12 #ifndef MLPACK_METHODS_ANN_LAYER_NEGATIVE_LOG_LIKELIHOOD_HPP    13 #define MLPACK_METHODS_ANN_LAYER_NEGATIVE_LOG_LIKELIHOOD_HPP    32     typename InputDataType = arma::mat,
    33     typename OutputDataType = arma::mat
    51   template<
typename PredictionType, 
typename TargetType>
    52   typename PredictionType::elem_type 
Forward(
const PredictionType& prediction,
    53                                              const TargetType& target);
    67   template<
typename PredictionType, 
typename TargetType, 
typename LossType>
    68   void Backward(
const PredictionType& prediction,
    69                 const TargetType& target,
    83   OutputDataType& 
Delta()
 const { 
return delta; }
    85   OutputDataType& 
Delta() { 
return delta; }
    90   template<
typename Archive>
    91   void serialize(Archive& , 
const uint32_t );
    98   InputDataType inputParameter;
   101   OutputDataType outputParameter;
   108 #include "negative_log_likelihood_impl.hpp" OutputDataType & OutputParameter() const
Get the output parameter. 
 
OutputDataType & Delta()
Modify the delta. 
 
Linear algebra utility functions, generally performed on matrices or vectors. 
 
The core includes that mlpack expects; standard C++ includes and Armadillo. 
 
Implementation of the negative log likelihood layer. 
 
NegativeLogLikelihood()
Create the NegativeLogLikelihoodLayer object. 
 
void Backward(const PredictionType &prediction, const TargetType &target, LossType &loss)
Ordinary feed backward pass of a neural network. 
 
InputDataType & InputParameter() const
Get the input parameter. 
 
PredictionType::elem_type Forward(const PredictionType &prediction, const TargetType &target)
Computes the Negative log likelihood. 
 
OutputDataType & OutputParameter()
Modify the output parameter. 
 
void serialize(Archive &, const uint32_t)
Serialize the layer. 
 
InputDataType & InputParameter()
Modify the input parameter. 
 
OutputDataType & Delta() const
Get the delta.