Class WeightMultiply

Namespace

NeuralNetworks.Operations.Parameterized

Assembly

NeuralNetworks.dll

Weight multiplication operation for a neural network.

public class WeightMultiply : ParamOperation<float[,], float[,], float[,]>, IParamOperation

Inheritance

object

Operation

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

ParamOperation<float[,], float[,]>

ParamOperation<float[,], float[,], float[,]>

WeightMultiply

Implements

IParamOperation

Inherited Members

ParamOperation<float[,], float[,], float[,]>.Param

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

ParamOperation<float[,], float[,], float[,]>.GetRegularizationLoss()

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

ParamOperation<float[,], float[,], float[,]>.GetData()

ParamOperation<float[,], float[,], float[,]>.ApplyData(ParamOperationData, int, int)

ParamOperation<float[,], float[,], float[,]>.GetParamCount()

ParamOperation<float[,], float[,], float[,]>.UpdateParams(Optimizer)

ParamOperation<float[,], float[,]>.GetParamCount()

ParamOperation<float[,], float[,]>.UpdateParams(Optimizer)

ParamOperation<float[,], float[,]>.GetData()

ParamOperation<float[,], float[,]>.ApplyData(ParamOperationData, int, int)

ParamOperation<float[,], float[,]>.GetRegularizationLoss()

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)

Operation.ToString()

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

Constructors

WeightMultiply(float[,], IRegularizer?)

Weight multiplication operation for a neural network.

public WeightMultiply(float[,] weights, IRegularizer? regularizer = null)

Parameters

weights float[,]

Weight matrix.

regularizer IRegularizer

Optional regularizer applied to the weights.

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[,]