Linear< InputDataType, OutputDataType, RegularizerType > Class Template Reference

Implementation of the Linear layer class. More...

Public Member Functions
	Linear ()
	Create the Linear object. More...
	Linear (const size_t inSize, const size_t outSize, RegularizerType regularizer=RegularizerType())
	Create the Linear layer object using the specified number of 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...
arma::mat &	Bias ()
	Modify the bias weights of the layer. 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 > &input, const arma::Mat< eT > &error, arma::Mat< eT > &gradient)
OutputDataType const &	Gradient () const
	Get the gradient. More...
OutputDataType &	Gradient ()
	Modify the gradient. More...
InputDataType const &	InputParameter () const
	Get the input parameter. More...
InputDataType &	InputParameter ()
	Modify the input parameter. More...
size_t	InputSize () const
	Get the input size. 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...
void	Reset ()
template<typename Archive >
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer. More...

Detailed Description

template<typename InputDataType, typename OutputDataType, typename RegularizerType>
class mlpack::ann::Linear< InputDataType, OutputDataType, RegularizerType >

Implementation of the Linear layer class.

The Linear class represents a single layer of a neural network.

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 82 of file layer_types.hpp.

Constructor & Destructor Documentation

Linear

(

)

Create the Linear object.

Linear	(	const size_t	inSize,
		const size_t	outSize,
		RegularizerType	regularizer = RegularizerType()
	)

Create the Linear layer object using the specified number of units.

Parameters

inSize	The number of input units.
outSize	The number of output units.
regularizer	The regularizer to use, optional.

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.

arma::mat& Bias ( )

inline

Modify the bias weights of the layer.

Definition at line 128 of file linear.hpp.

OutputDataType const& Delta ( ) const

inline

Get the delta.

Definition at line 112 of file linear.hpp.

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 114 of file linear.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 > &	input,
		const arma::Mat< eT > &	error,
		arma::Mat< eT > &	gradient
	)

OutputDataType const& Gradient ( ) const

inline

Get the gradient.

Definition at line 123 of file linear.hpp.

OutputDataType& Gradient ( )

inline

Modify the gradient.

Definition at line 125 of file linear.hpp.

InputDataType const& InputParameter ( ) const

inline

Get the input parameter.

Definition at line 102 of file linear.hpp.

InputDataType& InputParameter ( )

inline

Modify the input parameter.

Definition at line 104 of file linear.hpp.

size_t InputSize ( ) const

inline

Get the input size.

Definition at line 117 of file linear.hpp.

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 107 of file linear.hpp.

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 109 of file linear.hpp.

size_t OutputSize ( ) const

inline

Get the output size.

Definition at line 120 of file linear.hpp.

OutputDataType const& Parameters ( ) const

inline

Get the parameters.

Definition at line 97 of file linear.hpp.

OutputDataType& Parameters ( )

inline

Modify the parameters.

Definition at line 99 of file linear.hpp.

void Reset

(

)

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

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

• src/mlpack/methods/ann/layer/layer_types.hpp
• src/mlpack/methods/ann/layer/linear.hpp