add.hpp
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1 
12 #ifndef MLPACK_METHODS_ANN_LAYER_ADD_HPP
13 #define MLPACK_METHODS_ANN_LAYER_ADD_HPP
14 
15 #include <mlpack/prereqs.hpp>
17 
18 namespace mlpack {
19 namespace ann {
20 
30 template <
31  typename InputDataType = arma::mat,
32  typename OutputDataType = arma::mat
33 >
34 class Add
35 {
36  public:
42  Add(const size_t outSize = 0);
43 
51  template<typename eT>
52  void Forward(const arma::Mat<eT>&& input, arma::Mat<eT>&& output);
53 
63  template<typename eT>
64  void Backward(const arma::Mat<eT>&& /* input */,
65  const arma::Mat<eT>&& gy,
66  arma::Mat<eT>&& g);
67 
75  template<typename eT>
76  void Gradient(const arma::Mat<eT>&& /* input */,
77  arma::Mat<eT>&& error,
78  arma::Mat<eT>&& gradient);
79 
81  OutputDataType const& Parameters() const { return weights; }
83  OutputDataType& Parameters() { return weights; }
84 
86  OutputDataType const& OutputParameter() const { return outputParameter; }
88  OutputDataType& OutputParameter() { return outputParameter; }
89 
91  OutputDataType const& Delta() const { return delta; }
93  OutputDataType& Delta() { return delta; }
94 
96  OutputDataType const& Gradient() const { return gradient; }
98  OutputDataType& Gradient() { return gradient; }
99 
103  template<typename Archive>
104  void serialize(Archive& ar, const unsigned int /* version */);
105 
106  private:
108  size_t outSize;
109 
111  OutputDataType weights;
112 
114  OutputDataType delta;
115 
117  OutputDataType gradient;
118 
120  OutputDataType outputParameter;
121 }; // class Add
122 
123 } // namespace ann
124 } // namespace mlpack
125 
126 // Include implementation.
127 #include "add_impl.hpp"
128 
129 #endif
OutputDataType & Delta()
Modify the delta.
Definition: add.hpp:93
void Forward(const arma::Mat< eT > &&input, arma::Mat< eT > &&output)
Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activ...
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
Implementation of the Add module class.
Definition: add.hpp:34
.hpp
Definition: add_to_po.hpp:21
OutputDataType & Gradient()
Modify the gradient.
Definition: add.hpp:98
The core includes that mlpack expects; standard C++ includes and Armadillo.
OutputDataType const & Parameters() const
Get the parameters.
Definition: add.hpp:81
OutputDataType & Parameters()
Modify the parameters.
Definition: add.hpp:83
OutputDataType const & Delta() const
Get the delta.
Definition: add.hpp:91
OutputDataType const & OutputParameter() const
Get the output parameter.
Definition: add.hpp:86
void Backward(const arma::Mat< eT > &&, const arma::Mat< eT > &&gy, arma::Mat< eT > &&g)
Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backw...
Add(const size_t outSize=0)
Create the Add object using the specified number of output units.
OutputDataType & OutputParameter()
Modify the output parameter.
Definition: add.hpp:88
OutputDataType const & Gradient() const
Get the gradient.
Definition: add.hpp:96