The reconstruction loss performance function measures the network's performance equal to the negative log probability of the target with the input distribution. More...

Public Member Functions
	ReconstructionLoss ()
	Create the ReconstructionLoss object. More...

template < typename InputType , typename TargetType , typename OutputType >
void	Backward (const InputType &&input, const TargetType &&target, OutputType &&output)
	Ordinary feed backward pass of a neural network. More...

template < typename InputType , typename TargetType >
double	Forward (const InputType &&input, const TargetType &&target)
	Computes the reconstruction loss. More...

OutputDataType &	OutputParameter () const
	Get the output parameter. More...

OutputDataType &	OutputParameter ()
	Modify the output parameter. More...

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

Detailed Description

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat, typename DistType = BernoulliDistribution<InputDataType>>
class mlpack::ann::ReconstructionLoss< InputDataType, OutputDataType, DistType >

The reconstruction loss performance function measures the network's performance equal to the negative log probability of the target with the input distribution.

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).
DistType	The type of distribution parametrized by the input.

Definition at line 37 of file reconstruction_loss.hpp.

Constructor & Destructor Documentation

◆ ReconstructionLoss()

ReconstructionLoss ( )

Create the ReconstructionLoss object.

Member Function Documentation

◆ Backward()

void Backward	(	const InputType &&	input,
		const TargetType &&	target,
		OutputType &&	output
	)

Ordinary feed backward pass of a neural network.

Parameters

input	The propagated input activation.
target	The target matrix.
output	The calculated error.

◆ Forward()

double Forward	(	const InputType &&	input,
		const TargetType &&	target
	)

Computes the reconstruction loss.

Parameters

input	Input data used for evaluating the specified function.
target	The target matrix.

◆ OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 67 of file reconstruction_loss.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 69 of file reconstruction_loss.hpp.

References ReconstructionLoss< InputDataType, OutputDataType, DistType >::serialize().

◆ serialize()

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

Referenced by ReconstructionLoss< InputDataType, OutputDataType, DistType >::OutputParameter().

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

/home/ryan/src/mlpack.org/_src/mlpack-3.1.1/src/mlpack/methods/ann/loss_functions/reconstruction_loss.hpp

Public Member Functions