14 #ifndef MLPACK_METHODS_ANN_LAYER_LEAKYRELU_HPP    15 #define MLPACK_METHODS_ANN_LAYER_LEAKYRELU_HPP    41     typename InputDataType = arma::mat,
    42     typename OutputDataType = arma::mat
    63   template<
typename InputType, 
typename OutputType>
    64   void Forward(
const InputType& input, OutputType& output);
    75   template<
typename DataType>
    76   void Backward(
const DataType& input, 
const DataType& gy, DataType& g);
    84   OutputDataType 
const& 
Delta()
 const { 
return delta; }
    86   OutputDataType& 
Delta() { 
return delta; }
    89   double const& 
Alpha()
 const { 
return alpha; }
    91   double& 
Alpha() { 
return alpha; }
    99   template<
typename Archive>
   100   void serialize(Archive& ar, 
const uint32_t );
   104   OutputDataType delta;
   107   OutputDataType outputParameter;
   117 #include "leaky_relu_impl.hpp" 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...
 
LeakyReLU(const double alpha=0.03)
Create the LeakyReLU object using the specified parameters. 
 
Linear algebra utility functions, generally performed on matrices or vectors. 
 
The core includes that mlpack expects; standard C++ includes and Armadillo. 
 
The LeakyReLU activation function, defined by. 
 
OutputDataType const  & Delta() const
Get the delta. 
 
double const  & Alpha() const
Get the non zero gradient. 
 
void serialize(Archive &ar, const uint32_t)
Serialize the layer. 
 
size_t WeightSize() const
Get size of weights. 
 
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 & Alpha()
Modify the non zero gradient. 
 
OutputDataType & OutputParameter()
Modify the output parameter. 
 
OutputDataType & Delta()
Modify the delta.