Class BiasAddConv2D

Namespace

NeuralNetworks.Operations.Parameterized

Assembly

NeuralNetworks.dll

public class BiasAddConv2D : ParamOperation<float[,,,], float[,,,], float[]>, IParamOperation

Inheritance

object

Operation

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

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

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

BiasAddConv2D

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

BiasAddConv2D(float[], IRegularizer?)

public BiasAddConv2D(float[] bias, IRegularizer? regularizer = null)

Parameters

bias float[]

regularizer IRegularizer

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[]