Concat< InputDataType, OutputDataType, CustomLayers > Class Template Reference

Implementation of the Concat class. More...

Public Member Functions
	Concat (const bool model=true, const bool same=true)
	Create the Concat object using the specified parameters. More...
	~Concat ()
	Destroy the layers held by the model. More...
template < typename LayerType >
void	Add (const LayerType &layer)
template<class LayerType , class... Args>
void	Add (Args... args)
void	Add (LayerTypes< CustomLayers... > layer)
template < typename eT >
void	Backward (const arma::Mat< eT > &&, arma::Mat< eT > &&gy, arma::Mat< eT > &&g)
	Ordinary feed backward pass of a neural network, using 3rd-order tensors as input, calculating the function f(x) by propagating x backwards through f. More...
arma::mat const &	Delta () const
	Get the delta.e. More...
arma::mat &	Delta ()
	Modify the delta. More...
template < typename eT >
void	Forward (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 (arma::Mat< eT > &&, arma::Mat< eT > &&error, arma::Mat< eT > &&)
arma::mat const &	Gradient () const
	Get the gradient. More...
arma::mat &	Gradient ()
	Modify the gradient. More...
arma::mat const &	InputParameter () const
arma::mat &	InputParameter ()
	Modify the input parameter. More...
std::vector< LayerTypes< CustomLayers... > > &	Model ()
	Return the model modules. More...
arma::mat const &	OutputParameter () const
	Get the output parameter. More...
arma::mat &	OutputParameter ()
	Modify the output parameter. More...
const arma::mat &	Parameters () const
	Return the initial point for the optimization. More...
arma::mat &	Parameters ()
	Modify the initial point for the optimization. More...
template < typename Archive >
void	serialize (Archive &, const unsigned int)
	Serialize the layer. More...

Detailed Description

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

Implementation of the Concat class.

The Concat class works as a feed-forward fully connected network container which plugs various layers together.

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 if required.

Definition at line 44 of file concat.hpp.

Constructor & Destructor Documentation

Concat()

Concat	(	const bool	model = true,
		const bool	same = true
	)

Create the Concat object using the specified parameters.

Parameters

model	Expose all network modules.
same	Merge the error in the backward pass.

~Concat()

~Concat

(

)

Destroy the layers held by the model.

Member Function Documentation

Add() [1/3]

void Add ( const LayerType &  layer )

inline

Definition at line 102 of file concat.hpp.

Add() [2/3]

void Add ( Args...  args )

inline

Definition at line 110 of file concat.hpp.

Add() [3/3]

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

inline

Definition at line 117 of file concat.hpp.

Backward()

void Backward	(	const arma::Mat< eT > &&	,
		arma::Mat< eT > &&	gy,
		arma::Mat< eT > &&	g
	)

Ordinary feed backward pass of a neural network, using 3rd-order tensors as input, 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]

arma::mat const& Delta ( ) const

inline

Get the delta.e.

Definition at line 145 of file concat.hpp.

Delta() [2/2]

arma::mat& Delta ( )

inline

Modify the delta.

Definition at line 147 of file concat.hpp.

Forward()

void Forward	(	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.

Gradient() [1/3]

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

Gradient() [2/3]

arma::mat const& Gradient ( ) const

inline

Get the gradient.

Definition at line 150 of file concat.hpp.

Gradient() [3/3]

arma::mat& Gradient ( )

inline

Modify the gradient.

Definition at line 152 of file concat.hpp.

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

InputParameter() [1/2]

arma::mat const& InputParameter ( ) const

inline

Definition at line 135 of file concat.hpp.

InputParameter() [2/2]

arma::mat& InputParameter ( )

inline

Modify the input parameter.

Definition at line 137 of file concat.hpp.

Model()

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

inline

Return the model modules.

Definition at line 120 of file concat.hpp.

OutputParameter() [1/2]

arma::mat const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 140 of file concat.hpp.

OutputParameter() [2/2]

arma::mat& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 142 of file concat.hpp.

Parameters() [1/2]

const arma::mat& Parameters ( ) const

inline

Return the initial point for the optimization.

Definition at line 131 of file concat.hpp.

Parameters() [2/2]

arma::mat& Parameters ( )

inline

Modify the initial point for the optimization.

Definition at line 133 of file concat.hpp.

serialize()

void serialize	(	Archive &	,
		const unsigned	int
	)

Serialize the layer.

Referenced by Concat< InputDataType, OutputDataType, CustomLayers >::Gradient().

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

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