ConcatPerformance< OutputLayerType, InputDataType, OutputDataType > Class Template Reference

Implementation of the concat performance class. More...

Public Member Functions
	ConcatPerformance (const size_t inSize=0, OutputLayerType &&outputLayer=OutputLayerType())
	Create the ConcatPerformance object. More...
template < typename eT >
void	Backward (const arma::Mat< eT > &&input, const arma::Mat< eT > &&target, arma::Mat< eT > &&output)
	Ordinary feed backward pass of a neural network. More...
OutputDataType &	Delta () const
	Get the delta. More...
OutputDataType &	Delta ()
	Modify the delta. More...
template < typename eT >
double	Forward (const arma::Mat< eT > &&input, arma::Mat< eT > &&target)
InputDataType &	InputParameter () const
	Get the input parameter. More...
InputDataType &	InputParameter ()
	Modify the input parameter. More...
OutputDataType &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
template < typename Archive >
void	serialize (Archive &, const unsigned int)
	Serialize the layer. More...

Detailed Description

template<typename OutputLayerType = NegativeLogLikelihood<>, typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::ConcatPerformance< OutputLayerType, InputDataType, OutputDataType >

Implementation of the concat performance class.

The class works as a feed-forward fully connected network container which plugs performance layers together.

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 39 of file concat_performance.hpp.

Constructor & Destructor Documentation

ConcatPerformance()

ConcatPerformance	(	const size_t	inSize = 0,
		OutputLayerType &&	outputLayer = OutputLayerType()
	)

Create the ConcatPerformance object.

Parameters

inSize	The number of inputs.
outputLayer	Output layer used to evaluate the network.

Member Function Documentation

Backward()

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

Ordinary feed backward pass of a neural network.

The negative log likelihood layer expectes that the input contains log-probabilities for each class. The layer also expects a class index, in the range between 1 and the number of classes, as target when calling the Forward function.

Parameters

input	The propagated input activation.
target	The target vector, that contains the class index in the range between 1 and the number of classes.
output	The calculated error.

Delta() [1/2]

OutputDataType& Delta ( ) const

inline

Get the delta.

Definition at line 86 of file concat_performance.hpp.

Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 88 of file concat_performance.hpp.

References ConcatPerformance< OutputLayerType, InputDataType, OutputDataType >::serialize().

Forward()

double Forward	(	const arma::Mat< eT > &&	input,
		arma::Mat< eT > &&	target
	)

InputParameter() [1/2]

InputDataType& InputParameter ( ) const

inline

Get the input parameter.

Definition at line 76 of file concat_performance.hpp.

InputParameter() [2/2]

InputDataType& InputParameter ( )

inline

Modify the input parameter.

Definition at line 78 of file concat_performance.hpp.

OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 81 of file concat_performance.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 83 of file concat_performance.hpp.

serialize()

void serialize	(	Archive &	,
		const unsigned	int
	)

Serialize the layer.

Referenced by ConcatPerformance< OutputLayerType, InputDataType, OutputDataType >::Delta().

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

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