14 #ifndef MLPACK_METHODS_ANN_LAYER_SOFTMAX_HPP    15 #define MLPACK_METHODS_ANN_LAYER_SOFTMAX_HPP    35     typename InputDataType = arma::mat,
    36     typename OutputDataType = arma::mat
    53   template<
typename InputType, 
typename OutputType>
    54   void Forward(
const InputType& input, OutputType& output);
    66   void Backward(
const arma::Mat<eT>& input,
    67                 const arma::Mat<eT>& gy,
    79   InputDataType& 
Delta()
 const { 
return delta; }
    81   InputDataType& 
Delta() { 
return delta; }
    86   template<
typename Archive>
    87   void serialize(Archive& , 
const uint32_t );
    94   OutputDataType outputParameter;
   101 #include "softmax_impl.hpp" Linear algebra utility functions, generally performed on matrices or vectors. 
 
size_t WeightSize() const
Get the size of the weights. 
 
OutputDataType & OutputParameter()
Modify the output parameter. 
 
void Forward(const InputType &input, OutputType &output)
Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activ...
 
The core includes that mlpack expects; standard C++ includes and Armadillo. 
 
InputDataType & Delta() const
Get the delta. 
 
Implementation of the Softmax layer. 
 
Softmax()
Create the Softmax object. 
 
InputDataType & Delta()
Modify the delta. 
 
void serialize(Archive &, const uint32_t)
Serialize the layer. 
 
OutputDataType & 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...