Class LSTM

Represents an LSTM recurrent layer. This generates an output tensor by computing a one-layer LSTM (long short-term memory) on an input tensor.

Inheritance

Object

Layer

LSTM

Inherited Members

Layer.inputs

Layer.name

Layer.outputs

Layer.flags

Object.Equals(Object)

Object.Equals(Object, Object)

Object.ReferenceEquals(Object, Object)

Object.GetHashCode()

Object.GetType()

Object.MemberwiseClone()

Namespace: Unity.Sentis.Layers

Syntax

[Serializable]
public class LSTM : Layer

Constructors

LSTM(String, String[], String[], Int32, RnnDirection, RnnActivation[], Single[], Single[], Single, Boolean, RnnLayout)

Initializes and returns an instance of a Long Short-Term Memory Network (LSTM) recurrent layer.

Declaration

public LSTM(string name, string[] inputs, string[] outputs, int hiddenSize, RnnDirection direction, RnnActivation[] activations = null, float[] activationAlpha = null, float[] activationBeta = null, float clip = 3.40282347E+38F, bool inputForget = false, RnnLayout layout = RnnLayout.SequenceFirst)

Parameters

Type	Name	Description
String	name	The name to use for the first output tensor of the layer.
String[]	inputs	The names to use for the input tensors of the layer [X, W, R, (B, sequenceLens, initialH, initialC, P)]. X is the name of the input sequences tensor. W is the name of the weights tensor for the gates of the LSTM. R is the name of the recurrent weights tensor for the gates of the LSTM. B is the name of the optional bias tensor for the input gate of the LSTM. sequenceLens is the name of the optional 1D tensor specifying the lengths of the sequences in a batch. initialH is the name of the optional initial values tensor of the hidden neurons of the LSTM. If this is null then 0 is used. initialC is the name of the optional initial values tensor of the cells of the LSTM. If this is null then 0 is used. P is the name of the optional weight tensor for the peepholes of the LSTM. If this is null then 0 is used.///
String[]	outputs	The names for the output tensors of the layer [Y, Y_h, Y_c]. Y is the name of the concatenated intermediate output values tensor of the hidden neurons. Y_h is the name of the last output values tensor of the hidden neurons. Y_c is the name of the last output values tensor of the cells.
Int32	hiddenSize	The number of neurons in the hidden layer of the LSTM.
RnnDirection	direction	The direction of the LSTM as an RnnDirection.
RnnActivation[]	activations	The activation functions of the LSTM as an array of RnnActivation. If this is null then the LSTM uses the corresponding defaults for the given activations.
Single[]	activationAlpha	The alpha values of the activation functions of the LSTM. If this is null then the LSTM uses [0, 0, 0...].
Single[]	activationBeta	The beta values of the activation functions of the LSTM. If this is null then the LSTM uses the corresponding defaults for the given activations.
Single	clip	The cell clip threshold of the LSTM. The default value is float.MaxValue.
Boolean	inputForget	Whether to forget the input values in the LSTM. If this is false the input and forget gates are coupled. The default value is false.
RnnLayout	layout	The layout of the tensors as an RnnLayout. The default value is RnnLayout.SequenceFirst.

Fields

activationAlpha

The alpha values of the activation functions of the LSTM.

Declaration

public float[] activationAlpha

Field Value

Type	Description
Single[]

activationBeta

The beta values of the activation functions of the LSTM.

Declaration

public float[] activationBeta

Field Value

Type	Description
Single[]

activations

The activation functions of the LSTM as an array of RnnActivation.

Declaration

public RnnActivation[] activations

Field Value

Type	Description
RnnActivation[]

clip

The cell clip threshold of the LSTM.

Declaration

public float clip

Field Value

Type	Description
Single

direction

The direction of the LSTM as an RnnDirection.

Declaration

public RnnDirection direction

Field Value

Type	Description
RnnDirection

hiddenSize

The number of neurons in the hidden layer of the LSTM.

Declaration

public int hiddenSize

Field Value

Type	Description
Int32

inputForget

Whether to forget the input values in the LSTM. If this is false the input and forget gates are coupled.

Declaration

public bool inputForget

Field Value

Type	Description
Boolean

layout

The layout of the tensors as an RnnLayout.

Declaration

public RnnLayout layout

Field Value

Type	Description
RnnLayout

Properties

NumDirections

The number of directions of the LSTM inferred from the direction.

Declaration

public int NumDirections { get; }

Property Value

Type	Description
Int32

Methods

Execute(Tensor[], ExecutionContext)

Executes the layer using the operations and variables from the ExecutionContext and returns the output tensor.

If the layer has more than one output, output tensors are saved to variables.

Declaration

public override Tensor Execute(Tensor[] inputTensors, ExecutionContext ctx)

Parameters

Type	Name	Description
Tensor[]	inputTensors
ExecutionContext	ctx

Returns

Type	Description
Tensor

Overrides

Layer.Execute(Tensor[], ExecutionContext)

ToString()

Returns a string that represents the Layer.

Declaration

public override string ToString()

Returns

Type	Description
String

Overrides

Layer.ToString()