Class LeakyReLU4D

Namespace

NeuralNetworks.Operations.ActivationFunctions

Assembly

NeuralNetworks.dll

public class LeakyReLU4D : ActivationFunction<float[,,,], float[,,,]>

Inheritance

object

Operation

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

ActivationFunction<float[,,,], float[,,,]>

LeakyReLU4D

Inherited Members

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

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

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

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

LeakyReLU4D(float, float)

public LeakyReLU4D(float alfa = 0.01, float beta = 1)

Parameters

alfa float

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.