24 #ifndef MLPACK_METHODS_ANN_LAYER_ISRLU_HPP 25 #define MLPACK_METHODS_ANN_LAYER_ISRLU_HPP 57 typename InputDataType = arma::mat,
58 typename OutputDataType = arma::mat
69 ISRLU(
const double alpha = 1.0);
78 template<
typename InputType,
typename OutputType>
79 void Forward(
const InputType& input, OutputType& output);
90 template<
typename DataType>
91 void Backward(
const DataType& input,
const DataType& gy, DataType& g);
99 OutputDataType
const&
Delta()
const {
return delta; }
101 OutputDataType&
Delta() {
return delta; }
104 double const&
Alpha()
const {
return alpha; }
114 template<
typename Archive>
115 void serialize(Archive& ar,
const uint32_t );
119 OutputDataType delta;
122 OutputDataType outputParameter;
125 arma::mat derivative;
135 #include "isrlu_impl.hpp" void serialize(Archive &ar, const uint32_t)
Serialize the layer.
The ISRLU activation function, defined by.
Linear algebra utility functions, generally performed on matrices or vectors.
ISRLU(const double alpha=1.0)
Create the ISRLU object using the specified parameter.
OutputDataType & Delta()
Modify the delta.
The core includes that mlpack expects; standard C++ includes and Armadillo.
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...
double & Alpha()
Modify the non zero gradient.
size_t WeightSize()
Get size of weights.
OutputDataType & OutputParameter()
Modify the output parameter.
OutputDataType const & Delta() const
Get the delta.
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 & OutputParameter() const
Get the output parameter.
double const & Alpha() const
Get the non zero gradient.