Implementation of the MultiplyMerge module class. More...

Public Member Functions
	MultiplyMerge (const bool model=false, const bool run=true)
	Create the MultiplyMerge object using the specified parameters. More...

	MultiplyMerge (const MultiplyMerge &layer)
	Copy Constructor. More...

	MultiplyMerge (MultiplyMerge &&layer)
	Move Constructor. More...

	~MultiplyMerge ()
	Destructor to release allocated memory. More...

template<class LayerType , class... Args>
void	Add (Args... args)

void	Add (LayerTypes< CustomLayers... > layer)

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, using the results from the feed forward pass. More...

OutputDataType const &	Delta () const
	Get the delta. More...

OutputDataType &	Delta ()
	Modify the delta. More...

template < typename InputType , typename OutputType >
void	Forward (const InputType &, 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)

OutputDataType const &	Gradient () const
	Get the gradient. More...

OutputDataType &	Gradient ()
	Modify the gradient. More...

std::vector< LayerTypes< CustomLayers... > > &	Model ()
	Return the model modules. More...

MultiplyMerge &	operator= (const MultiplyMerge &layer)
	Copy assignment operator. More...

MultiplyMerge &	operator= (MultiplyMerge &&layer)
	Move assignment operator. 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...

template < typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the layer. More...

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

Detailed Description

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat, typename... CustomLayers>
class mlpack::ann::MultiplyMerge< InputDataType, OutputDataType, CustomLayers >

Implementation of the MultiplyMerge module class.

The MultiplyMerge class multiplies the output of various modules element-wise.

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).
CustomLayers	Additional custom layers that can be added.

Definition at line 211 of file layer_types.hpp.

Constructor & Destructor Documentation

◆ MultiplyMerge() [1/3]

MultiplyMerge	(	const bool	model = `false`,
		const bool	run = `true`
	)

Create the MultiplyMerge object using the specified parameters.

Parameters

model	Expose all the network modules.
run	Call the Forward/Backward method before the output is merged.

◆ MultiplyMerge() [2/3]

MultiplyMerge ( const MultiplyMerge< InputDataType, OutputDataType, CustomLayers > & layer )

Copy Constructor.

◆ MultiplyMerge() [3/3]

MultiplyMerge ( MultiplyMerge< InputDataType, OutputDataType, CustomLayers > && layer )

Move Constructor.

◆ ~MultiplyMerge()

~MultiplyMerge ( )

Destructor to release allocated memory.

Member Function Documentation

◆ Add() [1/2]

void Add ( Args... args )

inline

Definition at line 110 of file multiply_merge.hpp.

◆ Add() [2/2]

void Add ( LayerTypes< CustomLayers... > layer )

inline

Definition at line 117 of file multiply_merge.hpp.

◆ 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 const& Delta ( ) const

inline

Get the delta.

Definition at line 125 of file multiply_merge.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 127 of file multiply_merge.hpp.

◆ Forward()

void Forward	(	const InputType &	,
		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.

◆ Gradient() [1/3]

void Gradient	(	const arma::Mat< eT > &	input,
		const arma::Mat< eT > &	error,
		arma::Mat< eT > &	gradient
	)

◆ Gradient() [2/3]

OutputDataType const& Gradient ( ) const

inline

Get the gradient.

Definition at line 130 of file multiply_merge.hpp.

◆ Gradient() [3/3]

OutputDataType& Gradient ( )

inline

Modify the gradient.

Definition at line 132 of file multiply_merge.hpp.

◆ Model()

std::vector<LayerTypes<CustomLayers...> >& Model ( )

inline

Return the model modules.

Definition at line 135 of file multiply_merge.hpp.

◆ operator=() [1/2]

MultiplyMerge& operator= ( const MultiplyMerge< InputDataType, OutputDataType, CustomLayers > & layer )

Copy assignment operator.

◆ operator=() [2/2]

MultiplyMerge& operator= ( MultiplyMerge< InputDataType, OutputDataType, CustomLayers > && layer )

Move assignment operator.

◆ OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 120 of file multiply_merge.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 122 of file multiply_merge.hpp.

◆ Parameters() [1/2]

OutputDataType const& Parameters ( ) const

inline

Get the parameters.

Definition at line 146 of file multiply_merge.hpp.

◆ Parameters() [2/2]

OutputDataType& Parameters ( )

inline

Modify the parameters.

Definition at line 148 of file multiply_merge.hpp.

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

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

◆ WeightSize()

size_t WeightSize ( ) const

inline

Get the size of the weights.

Definition at line 151 of file multiply_merge.hpp.

References MultiplyMerge< InputDataType, OutputDataType, CustomLayers >::serialize().

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

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

Public Member Functions

Detailed Description

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat, typename... CustomLayers> class mlpack::ann::MultiplyMerge< InputDataType, OutputDataType, CustomLayers >

Constructor & Destructor Documentation

◆ MultiplyMerge() [1/3]

◆ MultiplyMerge() [2/3]

◆ MultiplyMerge() [3/3]

◆ ~MultiplyMerge()

Member Function Documentation

◆ Add() [1/2]

◆ Add() [2/2]

◆ Backward()

◆ Delta() [1/2]

◆ Delta() [2/2]

◆ Forward()

◆ Gradient() [1/3]

◆ Gradient() [2/3]

◆ Gradient() [3/3]

◆ Model()

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ OutputParameter() [1/2]

◆ OutputParameter() [2/2]

◆ Parameters() [1/2]

◆ Parameters() [2/2]

◆ serialize()

◆ WeightSize()

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat, typename... CustomLayers>
class mlpack::ann::MultiplyMerge< InputDataType, OutputDataType, CustomLayers >