12 #ifndef MLPACK_METHODS_ANN_LOSS_FUNCTION_RECONSTRUCTION_LOSS_HPP 13 #define MLPACK_METHODS_ANN_LOSS_FUNCTION_RECONSTRUCTION_LOSS_HPP 33 typename InputDataType = arma::mat,
34 typename OutputDataType = arma::mat,
35 typename DistType = BernoulliDistribution<InputDataType>
51 template<
typename InputType,
typename TargetType>
52 double Forward(
const InputType&& input,
const TargetType&& target);
61 template<
typename InputType,
typename TargetType,
typename OutputType>
62 void Backward(
const InputType&& input,
63 const TargetType&& target,
74 template<
typename Archive>
75 void serialize(Archive& ar,
const unsigned int );
82 OutputDataType outputParameter;
89 #include "reconstruction_loss_impl.hpp"
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
double Forward(const InputType &&input, const TargetType &&target)
Computes the reconstruction loss.
ReconstructionLoss()
Create the ReconstructionLoss object.
The core includes that mlpack expects; standard C++ includes and Armadillo.
The reconstruction loss performance function measures the network's performance equal to the negative...
OutputDataType & OutputParameter()
Modify the output parameter.
OutputDataType & OutputParameter() const
Get the output parameter.
void Backward(const InputType &&input, const TargetType &&target, OutputType &&output)
Ordinary feed backward pass of a neural network.