Class BiasAddConv1D

Namespace

NeuralNetworks.Operations.Parameterized

Assembly

NeuralNetworks.dll

public class BiasAddConv1D : ParamOperation<float[,,], float[,,], float[]>, IParamOperation

Inheritance

object

Operation

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

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

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

BiasAddConv1D

Implements

IParamOperation

Inherited Members

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

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

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)

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)

object.ToString()

Constructors

BiasAddConv1D(float[])

public BiasAddConv1D(float[] bias)

Parameters

bias 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[,,]

CalcParamGradient(float[,,])

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

Parameters

outputGradient float[,,]

Returns

float[]