PReLU< InputDataType, OutputDataType > Class Template Reference

The PReLU activation function, defined by (where alpha is trainable) More...

Public Member Functions
	PReLU (const double userAlpha=0.03)
	Create the PReLU object using the specified parameters. More...
double const &	Alpha () const
	Get the non zero gradient. More...
double &	Alpha ()
	Modify the non zero gradient. More...
template<typename DataType >
void	Backward (const DataType &input, const DataType &gy, DataType &g)
	Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards through f. More...
OutputDataType const &	Delta () const
	Get the delta. More...
OutputDataType &	Delta ()
	Modify the delta. 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	Gradient (const arma::Mat< eT > &input, const 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...
void	Reset ()
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::PReLU< InputDataType, OutputDataType >

The PReLU activation function, defined by (where alpha is trainable)

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 45 of file parametric_relu.hpp.

Constructor & Destructor Documentation

PReLU

(

const double

userAlpha = 0.03

)

Create the PReLU object using the specified parameters.

The non zero gradient can be adjusted by specifying tha parameter alpha in the range 0 to 1. Default (alpha = 0.03). This parameter is trainable.

Parameters

userAlpha

Non zero gradient

Member Function Documentation

double const& Alpha ( ) const

inline

Get the non zero gradient.

Definition at line 118 of file parametric_relu.hpp.

double& Alpha ( )

inline

Modify the non zero gradient.

Definition at line 120 of file parametric_relu.hpp.

void Backward	(	const DataType &	input,
		const DataType &	gy,
		DataType &	g
	)

Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards through 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 108 of file parametric_relu.hpp.

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 110 of file parametric_relu.hpp.

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.

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
	)

Calculate the gradient using the output delta and the input activation.

Parameters

input	The input parameter used for calculating the gradient.
error	The calculated error.
gradient	The calculated gradient.

OutputDataType const& Gradient ( ) const

inline

Get the gradient.

Definition at line 113 of file parametric_relu.hpp.

OutputDataType& Gradient ( )

inline

Modify the gradient.

Definition at line 115 of file parametric_relu.hpp.

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 103 of file parametric_relu.hpp.

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 105 of file parametric_relu.hpp.

OutputDataType const& Parameters ( ) const

inline

Get the parameters.

Definition at line 98 of file parametric_relu.hpp.

OutputDataType& Parameters ( )

inline

Modify the parameters.

Definition at line 100 of file parametric_relu.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 file:

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