Class GRUCell

Cell class for the GRU layer.

Inheritance

System.Object

Keras

Base

BaseLayer

RNN

GRUCell

Implements

System.IDisposable

Inherited Members

BaseLayer.Set(BaseLayer[])

Base.Parameters

Base.None

Base.Init()

Base.ToPython()

Base.InvokeStaticMethod(Object, String, Dictionary<String, Object>)

Base.InvokeMethod(String, Dictionary<String, Object>)

Base.Item[String]

Keras.Instance

Keras.keras

Keras.keras2onnx

Keras.tfjs

Keras.Dispose()

Keras.ToTuple(Array)

Keras.ToList(Array)

System.Object.Equals(System.Object)

System.Object.Equals(System.Object, System.Object)

System.Object.GetHashCode()

System.Object.GetType()

System.Object.MemberwiseClone()

System.Object.ReferenceEquals(System.Object, System.Object)

System.Object.ToString()

Namespace: Keras.Layers

Assembly: Keras.dll

Syntax

public class GRUCell : RNN, IDisposable

Constructors

GRUCell(Int32, String, String, Boolean, String, String, String, String, String, String, String, String, String, String, Single, Single, Int32, Boolean)

Initializes a new instance of the GRUCell class.

Declaration

public GRUCell(int units, string activation = "tanh", string recurrent_activation = "hard_sigmoid", bool use_bias = true, string kernel_initializer = "glorot_uniform", string recurrent_initializer = "orthogonal", string bias_initializer = "zeros", string kernel_regularizer = "", string recurrent_regularizer = "", string bias_regularizer = "", string activity_regularizer = "", string kernel_constraint = "", string recurrent_constraint = "", string bias_constraint = "", float dropout = 0F, float recurrent_dropout = 0F, int implementation = 1, bool reset_after = false)

Parameters

Type	Name	Description
System.Int32	units	Positive integer, dimensionality of the output space.
System.String	activation	Activation function to use (see activations). Default: hyperbolic tangent (tanh). If you pass None, no activation is applied (ie. "linear" activation: a(x) = x).
System.String	recurrent_activation	Activation function to use for the recurrent step (see activations). Default: hard sigmoid (hard_sigmoid). If you pass None, no activation is applied (ie. "linear" activation: a(x) = x).
System.Boolean	use_bias	Boolean, whether the layer uses a bias vector.
System.String	kernel_initializer	Initializer for the kernel weights matrix, used for the linear transformation of the inputs (see initializers).
System.String	recurrent_initializer	Initializer for the recurrent_kernel weights matrix, used for the linear transformation of the recurrent state (see initializers).
System.String	bias_initializer	Initializer for the bias vector (see initializers).
System.String	kernel_regularizer	Regularizer function applied to the kernel weights matrix (see regularizer).
System.String	recurrent_regularizer	Regularizer function applied to the recurrent_kernel weights matrix (see regularizer).
System.String	bias_regularizer	Regularizer function applied to the bias vector (see regularizer).
System.String	activity_regularizer	Regularizer function applied to the output of the layer (its "activation"). (see regularizer).
System.String	kernel_constraint	Constraint function applied to the kernel weights matrix (see constraints).
System.String	recurrent_constraint	Constraint function applied to the recurrent_kernel weights matrix (see constraints).
System.String	bias_constraint	Constraint function applied to the bias vector (see constraints).
System.Single	dropout	Float between 0 and 1. Fraction of the units to drop for the linear transformation of the inputs.
System.Single	recurrent_dropout	Float between 0 and 1. Fraction of the units to drop for the linear transformation of the recurrent state.
System.Int32	implementation	Implementation mode, either 1 or 2. Mode 1 will structure its operations as a larger number of smaller dot products and additions, whereas mode 2 will batch them into fewer, larger operations. These modes will have different performance profiles on different hardware and for different applications.
System.Boolean	reset_after	GRU convention (whether to apply reset gate after or before matrix multiplication). False = "before" (default), True = "after" (CuDNN compatible).

Implements

System.IDisposable