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NeuralConvolutionalLayer.h
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33 
34 #ifndef __NEURALCONVOLUTIONALLAYER_H__
35 #define __NEURALCONVOLUTIONALLAYER_H__
36 
37 #include <shogun/lib/common.h>
40 
41 namespace shogun
42 {
60 {
61 public:
64 
86  int32_t num_maps,
87  int32_t radius_x, int32_t radius_y,
88  int32_t pooling_width=1, int32_t pooling_height=1,
89  int32_t stride_x=1, int32_t stride_y=1);
90 
92 
100  virtual void set_batch_size(int32_t batch_size);
101 
111  virtual void initialize(CDynamicObjectArray* layers,
112  SGVector<int32_t> input_indices);
113 
128  virtual void initialize_parameters(SGVector<float64_t> parameters,
129  SGVector<bool> parameter_regularizable,
130  float64_t sigma);
131 
141  virtual void compute_activations(SGVector<float64_t> parameters,
142  CDynamicObjectArray* layers);
143 
169  virtual void compute_gradients(SGVector<float64_t> parameters,
170  SGMatrix<float64_t> targets,
171  CDynamicObjectArray* layers,
172  SGVector<float64_t> parameter_gradients);
173 
181 
190  virtual void enforce_max_norm(SGVector<float64_t> parameters,
191  float64_t max_norm);
192 
193  virtual const char* get_name() const { return "NeuralConvolutionalLayer"; }
194 
195 private:
196  void init();
197 
198 protected:
200  int32_t m_num_maps;
201 
203  int32_t m_input_width;
204 
206  int32_t m_input_height;
207 
210 
212  int32_t m_radius_x;
213 
215  int32_t m_radius_y;
216 
219 
222 
224  int32_t m_stride_x;
225 
227  int32_t m_stride_y;
228 
231 
234 
237 
240 };
241 
242 }
243 #endif
virtual void initialize(CDynamicObjectArray *layers, SGVector< int32_t > input_indices)
EConvMapActivationFunction m_activation_function
virtual void compute_activations(SGVector< float64_t > parameters, CDynamicObjectArray *layers)
virtual void set_batch_size(int32_t batch_size)
virtual void enforce_max_norm(SGVector< float64_t > parameters, float64_t max_norm)
SGMatrix< float64_t > m_convolution_output_gradients
virtual void compute_gradients(SGVector< float64_t > parameters, SGMatrix< float64_t > targets, CDynamicObjectArray *layers, SGVector< float64_t > parameter_gradients)
Base class for neural network layers.
Definition: NeuralLayer.h:87
double float64_t
Definition: common.h:50
virtual void initialize_parameters(SGVector< float64_t > parameters, SGVector< bool > parameter_regularizable, float64_t sigma)
Dynamic array class for CSGObject pointers that creates an array that can be used like a list or an a...
virtual const char * get_name() const
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
Main component in convolutional neural networks
virtual float64_t compute_error(SGMatrix< float64_t > targets)
EConvMapActivationFunction
Determines the activation function for neurons in a convolutional feature map.

SHOGUN Machine Learning Toolbox - Documentation