Add< InputDataType, OutputDataType > Class Template Reference

Implementation of the Add module class. More...

Public Member Functions
	Add (const size_t outSize=0)
	Create the Add object using the specified number of output units. More...
template
void	Backward (const arma::Mat< eT > &, const arma::Mat< eT > &gy, arma::Mat< eT > &g)
	Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards trough f. More...
OutputDataType const &	Delta () const
	Get the delta. More...
OutputDataType &	Delta ()
	Modify the delta. More...
template
void	Forward (const arma::Mat< eT > &input, arma::Mat< eT > &output)
	Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f. More...
template
void	Gradient (const arma::Mat< eT > &, const arma::Mat< eT > &error, arma::Mat< eT > &gradient)
	Calculate the gradient using the output delta and the input activation. More...
OutputDataType const &	Gradient () const
	Get the gradient. More...
OutputDataType &	Gradient ()
	Modify the gradient. More...
OutputDataType const &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
size_t	OutputSize () const
	Get the output size. More...
OutputDataType const &	Parameters () const
	Get the parameters. More...
OutputDataType &	Parameters ()
	Modify the parameters. More...
template
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer. More...
size_t	WeightSize () const
	Get the size of weights. More...

Detailed Description

template
class mlpack::ann::Add< InputDataType, OutputDataType >

Implementation of the Add module class.

The Add module applies a bias term to the incoming data.

Template Parameters

InputDataType	Type of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataType	Type of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).

Definition at line 34 of file add.hpp.

Constructor & Destructor Documentation

Add()

Add

(

const size_t

outSize = 0

)

Create the Add object using the specified number of output units.

Parameters

outSize

The number of output units.

Member Function Documentation

Backward()

void Backward	(	const arma::Mat< eT > &	,
		const arma::Mat< eT > &	gy,
		arma::Mat< eT > &	g
	)

Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards trough f.

Using the results from the feed forward pass.

Parameters

*	(input) The propagated input activation.
gy	The backpropagated error.
g	The calculated gradient.

Delta() [1/2]

OutputDataType const& Delta ( ) const

inline

Get the delta.

Definition at line 91 of file add.hpp.

Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 93 of file add.hpp.

Forward()

void Forward	(	const arma::Mat< eT > &	input,
		arma::Mat< eT > &	output
	)

Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f.

Parameters

input	Input data used for evaluating the specified function.
output	Resulting output activation.

Gradient() [1/3]

void Gradient	(	const arma::Mat< eT > &	,
		const arma::Mat< eT > &	error,
		arma::Mat< eT > &	gradient
	)

Calculate the gradient using the output delta and the input activation.

Parameters

*	(input) The propagated input.
error	The calculated error.
gradient	The calculated gradient.

Gradient() [2/3]

OutputDataType const& Gradient ( ) const

inline

Get the gradient.

Definition at line 96 of file add.hpp.

Gradient() [3/3]

OutputDataType& Gradient ( )

inline

Modify the gradient.

Definition at line 98 of file add.hpp.

OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 86 of file add.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 88 of file add.hpp.

OutputSize()

size_t OutputSize ( ) const

inline

Get the output size.

Definition at line 101 of file add.hpp.

Parameters() [1/2]

OutputDataType const& Parameters ( ) const

inline

Get the parameters.

Definition at line 81 of file add.hpp.

Parameters() [2/2]

OutputDataType& Parameters ( )

inline

Modify the parameters.

Definition at line 83 of file add.hpp.

serialize()

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

Referenced by Add< InputDataType, OutputDataType >::WeightSize().

WeightSize()

size_t WeightSize ( ) const

inline

Get the size of weights.

Definition at line 104 of file add.hpp.

References Add< InputDataType, OutputDataType >::serialize().

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The documentation for this class was generated from the following file:

• /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.4.2/src/mlpack/methods/ann/layer/add.hpp