mlpack::ann::Subview< InputDataType, OutputDataType > Class Template Reference

Implementation of the subview layer. More...

#include <subview.hpp>

Public Member Functions
	Subview (const size_t inSize=1, const size_t beginRow=0, const size_t endRow=0, const size_t beginCol=0, const size_t endCol=0)
	Create the Subview layer object using the specified range of input to accept. More...
template<typename InputType , typename OutputType >
void	Forward (const InputType &input, OutputType &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	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 &	OutputParameter () const
	Get the output parameter.
OutputDataType &	OutputParameter ()
	Modify the output parameter.
OutputDataType const &	Delta () const
	Get the delta.
OutputDataType &	Delta ()
	Modify the delta.
size_t	InSize () const
	Get the width of each sample.
size_t const &	BeginRow () const
	Get the starting row index of subview vector or matrix.
size_t &	BeginRow ()
	Modify the width of each sample.
size_t const &	EndRow () const
	Get the ending row index of subview vector or matrix.
size_t &	EndRow ()
	Modify the width of each sample.
size_t const &	BeginCol () const
	Get the width of each sample.
size_t &	BeginCol ()
	Modify the width of each sample.
size_t const &	EndCol () const
	Get the ending column index of subview vector or matrix.
size_t &	EndCol ()
	Modify the width of each sample.
template<typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the layer.

Detailed Description

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::Subview< InputDataType, OutputDataType >

Implementation of the subview layer.

The subview layer modifies the input to a submatrix of required size.

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).

Constructor & Destructor Documentation

Subview()

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

mlpack::ann::Subview< InputDataType, OutputDataType >::Subview ( const size_t  inSize = 1, const size_t  beginRow = 0, const size_t  endRow = 0, const size_t  beginCol = 0, const size_t  endCol = 0  )

inline

Create the Subview layer object using the specified range of input to accept.

Parameters

inSize	Width of sample.
beginRow	Starting row index.
endRow	Ending row index.
beginCol	Starting column index.
endCol	Ending column index.

Member Function Documentation

Backward()

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

template<typename eT >

void mlpack::ann::Subview< InputDataType, OutputDataType >::Backward ( const arma::Mat< eT > &  , const arma::Mat< eT > &  gy, arma::Mat< eT > &  g  )

inline

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.

Forward()

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

template<typename InputType , typename OutputType >

void mlpack::ann::Subview< InputDataType, OutputDataType >::Forward ( const InputType &  input, OutputType &  output  )

inline

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.

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

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