详细描述

Handles convolution and gradient calculation for a single feature map in a convolutional neural network.

Public 成员函数
	CConvolutionalFeatureMap (int32_t input_width, int32_t input_height, int32_t radius_x, int32_t radius_y, int32_t stride_x=1, int32_t stride_y=1, int32_t index=0, EConvMapActivationFunction function=CMAF_IDENTITY, ENLAutoencoderPosition autoencoder_position=NLAP_NONE)

void	compute_activations (SGVector< float64_t > parameters, CDynamicObjectArray *layers, SGVector< int32_t > input_indices, SGMatrix< float64_t > activations)

void	compute_gradients (SGVector< float64_t > parameters, SGMatrix< float64_t > activations, SGMatrix< float64_t > activation_gradients, CDynamicObjectArray *layers, SGVector< int32_t > input_indices, SGVector< float64_t > parameter_gradients)

void	pool_activations (SGMatrix< float64_t > activations, int32_t pooling_width, int32_t pooling_height, SGMatrix< float64_t > pooled_activations, SGMatrix< float64_t > max_indices)

Protected 成员函数
void	convolve (SGMatrix< float64_t > inputs, SGMatrix< float64_t > weights, SGMatrix< float64_t > outputs, bool flip, bool reset_output, int32_t inputs_row_offset, int32_t outputs_row_offset)

void	compute_weight_gradients (SGMatrix< float64_t > inputs, SGMatrix< float64_t > local_gradients, SGMatrix< float64_t > weight_gradients, int32_t inputs_row_offset, int32_t local_gradients_row_offset)

Protected 属性
int32_t	m_input_width

int32_t	m_input_height

int32_t	m_radius_x

int32_t	m_radius_y

int32_t	m_stride_x

int32_t	m_stride_y

int32_t	m_index

EConvMapActivationFunction	m_activation_function

int32_t	m_output_width

int32_t	m_output_height

int32_t	m_input_num_neurons

int32_t	m_output_num_neurons

int32_t	m_row_offset

int32_t	m_filter_width

int32_t	m_filter_height

ENLAutoencoderPosition	m_autoencoder_position

构造及析构函数说明

CConvolutionalFeatureMap	(	int32_t	input_width,
		int32_t	input_height,
		int32_t	radius_x,
		int32_t	radius_y,
		int32_t	stride_x = `1`,
		int32_t	stride_y = `1`,
		int32_t	index = `0`,
		EConvMapActivationFunction	function = `CMAF_IDENTITY`,
		ENLAutoencoderPosition	autoencoder_position = `NLAP_NONE`
	)

Constuctor

参数

input_width	Width of the input
input_height	Height of the input
radius_x	Radius of the convolution filter on the x (width) axis
radius_y	Radius of the convolution filter on the y (height) axis
stride_x	Stride in the x direction
stride_y	Stride in the y direction
index	Index of this feature map in its layer. This affects which part of the activations/activation_gradients matrix the map will store its outputs in.
function	Activation function
autoencoder_position	Autoencoder position

Computes the activations of the feature map

参数

parameters	Vector of parameters for the map. length widthheight+(2radius_x+1)+(2*radius_y+1)
layers	The layers array that forms the network in which the map is being used
input_indices	Indices of the layers that are connected to the map as input
activations	Matrix in which the activations are to be stored

Computes the gradients with respect to the parameters and the inputs to the map

参数

parameters	Vector of parameters for the map. length widthheight+(2radius_x+1)+(2*radius_y+1)
activations	Activations of the map
activation_gradients	Gradients of the error with respect to the map's activations
layers	The layers array that forms the network in which the map is being used
input_indices	Indices of the layers that are connected to the map as input
parameter_gradients	Vector in which the parameters gradients are to be stored

void compute_weight_gradients	(	SGMatrix< float64_t >	inputs,
		SGMatrix< float64_t >	local_gradients,
		SGMatrix< float64_t >	weight_gradients,
		int32_t	inputs_row_offset,
		int32_t	local_gradients_row_offset
	)

protected

Computes the gradients of the error with respect to the weights, for a particular input matrix

参数

inputs	Inputs matrix
local_gradients	Gradients with respect the map's pre-activations
weight_gradients	Matrix to store the gradients in
inputs_row_offset	Offset for accessing the rows of the inputs matrix
local_gradients_row_offset	Offset for accessing the rows of the local gradients matrix

protected

Perfoms convolution

参数

inputs	Inputs matrix. Each column in the matrix is treated as an image in column major format
weights	Convolution filter
outputs	Output matrix
flip	If true the weights are flipped, performing cross-correlation instead of convolution
reset_output	true the output is reset to zero before performing convolution
inputs_row_offset	Index of the row at which the input image starts
outputs_row_offset	Index of the row at which the output image starts

Applies max pooling to the activations

参数

activations	Activations of the map
pooling_width	Width of the pooling region
pooling_height	Height of the pooling region
pooled_activations	Result of the pooling process
max_indices	Row indices of the max elements for each pooling region