A convolution layer class. More...

#include <dnn_layer_conv.h>

Inheritance diagram for dnn::layer_conv:

Public Member Functions
	layer_conv (const arma::uword n_channels, const arma::uword n_kernel, const arma::uword n_pad=0, const arma::uword n_stride=1)
	Convolution layer constructor. More...

void	init (void)
	Initialization of layer. More...

void	upd_buf_size (arma::uword nmb)
	Updates the buffer sizes. More...

arma::Mat< DNN_Dtype >	rotate_180 (const arma::Mat< DNN_Dtype > &M)
	Rotates a matrix 180 degree. More...

arma::Cube< DNN_Dtype >	rotate_180 (const arma::Cube< DNN_Dtype > &C)
	Rotates each matrix in a cube 180 degree. More...

template<typename DNN_Dtype >
void	im2col_nzp (DNN_Dtype Dptr, const DNN_Dtype Xptr, const arma::uword XRows, const arma::uword XCols, const arma::uword XDepth, const arma::uword KRows, const arma::uword KCols, const arma::uword SRows, const arma::uword SCols)
	Im2col without zero padding. More...

template<typename DNN_Dtype >
void	im2col (DNN_Dtype Dptr, const DNN_Dtype Xptr, const arma::uword XRows, const arma::uword XCols, const arma::uword XDepth, const arma::uword KRows, const arma::uword KCols, const arma::uword PRows, const arma::uword PCols, const arma::uword SRows, const arma::uword SCols)
	Im2col with zero padding. More...

template<typename DNN_Dtype >
void	im2row (DNN_Dtype Dptr, const DNN_Dtype Xptr, const unsigned int XRows, const unsigned int XCols, const unsigned int XDepth, const unsigned int KRows, const unsigned int KCols, const unsigned int PRows, const unsigned int PCols, const unsigned int SRows, const unsigned int SCols)
	Im2row with zero padding. More...

void	disp (void)
	Display info about layer. More...

arma::uword	get_nrof_params (void)
	Get info about number of trainable parameters in layer. More...

void	prop (void)
	Forward propagation though layer. More...

void	prop_mb (void)
	Forward mini batch propagation though layer. More...

void	backprop (void)
	Backpropagation of mini batch propagation though layer. More...

void	update (void)
	Updates the trainable parameters. More...

arma::Mat< DNN_Dtype >	weights2img (arma::uword IR)
	Generate an image of the weights. More...

Public Member Functions inherited from dnn::layer
	layer (void)
	Layer constructor. More...

	~layer ()

virtual void	enable_training (void)
	Enable training of layer. More...

virtual void	disable_training (void)
	Disable training of layer. More...

virtual void	enable_bias (void)
	Enable bias term in layer. More...

virtual void	disable_bias (void)
	Disable bias term in layer. More...

virtual arma::Mat< DNN_Dtype >	get_B (void)
	Get bias. More...

virtual arma::Cube< DNN_Dtype >	get_W (void)
	Get weights. More...

virtual void	set_B (arma::Mat< DNN_Dtype > &b)
	Set bias. More...

virtual void	set_W (arma::Cube< DNN_Dtype > &w)
	Set weights. More...

virtual void	set_phase (PHASE p)
	Set phase/state. More...

virtual void	set_left (layer *lptr)
	Set pointer to left layer. More...

virtual void	set_right (layer *rptr)
	Set pointer to right layer. More...

virtual void	set_id (const std::string str)
	Set layer id string. More...

virtual std::string	get_id (void)
	Get layer id string. More...

virtual void	set_type (const std::string str)
	Set layer type string. More...

virtual std::string	get_type (void)
	Get layer type string. More...

virtual void	set_ix (const arma::uword n)
	Set layer index. More...

virtual arma::uword	get_ix (void)
	Get layer index. More...

virtual void	set_batch_size (const arma::uword n)
	Set mini batch size. More...

virtual arma::uword	get_batch_size (void)
	Get mini batch size. More...

virtual void	set_Y1 (arma::Mat< DNN_Dtype > &y)
	Set output buffer. More...

virtual void	set_Y (arma::Mat< DNN_Dtype > &y)
	Set output buffer - mini batch. More...

virtual void	set_Dleft (arma::Mat< DNN_Dtype > &d)
	Set error output buffer - mini batch. More...

virtual void	set_rows_in (arma::uword r)
	Set input buffer row size. More...

virtual arma::uword	get_nrof_rows (void)
	Get output buffer row size. More...

virtual void	set_cols_in (arma::uword c)
	Set input buffer column size. More...

