13#ifndef MLPACK_METHODS_ANN_LAYER_MULTIPLY_CONSTANT_HPP
14#define MLPACK_METHODS_ANN_LAYER_MULTIPLY_CONSTANT_HPP
31 typename InputDataType = arma::mat,
32 typename OutputDataType = arma::mat
49 template<
typename InputType,
typename OutputType>
50 void Forward(
const InputType& input, OutputType& output);
60 template<
typename DataType>
61 void Backward(
const DataType& ,
const DataType& gy, DataType& g);
69 OutputDataType&
Delta()
const {
return delta; }
71 OutputDataType&
Delta() {
return delta; }
74 double Scalar()
const {
return scalar; }
81 template<
typename Archive>
92 OutputDataType outputParameter;
99#include "multiply_constant_impl.hpp"
Implementation of the multiply constant layer.
void Forward(const InputType &input, OutputType &output)
Ordinary feed forward pass of a neural network.
OutputDataType & OutputParameter() const
Get the output parameter.
void Backward(const DataType &, const DataType &gy, DataType &g)
Ordinary feed backward pass of a neural network.
OutputDataType & Delta() const
Get the delta.
double Scalar() const
Get the scalar multiplier.
MultiplyConstant(const double scalar=1.0)
Create the MultiplyConstant object.
double & Scalar()
Modify the scalar multiplier.
OutputDataType & OutputParameter()
Modify the output parameter.
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
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.