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 PredictionType , typename TargetType , typename LossType >
void	Backward (const PredictionType &prediction, const TargetType &target, LossType &loss)
	Ordinary feed backward pass of a neural network. More...

template < typename PredictionType , typename TargetType >
PredictionType::elem_type	Forward (const PredictionType &prediction, 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 uint32_t)
	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 PredictionType &	prediction,
		const TargetType &	target,
		LossType &	loss
	)

Ordinary feed backward pass of a neural network.

Parameters

prediction	Predictions used for evaluating the specified loss function.
target	The target matrix.
loss	The calculated error.

◆ Forward()

PredictionType::elem_type Forward	(	const PredictionType &	prediction,
		const TargetType &	target
	)

Computes the reconstruction loss.

Parameters

prediction	Predictions used for evaluating the specified loss function.
target	The target matrix.

◆ OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 70 of file reconstruction_loss.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 72 of file reconstruction_loss.hpp.

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

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

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-git/src/mlpack/methods/ann/loss_functions/reconstruction_loss.hpp

Public Member Functions