virtual arma::uword	get_nrof_cols (void)
	Get output buffer column size. More...

virtual void	set_channels_in (arma::uword l)
	Set input buffer channel/layer size. More...

virtual arma::uword	get_nrof_channels (void)
	Get output buffer channel/layer size. More...

virtual void	set_opt_alg (opt &alg_class)
	Set pointer to optimizer class. More...

virtual opt *	get_opt_alg (void)
	Get pointer to optimizer class. More...

virtual arma::uword	get_nrof_inputs (void)
	Get total number of layer inputs. More...

virtual arma::uword	get_nrof_outputs (void)
	Get total number of layer outputs. More...

virtual arma::Mat< DNN_Dtype >	get_Y1 (void)
	Get output buffer. More...

virtual arma::Mat< DNN_Dtype > *	get_Y1_ptr (void)
	Get output buffer pointer. More...

virtual DNN_Dtype *	get_Y1_memptr (void)
	Get output buffer memory pointer. More...

virtual arma::Mat< DNN_Dtype >	get_Y (void)
	Get output buffer - mini batch. More...

virtual arma::Mat< DNN_Dtype > *	get_Y_ptr (void)
	Get output buffer pointer - mini batch. More...

virtual DNN_Dtype *	get_Y_memptr (void)
	Get output buffer memory pointer - mini batch. More...

virtual DNN_Dtype *	get_Y_colptr (const arma::uword n)
	Get output buffer memory column pointer - mini batch. More...

virtual arma::Mat< DNN_Dtype >	get_Dleft ()
	Get error buffer - mini batch. More...

virtual arma::Mat< DNN_Dtype > *	get_Dleft_ptr (void)
	Get error buffer pointer - mini batch. More...

virtual DNN_Dtype *	get_Dleft_memptr (void)
	Get error buffer memory pointer - mini batch. More...

virtual DNN_Dtype *	get_Dleft_colptr (const arma::uword n)
	Get error buffer memory column pointer - mini batch. More...

virtual void	save_layer_param (std::string name, PARAM_FORMAT f=PARAM_FORMAT::ASCII)
	Save layer weight and bias. More...

virtual void	load_layer_param (std::string name, PARAM_FORMAT f=PARAM_FORMAT::AUTO)
	Load layer weight and bias. More...

template<typename T >
void	init_weights (T &w, arma::uword fan_in, arma::uword fan_out, INIT_W_ALG alg, INIT_W_DIST dist)
	Initiate weights. More...

DNN_Dtype	sigmoid (const DNN_Dtype x)
	Sigmoid function - scalar. More...

arma::Mat< DNN_Dtype >	sigmoid (const arma::Mat< DNN_Dtype > &x)
	Sigmoid function - matrix. More...

arma::Mat< DNN_Dtype >	softmax (const arma::Mat< DNN_Dtype > &x)
	Softmax function - matrix. More...

Private Attributes
arma::uword	N_filter_size
	Conv. filter size. More...

arma::uword	N_pad
	Padding. More...

arma::uword	N_stride
	Stride. More...

arma::Cube< DNN_Dtype >	C
	Input expanded by im2col. More...

arma::Mat< DNN_Dtype >	Cbp
	Input expanded by im2col. More...

Additional Inherited Members
Protected Attributes inherited from dnn::layer
layer *	left
	Pointer to previous layer. More...

layer *	right
	Pointer to next layer. More...

std::string	id
	Layer id string. More...

std::string	type
	Layer type string. More...

arma::uword	layer_ix
	Layer index [0..]. More...

bool	train_par
	Enable training. More...

bool	add_bias
	Enable bias. More...

opt *	opt_alg
	Pointer to optimizer. More...

PHASE	phase
	Active state/phase. More...

arma::uword	N_batch
	Mini batch size. More...

arma::uword	N_rows_left
	Input rows. More...

arma::uword	N_cols_left
	Input cols. More...

arma::uword	N_channels_left
	Input channels, number of filters. More...

arma::uword	N_rows_right
	Output rows. More...

arma::uword	N_cols_right
	Output cols. More...

arma::uword	N_channels_right
	Output channels, number of filters. More...

arma::uword	N_left
	Total size left. More...

arma::uword	N_right
	Total size right. More...

arma::Mat< DNN_Dtype >	Y
	Output buffer mini batch [N_right,N_batch]. More...

arma::Mat< DNN_Dtype >	Y1
	Output buffer [N_right,1]. More...

arma::Mat< DNN_Dtype >	Dleft
	Error buffer [N_left,N_batch]. More...

arma::Cube< DNN_Dtype >	W
	Weights. More...

arma::Mat< DNN_Dtype >	B
	Bias. More...

