NegativeLogLikelihood< InputDataType, OutputDataType > Class Template Reference

Implementation of the negative log likelihood layer. More...

Public Member Functions

 NegativeLogLikelihood ()
 Create the NegativeLogLikelihoodLayer 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...

 
OutputDataType & Delta () const
 Get the delta. More...

 
OutputDataType & Delta ()
 Modify the delta. More...

 
template
<
typename
InputType
,
typename
TargetType
>
double Forward (const InputType &&input, TargetType &&target)
 Computes the Negative log likelihood. More...

 
InputDataType & InputParameter () const
 Get the input parameter. More...

 
InputDataType & InputParameter ()
 Modify the input parameter. More...

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

 
OutputDataType & OutputParameter ()
 Modify the output parameter. 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
>

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

Implementation of the negative log likelihood layer.

The negative log likelihood layer expectes that the input contains log-probabilities for each class. The layer also expects a class index, in the range between 1 and the number of classes, as target when calling the Forward function.

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).

Definition at line 35 of file negative_log_likelihood.hpp.

Constructor & Destructor Documentation

◆ NegativeLogLikelihood()

Create the NegativeLogLikelihoodLayer object.

Member Function Documentation

◆ Backward()

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

Ordinary feed backward pass of a neural network.

The negative log likelihood layer expects that the input contains log-probabilities for each class. The layer also expects a class index, in the range between 1 and the number of classes, as target when calling the Forward function.

Parameters
inputThe propagated input activation.
targetThe target vector, that contains the class index in the range between 1 and the number of classes.
outputThe calculated error.

◆ Delta() [1/2]

OutputDataType& Delta ( ) const
inline

Get the delta.

Definition at line 80 of file negative_log_likelihood.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )
inline

◆ Forward()

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

Computes the Negative log likelihood.

Parameters
inputInput data used for evaluating the specified function.
targetThe target vector, that contains the class index in the range between 1 and the number of classes.

◆ InputParameter() [1/2]

InputDataType& InputParameter ( ) const
inline

Get the input parameter.

Definition at line 70 of file negative_log_likelihood.hpp.

◆ InputParameter() [2/2]

InputDataType& InputParameter ( )
inline

Modify the input parameter.

Definition at line 72 of file negative_log_likelihood.hpp.

◆ OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 75 of file negative_log_likelihood.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 77 of file negative_log_likelihood.hpp.

◆ serialize()

void serialize ( Archive &  ,
const unsigned  int 
)

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