Select< InputDataType, OutputDataType > Class Template Reference

The select module selects the specified column from a given input matrix. More...

Public Member Functions
	Select (const size_t index=0, const size_t elements=0)
	Create the Select object. 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 &	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...
size_t const &	Index () const
	Get the column index. More...
size_t const &	NumElements () const
	Get the number of elements selected. More...
OutputDataType &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
template < typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the layer. More...

Detailed Description

template

<

typename

InputDataType

=

arma::mat

,

typename

OutputDataType

=

arma::mat

>

class mlpack::ann::Select< InputDataType, OutputDataType >

The select module selects the specified column from a given input matrix.

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 32 of file select.hpp.

Constructor & Destructor Documentation

Select()

Select	(	const size_t	index = 0,
		const size_t	elements = 0
	)

Create the Select object.

Parameters

index	The column which should be extracted from the given input.
elements	The number of elements that should be used.

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& Delta ( ) const

inline

Get the delta.

Definition at line 73 of file select.hpp.

Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 75 of file select.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.

Index()

size_t const& Index ( ) const

inline

Get the column index.

Definition at line 78 of file select.hpp.

NumElements()

size_t const& NumElements ( ) const

inline

Get the number of elements selected.

Definition at line 81 of file select.hpp.

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

OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 68 of file select.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 70 of file select.hpp.

serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

Referenced by Select< InputDataType, OutputDataType >::NumElements().

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

• /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/select.hpp