Detailed Description

A convolution layer class.

A layer that convolves (actually correlates) the input layers with a stack of kernel filters. If the input has size [Ri,Ci,Li] and the filter kernel har size [K,K,LiLo] then the output will have size [Ro,Co,Lo] depending upon padding and stride parameters during the convolution.

Definition at line 31 of file dnn_layer_conv.h.

Constructor & Destructor Documentation

◆ layer_conv()

dnn::layer_conv::layer_conv	(	const arma::uword	n_channels,
		const arma::uword	n_kernel,
		const arma::uword	n_pad = `0`,
		const arma::uword	n_stride = `1`
	)

inline

Convolution layer constructor.

Parameters

[in]	n_channels	Nr of output channels/layers
[in]	n_kernel	Filter kernel size [KxK]
[in]	n_pad	Input image padding
[in]	n_stride	Stride (for row AND col)

Definition at line 49 of file dnn_layer_conv.h.

Member Function Documentation

◆ backprop()

void dnn::layer_conv::backprop ( void )

inlinevirtual

Backpropagation of mini batch propagation though layer.

Performas a error backpropagation mini batch pass through layer

Reimplemented from dnn::layer.

Definition at line 363 of file dnn_layer_conv.h.

◆ disp()

void dnn::layer_conv::disp ( void )

inlinevirtual

Display info about layer.

Reimplemented from dnn::layer.

Definition at line 288 of file dnn_layer_conv.h.

◆ get_nrof_params()

arma::uword dnn::layer_conv::get_nrof_params ( void )

inlinevirtual

Get info about number of trainable parameters in layer.

Returns: Number of trainable parameters

Reimplemented from dnn::layer.

Definition at line 303 of file dnn_layer_conv.h.

◆ im2col()

template<typename DNN_Dtype >

void dnn::layer_conv::im2col	(	DNN_Dtype *	Dptr,
		const DNN_Dtype *	Xptr,
		const arma::uword	XRows,
		const arma::uword	XCols,
		const arma::uword	XDepth,
		const arma::uword	KRows,
		const arma::uword	KCols,
		const arma::uword	PRows,
		const arma::uword	PCols,
		const arma::uword	SRows,
		const arma::uword	SCols
	)

inline

Im2col with zero padding.

Parameters

[in,out]	Dptr,Xptr	Pointers to destination and source data
[in]	XRows,XCols	Number of rows/cols in source data
[in]	XDepth	Number of channels in source data
[in]	KRows,KCols	Number of rows/cols in kernel (filter)
[in]	PRows,PCols	Padding for row/col (on each side of image)
[in]	SRows,SCols	Stride for row/col

im2col generates a matrix of size [XDepth*KRows*KCols,DRow*Dcol] where DCol=(XCol+2PCol-KCol)/SCol+1 and DRow=(XRow+2PRow-KRow)/SRow+1

Definition at line 183 of file dnn_layer_conv.h.

◆ im2col_nzp()

template<typename DNN_Dtype >

void dnn::layer_conv::im2col_nzp	(	DNN_Dtype *	Dptr,
		const DNN_Dtype *	Xptr,
		const arma::uword	XRows,
		const arma::uword	XCols,
		const arma::uword	XDepth,
		const arma::uword	KRows,
		const arma::uword	KCols,
		const arma::uword	SRows,
		const arma::uword	SCols
	)

inline

Im2col without zero padding.

Parameters

[in,out]	Dptr,Xptr	Pointers to destination and source data
[in]	XRows,XCols	Number of rows/cols in source data
[in]	XDepth	Number of channels in source data
[in]	KRows,KCols	Number of rows/cols in kernel (filter)
[in]	SRows,SCols	Stride for row/col

im2col_nzp generates a matrix of size [XDepth*KRows*KCols,DRow*Dcol] where DCol=(XCol-KCol)/SCol+1 and DRow=(XRow-KRow)/SRow+1

Definition at line 141 of file dnn_layer_conv.h.

◆ im2row()

template<typename DNN_Dtype >

void dnn::layer_conv::im2row	(	DNN_Dtype *	Dptr,
		const DNN_Dtype *	Xptr,
		const unsigned int	XRows,
		const unsigned int	XCols,
		const unsigned int	XDepth,
		const unsigned int	KRows,
		const unsigned int	KCols,
		const unsigned int	PRows,
		const unsigned int	PCols,
		const unsigned int	SRows,
		const unsigned int	SCols
	)

inline

Im2row with zero padding.

