Class ReLU2D

Namespace

NeuralNetworks.Operations.ActivationFunctions

Assembly

NeuralNetworks.dll

public class ReLU2D : ActivationFunction2D

Inheritance

object

Operation

Operation<float[,], float[,]>

Operation2D

ActivationFunction2D

ReLU2D

Inherited Members

Operation2D.EnsureSameShapeForInput(float[,], float[,])

Operation2D.EnsureSameShapeForOutput(float[,], float[,])

Operation<float[,], float[,]>.Input

Operation<float[,], float[,]>.Output

Operation<float[,], float[,]>.Forward(float[,], bool)

Operation<float[,], float[,]>.Backward(float[,])

Operation<float[,], float[,]>.EnsureSameShapeForInput(float[,], float[,])

Operation<float[,], float[,]>.EnsureSameShapeForOutput(float[,], float[,])

Operation<float[,], float[,]>.CalcOutput(bool)

Operation<float[,], float[,]>.CalcInputGradient(float[,])

Operation<float[,], float[,]>.Forward(object, bool)

Operation<float[,], float[,]>.Backward(object)

Operation<float[,], float[,]>.GetOutputType()

Operation<float[,], float[,]>.GetInputType()

Operation<float[,], float[,]>.CloneBase()

Operation<float[,], float[,]>.Clone()

Operation.SetRegistered()

Operation.GetOutputType()

Operation.GetInputType()

Operation.Forward(object, bool)

Operation.Backward(object)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

Constructors

ReLU2D(float)

public ReLU2D(float beta = 1)

Parameters

beta float

Methods

CalcInputGradient(float[,])

Calculates input gradient.

protected override float[,] CalcInputGradient(float[,] outputGradient)

Parameters

outputGradient float[,]

Returns

float[,]

Remarks

Based on outputGradient, calculates changes in input.

CalcOutput(bool)

Computes output.

protected override float[,] CalcOutput(bool inference)

Parameters

inference bool

Returns

float[,]

ToString()

Returns a string that represents the current object.

public override string ToString()

Returns

string

A string that represents the current object.