12 #ifndef MLPACK_METHODS_ANN_LAYER_LOG_SOFTMAX_HPP 13 #define MLPACK_METHODS_ANN_LAYER_LOG_SOFTMAX_HPP 33 typename InputDataType = arma::mat,
34 typename OutputDataType = arma::mat
51 template<
typename InputType,
typename OutputType>
52 void Forward(
const InputType& input, OutputType& output);
64 void Backward(
const arma::Mat<eT>& input,
65 const arma::Mat<eT>& gy,
74 InputDataType&
Delta()
const {
return delta; }
76 InputDataType&
Delta() {
return delta; }
81 template<
typename Archive>
82 void serialize(Archive& ,
const uint32_t );
89 OutputDataType outputParameter;
96 #include "log_softmax_impl.hpp" void Forward(const InputType &input, OutputType &output)
Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activ...
Implementation of the log softmax layer.
Linear algebra utility functions, generally performed on matrices or vectors.
The core includes that mlpack expects; standard C++ includes and Armadillo.
InputDataType & Delta()
Modify the delta.
void serialize(Archive &, const uint32_t)
Serialize the layer.
OutputDataType & OutputParameter()
Modify 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...
InputDataType & Delta() const
Get the delta.
LogSoftMax()
Create the LogSoftmax object.
OutputDataType & OutputParameter() const
Get the output parameter.