10 #ifndef MLPACK_METHODS_ANN_LAYER_BILINEAR_INTERPOLATION_HPP 11 #define MLPACK_METHODS_ANN_LAYER_BILINEAR_INTERPOLATION_HPP 35 typename InputDataType = arma::mat,
36 typename OutputDataType = arma::mat
54 const size_t inColSize,
55 const size_t outRowSize,
56 const size_t outColSize,
67 void Forward(
const arma::Mat<eT>&& input, arma::Mat<eT>&& output);
81 void Backward(
const arma::Mat<eT>&& ,
82 arma::Mat<eT>&& gradient,
83 arma::Mat<eT>&& output);
96 OutputDataType
const&
Delta()
const {
return delta; }
98 OutputDataType&
Delta() {
return delta; }
103 template<
typename Archive>
104 void serialize(Archive& ar,
const unsigned int );
118 OutputDataType delta;
120 InputDataType inputParameter;
122 OutputDataType outputParameter;
129 #include "bilinear_interpolation_impl.hpp" OutputDataType const & OutputParameter() const
Get the output parameter.
InputDataType const & InputParameter() const
Get the input parameter.
OutputDataType & Delta()
Modify the delta.
void Forward(const arma::Mat< eT > &&input, arma::Mat< eT > &&output)
Forward pass through the layer.
The core includes that mlpack expects; standard C++ includes and Armadillo.
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
OutputDataType & OutputParameter()
Modify the output parameter.
InputDataType & InputParameter()
Modify the input parameter.
OutputDataType const & Delta() const
Get the delta.
BilinearInterpolation()
Create the Bilinear Interpolation object.
Definition and Implementation of the Bilinear Interpolation Layer.
void Backward(const arma::Mat< eT > &&, arma::Mat< eT > &&gradient, arma::Mat< eT > &&output)
Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backw...