add_merge.hpp
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1 
13 #ifndef MLPACK_METHODS_ANN_LAYER_ADD_MERGE_HPP
14 #define MLPACK_METHODS_ANN_LAYER_ADD_MERGE_HPP
15 
16 #include <mlpack/prereqs.hpp>
17 
18 #include "../visitor/delete_visitor.hpp"
19 #include "../visitor/delta_visitor.hpp"
20 #include "../visitor/output_parameter_visitor.hpp"
21 
22 #include "layer_types.hpp"
23 
24 namespace mlpack {
25 namespace ann {
26 
37 template<
38  typename InputDataType = arma::mat,
39  typename OutputDataType = arma::mat,
40  typename... CustomLayers
41 >
42 class AddMerge
43 {
44  public:
51  AddMerge(const bool model = false, const bool run = true);
52 
60  AddMerge(const bool model, const bool run, const bool ownsLayers);
61 
63  ~AddMerge();
64 
72  template<typename InputType, typename OutputType>
73  void Forward(const InputType& /* input */, OutputType& output);
74 
84  template<typename eT>
85  void Backward(const arma::Mat<eT>& /* input */,
86  const arma::Mat<eT>& gy,
87  arma::Mat<eT>& g);
88 
98  template<typename eT>
99  void Backward(const arma::Mat<eT>& /* input */,
100  const arma::Mat<eT>& gy,
101  arma::Mat<eT>& g,
102  const size_t index);
103 
104  /*
105  * Calculate the gradient using the output delta and the input activation.
106  *
107  * @param input The input parameter used for calculating the gradient.
108  * @param error The calculated error.
109  * @param gradient The calculated gradient.
110  */
111  template<typename eT>
112  void Gradient(const arma::Mat<eT>& input,
113  const arma::Mat<eT>& error,
114  arma::Mat<eT>& gradient);
115 
116  /*
117  * This is the overload of Gradient() that runs a specific layer with the
118  * given input.
119  *
120  * @param input The input parameter used for calculating the gradient.
121  * @param error The calculated error.
122  * @param gradient The calculated gradient.
123  * @param The index of the layer to run.
124  */
125  template<typename eT>
126  void Gradient(const arma::Mat<eT>& input,
127  const arma::Mat<eT>& error,
128  arma::Mat<eT>& gradient,
129  const size_t index);
130 
131  /*
132  * Add a new module to the model.
133  *
134  * @param args The layer parameter.
135  */
136  template <class LayerType, class... Args>
137  void Add(Args... args) { network.push_back(new LayerType(args...)); }
138 
139  /*
140  * Add a new module to the model.
141  *
142  * @param layer The Layer to be added to the model.
143  */
144  void Add(LayerTypes<CustomLayers...> layer) { network.push_back(layer); }
145 
147  InputDataType const& InputParameter() const { return inputParameter; }
149  InputDataType& InputParameter() { return inputParameter; }
150 
152  OutputDataType const& OutputParameter() const { return outputParameter; }
154  OutputDataType& OutputParameter() { return outputParameter; }
155 
157  OutputDataType const& Delta() const { return delta; }
159  OutputDataType& Delta() { return delta; }
160 
162  std::vector<LayerTypes<CustomLayers...> >& Model()
163  {
164  if (model)
165  {
166  return network;
167  }
168 
169  return empty;
170  }
171 
173  OutputDataType const& Parameters() const { return weights; }
175  OutputDataType& Parameters() { return weights; }
176 
178  bool Run() const { return run; }
180  bool& Run() { return run; }
181 
185  template<typename Archive>
186  void serialize(Archive& ar, const uint32_t /* version */);
187 
188  private:
190  bool model;
191 
194  bool run;
195 
198  bool ownsLayers;
199 
201  std::vector<LayerTypes<CustomLayers...> > network;
202 
204  std::vector<LayerTypes<CustomLayers...> > empty;
205 
207  DeleteVisitor deleteVisitor;
208 
210  OutputParameterVisitor outputParameterVisitor;
211 
213  DeltaVisitor deltaVisitor;
214 
216  OutputDataType delta;
217 
219  OutputDataType gradient;
220 
222  InputDataType inputParameter;
223 
225  OutputDataType outputParameter;
226 
228  OutputDataType weights;
229 }; // class AddMerge
230 
231 } // namespace ann
232 } // namespace mlpack
233 
234 // Include implementation.
235 #include "add_merge_impl.hpp"
236 
237 #endif
DeleteVisitor executes the destructor of the instantiated object.
InputDataType const & InputParameter() const
Get the input parameter.
Definition: add_merge.hpp:147
void Gradient(const arma::Mat< eT > &input, const arma::Mat< eT > &error, arma::Mat< eT > &gradient)
bool & Run()
Modify the value of run parameter.
Definition: add_merge.hpp:180
Implementation of the AddMerge module class.
