MultiplyMerge< InputDataType, OutputDataType, CustomLayers > Class Template Reference

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 ()
	Destructor to release allocated memory. More...
template
void	Add (Args... args)
void	Add (LayerTypes< CustomLayers... > layer)
template
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
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
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...
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
void	serialize (Archive &ar, const unsigned int)
	Serialize the layer. More...

Detailed Description

template
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 202 of file layer_types.hpp.

Constructor & Destructor Documentation

MultiplyMerge()

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()

~MultiplyMerge

(

)

Destructor to release allocated memory.

Member Function Documentation

Add() [1/2]

void Add ( Args...  args )

inline

Definition at line 98 of file multiply_merge.hpp.

Add() [2/2]

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

inline

Definition at line 105 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 113 of file multiply_merge.hpp.

Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 115 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 118 of file multiply_merge.hpp.

Gradient() [3/3]

OutputDataType& Gradient ( )

inline

Modify the gradient.

Definition at line 120 of file multiply_merge.hpp.

Model()

std::vector<LayerTypes >& Model ( )

inline

Return the model modules.

Definition at line 123 of file multiply_merge.hpp.

OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 108 of file multiply_merge.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 110 of file multiply_merge.hpp.

Parameters() [1/2]

OutputDataType const& Parameters ( ) const

inline

Get the parameters.

Definition at line 134 of file multiply_merge.hpp.

Parameters() [2/2]

OutputDataType& Parameters ( )

inline

Modify the parameters.

Definition at line 136 of file multiply_merge.hpp.

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

serialize()

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

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

---

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

• /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.4.2/src/mlpack/methods/ann/layer/layer_types.hpp
• /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.4.2/src/mlpack/methods/ann/layer/multiply_merge.hpp