Class BiasAdd

Namespace

NeuralNetworks.Operations

Assembly

NeuralNetworks.dll

Computes bias addition.

public class BiasAdd : ParamOperation2D<float[]>

Inheritance

object

Operation

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

Operation2D

ParamOperation2D

ParamOperation2D<float[]>

BiasAdd

Inherited Members

ParamOperation2D<float[]>.Param

ParamOperation2D<float[]>.ParamGradient

ParamOperation2D<float[]>.Backward(float[,])

ParamOperation2D<float[]>.EnsureSameShapeForParam(float[], float[])

ParamOperation2D<float[]>.CalcParamGradient(float[,])

ParamOperation2D<float[]>.CloneBase()

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)

object.ToString()

Constructors

BiasAdd(float[])

Computes bias addition.

public BiasAdd(float[] bias)

Parameters

bias float[]

Bias matrix.

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[,]

CalcParamGradient(float[,])

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

Parameters

outputGradient float[,]

Returns

float[]

EnsureSameShapeForParam(float[]?, float[])

protected override void EnsureSameShapeForParam(float[]? param, float[] paramGradient)

Parameters

param float[]

paramGradient float[]

GetParamCount()

public override int GetParamCount()

Returns

int

UpdateParams(Layer?, Optimizer)

public override void UpdateParams(Layer? layer, Optimizer optimizer)

Parameters

layer Layer

optimizer Optimizer