34 #ifndef __NEURALCONVOLUTIONALLAYER_H__
35 #define __NEURALCONVOLUTIONALLAYER_H__
103 int32_t radius_x, int32_t radius_y,
104 int32_t pooling_width=1, int32_t pooling_height=1,
105 int32_t stride_x=1, int32_t stride_y=1,
210 virtual const char*
get_name()
const {
return "NeuralConvolutionalLayer"; }
CNeuralConvolutionalLayer()
EConvMapActivationFunction m_activation_function
virtual void compute_activations(SGVector< float64_t > parameters, CDynamicObjectArray *layers)
virtual void set_batch_size(int32_t batch_size)
EInitializationMode m_initialization_mode
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.
virtual ~CNeuralConvolutionalLayer()
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 void initialize_neural_layer(CDynamicObjectArray *layers, SGVector< int32_t > input_indices)
virtual const char * get_name() const
all of classes and functions are contained in the shogun namespace
Main component in convolutional neural networks
SGMatrix< float64_t > m_max_indices
virtual float64_t compute_error(SGMatrix< float64_t > targets)
EConvMapActivationFunction
Determines the activation function for neurons in a convolutional feature map.
int32_t m_input_num_channels
SGMatrix< float64_t > m_convolution_output