The Flatten T Swish activation function, defined by. More...

Public Member Functions
	FlattenTSwish (const double T=-0.20)
	Create the Flatten T Swish object using the specified parameters. 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...

OutputDataType const &	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...

double const &	T () const
	Get the T parameter. More...

double &	T ()
	Modify the T parameter. More...

size_t	WeightSize () const
	Get size of weights. More...

Detailed Description

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

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

The Flatten T Swish activation function, defined by.

$\begin{eqnarray*} f'(x) &=& \left\{ \begin{array}{lr} frac{x}{1+exp(-x)} + T & : x \ge 0 \\ T & : x < 0 \end{array} \right. \\ f'(x) &=& \left\{ \begin{array}{lr} \sigma(x)(1 - f(x)) + f(x) & : x > 0 \\ 0 & : x \le 0 \end{array} \right. \end{eqnarray*}$

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 49 of file flatten_t_swish.hpp.

Constructor & Destructor Documentation

◆ FlattenTSwish()

FlattenTSwish ( const double T = -0.20 )

Create the Flatten T Swish object using the specified parameters.

The thresholded value T can be adjusted via T paramaters. When the x is < 0, T will be used instead of 0. The default value of T is -0.20 as suggested in the paper.

Parameters

T

Member Function Documentation

◆ Backward()

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.

◆ Delta() [1/2]

OutputDataType const& Delta ( ) const

inline

Get the delta.

Definition at line 89 of file flatten_t_swish.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 91 of file flatten_t_swish.hpp.

◆ Forward()

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.

◆ OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 84 of file flatten_t_swish.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 86 of file flatten_t_swish.hpp.

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

Referenced by FlattenTSwish< InputDataType, OutputDataType >::WeightSize().

◆ T() [1/2]

double const& T ( ) const

inline

Get the T parameter.

Definition at line 94 of file flatten_t_swish.hpp.

◆ T() [2/2]

double& T ( )

inline

Modify the T parameter.

Definition at line 96 of file flatten_t_swish.hpp.

◆ WeightSize()

size_t WeightSize ( ) const

inline

Get size of weights.

Definition at line 99 of file flatten_t_swish.hpp.

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

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

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

Public Member Functions

Detailed Description

template<typenameInputDataType=arma::mat,typenameOutputDataType=arma::mat> class mlpack::ann::FlattenTSwish< InputDataType, OutputDataType >

Constructor & Destructor Documentation

◆ FlattenTSwish()

Member Function Documentation

◆ Backward()

◆ Delta() [1/2]

◆ Delta() [2/2]

◆ Forward()

◆ OutputParameter() [1/2]

◆ OutputParameter() [2/2]

◆ serialize()

◆ T() [1/2]

◆ T() [2/2]

◆ WeightSize()

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

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