ReconstructionLoss< InputDataType, OutputDataType, DistType > Class Template Reference

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
InputDataTypeType of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataTypeType of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
DistTypeThe type of distribution parametrized by the input.

Definition at line 37 of file reconstruction_loss.hpp.

Constructor & Destructor Documentation

◆ 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
inputThe propagated input activation.
targetThe target matrix.
outputThe calculated error.

◆ Forward()

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

Computes the reconstruction loss.

Parameters
inputInput data used for evaluating the specified function.
targetThe 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 
)

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