16#ifndef MLPACK_METHODS_ANN_LAYER_FLEXIBLERELU_HPP
17#define MLPACK_METHODS_ANN_LAYER_FLEXIBLERELU_HPP
56 typename InputDataType = arma::mat,
57 typename OutputDataType = arma::mat
86 template<
typename InputType,
typename OutputType>
87 void Forward(
const InputType& input, OutputType& output);
98 template<
typename DataType>
99 void Backward(
const DataType& input,
const DataType& gy, DataType& g);
108 template<
typename eT>
110 const arma::Mat<eT>& error,
111 arma::Mat<eT>& gradient);
124 OutputDataType
const&
Delta()
const {
return delta; }
126 OutputDataType&
Delta() {
return delta;}
129 OutputDataType
const&
Gradient()
const {
return gradient; }
134 double const&
Alpha()
const {
return alpha; }
141 template<
typename Archive>
146 OutputDataType delta;
149 OutputDataType outputParameter;
152 OutputDataType alpha;
155 OutputDataType gradient;
165#include "flexible_relu_impl.hpp"
The FlexibleReLU activation function, defined by.
void Forward(const InputType &input, OutputType &output)
Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activ...
OutputDataType const & Delta() const
Get the delta.
OutputDataType const & Parameters() const
Get the parameters.
void Reset()
Reset the layer parameter.
double & Alpha()
Modify the parameter controlling the range of the relu function.
OutputDataType const & OutputParameter() const
Get the output parameter.
FlexibleReLU(const double alpha=0)
Create the FlexibleReLU object using the specified parameters.
void Gradient(const arma::Mat< eT > &input, const arma::Mat< eT > &error, arma::Mat< eT > &gradient)
Calculate the gradient using the output delta and the input activation.
OutputDataType const & Gradient() const
Get the gradient.
OutputDataType & Gradient()
Modify the gradient.
OutputDataType & OutputParameter()
Modify the output parameter.
double const & Alpha() const
Get the parameter controlling the range of the relu function.
void Backward(const DataType &input, const DataType &gy, DataType &g)
Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backw...
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
OutputDataType & Parameters()
Modify the parameters.
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.