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<typename eT >
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<typename eT >
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<typename eT >
void	Gradient (const arma::Mat< eT > &&, 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...
OutputDataType const &	Parameters () const
	Get the parameters. More...
OutputDataType &	Parameters ()
	Modify the parameters. More...
template<typename Archive >
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer. More...

Detailed Description

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
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

(

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

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.

OutputDataType const& Delta ( ) const

inline

Get the delta.

Definition at line 91 of file add.hpp.

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 93 of file add.hpp.

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.

void Gradient	(	const arma::Mat< eT > &&	,
		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.

OutputDataType const& Gradient ( ) const

inline

Get the gradient.

Definition at line 96 of file add.hpp.

OutputDataType& Gradient ( )

inline

Modify the gradient.

Definition at line 98 of file add.hpp.

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 86 of file add.hpp.

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 88 of file add.hpp.

OutputDataType const& Parameters ( ) const

inline

Get the parameters.

Definition at line 81 of file add.hpp.

OutputDataType& Parameters ( )

inline

Modify the parameters.

Definition at line 83 of file add.hpp.

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

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

• src/mlpack/methods/ann/layer/add.hpp