddenStateProduct inside the LSTM Projected Layer block. 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 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 hidden state h_t as h_t=o_t⊙σ_c(c_t),where o denotes the output gate, σ_c denotes the state activation function, and ⊙ denotes the Hadamard product (element-wise multiplication of vectors). For more information, see Long Short-Term Memory Layer and LSTM Projected Layer.

Programmatic Use

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

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

Input weights matrix multiply output — Data type of input weights matrix multiply output

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

Choose the data type for the output of the Product block InputWeightsMatrixMultiply/W*x inside the LSTM Projected Layer block. 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 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 projected input at the time step (x_t). For more information, see Long Short-Term Memory Layer and LSTM Projected Layer.

Programmatic Use

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

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

Recurrent weights matrix multiply output — Data type of recurrent weights matrix multiply output

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

Choose the data type for the output of the Product block ForIteratorSubsystem/LSTMProjectedCore/RecurrentWeightsMatrixMultiply/R*h_t-1 inside the LSTM Projected Layer block. 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 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 projected hidden state at the previous time step (h_t-1). For more information, see Long Short-Term Memory Layer and LSTM Projected Layer.

Programmatic Use

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

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

Input projector weights matrix multiply output — Data type of input projector weights matrix multiply output

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

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

The Product block computes the product of the transposed input (x^T) and the input projector weights (Q_in). For more information, see LSTM Projected Layer.

Programmatic Use

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

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

Output projector weights matrix multiply output — Data type of output projector weights matrix multiply output

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

Choose the data type for the output of the Product block ForIteratorSubsystem/LSTMProjectedCore/RecurrentWeightsMatrixMultiply/h_t-1'*Q_out inside the LSTM Projected Layer block. 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 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 transposed previous hidden state (h_t-1^T) and the output projector weights (Q_out). For more information, see LSTM Projected Layer.

Programmatic Use

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

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

Linear gate accumulator — Data type of linear gate accumulator

Inherit: Inherit via internal rule (default) | Inherit: Same as first input | <data type expression>

Choose the data type for the accumulator of the Sum block ForIteratorSubsystem/LSTMProjectedCore/LinearGateAdd/Wx+Rh+b inside the LSTM Projected Layer block. 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 chooses a data type to balance numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware.

The Sum block computes the sum WQ_in^Tx+RQ_out^Th_t+b, where W denotes the input weights, Q_in denotes the input projector matrix, x denotes the input, R denotes the recurrent weights, Q_out denotes the output projector matrix, h_t denotes the hidden state at time step t, and b denotes the bias. For more information, see Long Short-Term Memory Layer.

Programmatic Use

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

Parameter:	LinearGateAccumDataTypeStr
Values:	'Inherit: Inherit via internal rule' (default) | 'Inherit: Same as first input' | <data type expression>

Linear gate add output — Data type of linear gate sum

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

Choose the data type for the output of the Sum block ForIteratorSubsystem/LSTMProjectedCore/LinearGateAdd/Wx+Rh+b inside the LSTM Projected Layer block. 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 chooses a data type to balance numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware.

The Sum block computes the sum WQ_in^Tx+RQ_out^Th_t+b, where W denotes the input weights, Q_in denotes the input projector matrix, x denotes the input, R denotes the recurrent weights, Q_out denotes the output projector matrix, h_t denotes the hidden state at time step t, and b denotes the bias. For more information, see Long Short-Term Memory Layer.

Programmatic Use

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

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

Cell state product output — Data type of cell state product

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

Choose the data type for the output of the Product blocks ForIteratorSubsystem/LSTMProjectedCore/f*c_t-1 and ForIteratorSubsystem/LSTMProjectedCore/i*g inside the LSTM Projected Layer block. 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 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 blocks compute the Hadamard products (element-wise multiplication of vectors, denoted as ⊙) f_t⊙c_t-1 and i_t⊙g_t, where f denotes the forget gate, c denotes the cell state, i denotes the input gate, and g denotes the cell candidate. For more information, see Long Short-Term Memory Layer.

Programmatic Use

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

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

Cell state accumulator — Data type of cell state accumulator

Inherit: Inherit via internal rule (default) | Inherit: Same as first input | <data type expression>

Choose the data type for the accumulator of the Sum block ForIteratorSubsystem/LSTMProjectedCore/CellAdd inside the LSTM Projected Layer block. 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 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 Sum block computes the cell state c_t as

ct=ft⊙ct-1+it⊙gt

(1)

,

where i, f, and g denote the input gate, forget gate, and cell candidate gate, respectively, and ⊙ denotes the Hadamard product (element-wise multiplication of vectors). For more information, see Long Short-Term Memory Layer.

Programmatic Use

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

Parameter:	CellStateProductOutDataTypeStr
Values:	'Inherit: Inherit via internal rule' (default) | 'Inherit: Same as first input' | <data type expression>

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 upon the context of the block within the model.

Programmatic Use

Block Parameter: SampleTime

Type: character vector

Values: scalar

Default: '-1'

Extended Capabilities

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

Version History

Introduced in R2024b