Definition: add_merge.hpp:42
Linear algebra utility functions, generally performed on matrices or vectors.
The core includes that mlpack expects; standard C++ includes and Armadillo.
boost::variant< AdaptiveMaxPooling< arma::mat, arma::mat > *, AdaptiveMeanPooling< arma::mat, arma::mat > *, Add< arma::mat, arma::mat > *, AddMerge< arma::mat, arma::mat > *, AlphaDropout< arma::mat, arma::mat > *, AtrousConvolution< NaiveConvolution< ValidConvolution >, NaiveConvolution< FullConvolution >, NaiveConvolution< ValidConvolution >, arma::mat, arma::mat > *, BaseLayer< LogisticFunction, arma::mat, arma::mat > *, BaseLayer< IdentityFunction, arma::mat, arma::mat > *, BaseLayer< TanhFunction, arma::mat, arma::mat > *, BaseLayer< SoftplusFunction, arma::mat, arma::mat > *, BaseLayer< RectifierFunction, arma::mat, arma::mat > *, BatchNorm< arma::mat, arma::mat > *, BilinearInterpolation< arma::mat, arma::mat > *, CELU< arma::mat, arma::mat > *, Concat< arma::mat, arma::mat > *, Concatenate< arma::mat, arma::mat > *, ConcatPerformance< NegativeLogLikelihood< arma::mat, arma::mat >, arma::mat, arma::mat > *, Constant< arma::mat, arma::mat > *, Convolution< NaiveConvolution< ValidConvolution >, NaiveConvolution< FullConvolution >, NaiveConvolution< ValidConvolution >, arma::mat, arma::mat > *, CReLU< arma::mat, arma::mat > *, DropConnect< arma::mat, arma::mat > *, Dropout< arma::mat, arma::mat > *, ELU< arma::mat, arma::mat > *, FastLSTM< arma::mat, arma::mat > *, FlexibleReLU< arma::mat, arma::mat > *, GRU< arma::mat, arma::mat > *, HardTanH< arma::mat, arma::mat > *, Join< arma::mat, arma::mat > *, LayerNorm< arma::mat, arma::mat > *, LeakyReLU< arma::mat, arma::mat > *, Linear< arma::mat, arma::mat, NoRegularizer > *, LinearNoBias< arma::mat, arma::mat, NoRegularizer > *, LogSoftMax< arma::mat, arma::mat > *, Lookup< arma::mat, arma::mat > *, LSTM< arma::mat, arma::mat > *, MaxPooling< arma::mat, arma::mat > *, MeanPooling< arma::mat, arma::mat > *, MiniBatchDiscrimination< arma::mat, arma::mat > *, MultiplyConstant< arma::mat, arma::mat > *, MultiplyMerge< arma::mat, arma::mat > *, NegativeLogLikelihood< arma::mat, arma::mat > *, NoisyLinear< arma::mat, arma::mat > *, Padding< arma::mat, arma::mat > *, PReLU< arma::mat, arma::mat > *, Softmax< arma::mat, arma::mat > *, SpatialDropout< arma::mat, arma::mat > *, TransposedConvolution< NaiveConvolution< ValidConvolution >, NaiveConvolution< ValidConvolution >, NaiveConvolution< ValidConvolution >, arma::mat, arma::mat > *, WeightNorm< arma::mat, arma::mat > *, MoreTypes, CustomLayers *... > LayerTypes
OutputDataType const & Delta() const
Get the delta.
Definition: add_merge.hpp:157
void Forward(const InputType &, OutputType &output)
Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activ...
OutputDataType & Parameters()
Modify the parameters.
Definition: add_merge.hpp:175
void Add(Args... args)
Definition: add_merge.hpp:137
void serialize(Archive &ar, const uint32_t)
Serialize the layer.
OutputDataType & OutputParameter()
Modify the output parameter.
Definition: add_merge.hpp:154
OutputDataType & Delta()
Modify the delta.
Definition: add_merge.hpp:159
OutputParameterVisitor exposes the output parameter of the given module.
AddMerge(const bool model=false, const bool run=true)
Create the AddMerge object using the specified parameters.
InputDataType & InputParameter()
Modify the input parameter.
Definition: add_merge.hpp:149
DeltaVisitor exposes the delta parameter of the given module.
~AddMerge()
Destructor to release allocated memory.
std::vector< LayerTypes< CustomLayers... > > & Model()
Return the model modules.
Definition: add_merge.hpp:162
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...
OutputDataType const & OutputParameter() const
Get the output parameter.
Definition: add_merge.hpp:152
OutputDataType const & Parameters() const
Get the parameters.
Definition: add_merge.hpp:173
void Add(LayerTypes< CustomLayers... > layer)
Definition: add_merge.hpp:144
bool Run() const
Get the value of run parameter.
Definition: add_merge.hpp:178