13#ifndef MLPACK_METHODS_ANN_LAYER_REPARAMETRIZATION_HPP
14#define MLPACK_METHODS_ANN_LAYER_REPARAMETRIZATION_HPP
19#include "../activation_functions/softplus_function.hpp"
53 typename InputDataType = arma::mat,
54 typename OutputDataType = arma::mat
71 const bool stochastic =
true,
72 const bool includeKl =
true,
73 const double beta = 1);
83 void Forward(
const arma::Mat<eT>& input, arma::Mat<eT>& output);
96 const arma::Mat<eT>& gy,
105 OutputDataType
const&
Delta()
const {
return delta; }
107 OutputDataType&
Delta() {
return delta; }
120 return -0.5 * beta * arma::accu(2 * arma::log(stdDev) - arma::pow(stdDev, 2)
121 - arma::pow(mean, 2) + 1) / mean.n_cols;
131 double Beta()
const {
return beta; }
136 template<
typename Archive>
153 OutputDataType delta;
156 OutputDataType gaussianSample;
163 OutputDataType preStdDev;
166 OutputDataType stdDev;
169 OutputDataType outputParameter;
176#include "reparametrization_impl.hpp"
Implementation of the Reparametrization layer class.
OutputDataType const & Delta() const
Get the delta.
void Forward(const arma::Mat< eT > &input, arma::Mat< eT > &output)
Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activ...
Reparametrization(const size_t latentSize, const bool stochastic=true, const bool includeKl=true, const double beta=1)
Create the Reparametrization layer object using the specified sample vector size.
size_t & OutputSize()
Modify the output size.
OutputDataType const & OutputParameter() const
Get the output parameter.
void Backward(const arma::Mat< eT > &input, const arma::Mat< eT > &gy, arma::Mat< eT > &g)
Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backw...
Reparametrization()
Create the Reparametrization object.
size_t const & OutputSize() const
Get the output size.
double Loss()
Get the KL divergence with standard normal.
bool IncludeKL() const
Get the value of the includeKl parameter.
double Beta() const
Get the value of the beta hyperparameter.
OutputDataType & OutputParameter()
Modify the output parameter.
bool Stochastic() const
Get the value of the stochastic parameter.
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
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.