Constant< InputDataType, OutputDataType > Class Template Reference

Implementation of the constant layer. More...

Public Member Functions
	Constant (const size_t outSize=0, const double scalar=0.0)
	Create the Constant object that outputs a given constant scalar value given any input value. More...
template < typename DataType >
void	Backward (const DataType &, const DataType &, DataType &g)
	Ordinary feed backward pass of a neural network. More...
OutputDataType &	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. More...
OutputDataType &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
size_t	OutSize () const
	Get the output size. 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

>

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

Implementation of the constant layer.

The constant layer outputs a given constant value given any input value.

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 34 of file constant.hpp.

Constructor & Destructor Documentation

Constant()

Constant	(	const size_t	outSize = 0,
		const double	scalar = 0.0
	)

Create the Constant object that outputs a given constant scalar value given any input value.

Parameters

outSize	The number of output units.
scalar	The constant value used to create the constant output.

Member Function Documentation

Backward()

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

Ordinary feed backward pass of a neural network.

The backward pass of the constant layer is returns always a zero output error matrix.

Parameters

*	(input) The propagated input activation.
*	(gy) The backpropagated error.
g	The calculated gradient.

Delta() [1/2]

OutputDataType& Delta ( ) const

inline

Get the delta.

Definition at line 75 of file constant.hpp.

Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 77 of file constant.hpp.

Forward()

void Forward	(	const InputType &	input,
		OutputType &	output
	)

Ordinary feed forward pass of a neural network.

The forward pass fills the output with the specified constant parameter.

Parameters

input	Input data used for evaluating the specified function.
output	Resulting output activation.

OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 70 of file constant.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 72 of file constant.hpp.

OutSize()

size_t OutSize ( ) const

inline

Get the output size.

Definition at line 80 of file constant.hpp.

serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

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

WeightSize()

size_t WeightSize ( ) const

inline

Get the size of the weights.

Definition at line 83 of file constant.hpp.

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

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

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