Parameters

[in,out]	Dptr,Xptr	Pointers to destination and source data
[in]	XRows,XCols	Number of rows/cols in source data
[in]	XDepth	Number of channels in source data
[in]	KRows,KCols	Number of rows/cols in kernel (filter)
[in]	PRows,PCols	Padding for row/col (on each side of image)
[in]	SRows,SCols	Stride for row/col

im2row generates a matrix of size [DRow*Dcol,XDepth*KRows*KCols] where DCol=(XCol+2PCol-KCol)/SCol+1 and DRow=(XRow+2PRow-KRow)/SRow+1

Definition at line 246 of file dnn_layer_conv.h.

◆ init()

void dnn::layer_conv::init ( void )

inlinevirtual

Initialization of layer.

Calculates the output and internal buffer sizes and initializes the parameters

Reimplemented from dnn::layer.

Definition at line 66 of file dnn_layer_conv.h.

◆ prop()

void dnn::layer_conv::prop ( void )

inlinevirtual

Forward propagation though layer.

Performas a forward pass through layer

Reimplemented from dnn::layer.

Definition at line 313 of file dnn_layer_conv.h.

◆ prop_mb()

void dnn::layer_conv::prop_mb ( void )

inlinevirtual

Forward mini batch propagation though layer.

Performas a forward mini batch pass through layer

Reimplemented from dnn::layer.

Definition at line 337 of file dnn_layer_conv.h.

◆ rotate_180() [1/2]

arma::Mat<DNN_Dtype> dnn::layer_conv::rotate_180 ( const arma::Mat< DNN_Dtype > & M )

inline

Rotates a matrix 180 degree.

Parameters

[in] M Input matrix

Returns: Rotated matrix

Rotates a matrix 180 degree (equals fliplr(flipud(M)) in Matlab)

Definition at line 106 of file dnn_layer_conv.h.

◆ rotate_180() [2/2]

arma::Cube<DNN_Dtype> dnn::layer_conv::rotate_180 ( const arma::Cube< DNN_Dtype > & C )

inline

Rotates each matrix in a cube 180 degree.

Parameters

[in] C Input matrix

Returns: Cube with each slice rotated

Rotates each matrix 180 degree (equals flipud(fliplr(C)) in Matlab)

Definition at line 119 of file dnn_layer_conv.h.

◆ upd_buf_size()

void dnn::layer_conv::upd_buf_size ( arma::uword nmb )

inlinevirtual

Updates the buffer sizes.

Parameters

[in] nmb New mini batch buffer size

Updates and clears the buffer sizes, called when size of mini batch is changed

Reimplemented from dnn::layer.

Definition at line 93 of file dnn_layer_conv.h.

◆ update()

void dnn::layer_conv::update ( void )

inlinevirtual

Updates the trainable parameters.

Calculates the gradients and update the trainiable parameters

Reimplemented from dnn::layer.

Definition at line 384 of file dnn_layer_conv.h.

◆ weights2img()

arma::Mat<DNN_Dtype> dnn::layer_conv::weights2img ( arma::uword IR )

inline

Generate an image of the weights.

Parameters

[in] IR Number of images per row

Returns: An image of the weights

Flattens weights from each layer into a concatenated image

Definition at line 423 of file dnn_layer_conv.h.

Member Data Documentation

◆ C

arma::Cube<DNN_Dtype> dnn::layer_conv::C

private

Input expanded by im2col.

Definition at line 38 of file dnn_layer_conv.h.

◆ Cbp

arma::Mat<DNN_Dtype> dnn::layer_conv::Cbp

private

Input expanded by im2col.

Definition at line 39 of file dnn_layer_conv.h.

◆ N_filter_size

arma::uword dnn::layer_conv::N_filter_size

private

Conv. filter size.

Definition at line 34 of file dnn_layer_conv.h.

◆ N_pad

arma::uword dnn::layer_conv::N_pad

private

Padding.

Definition at line 35 of file dnn_layer_conv.h.

◆ N_stride

arma::uword dnn::layer_conv::N_stride

private

Stride.

Definition at line 36 of file dnn_layer_conv.h.

The documentation for this class was generated from the following file:

dnn_layer_conv.h

Public Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ layer_conv()

Member Function Documentation

◆ backprop()

◆ disp()

◆ get_nrof_params()

◆ im2col()

◆ im2col_nzp()

◆ im2row()

◆ init()

◆ prop()

◆ prop_mb()

◆ rotate_180() [1/2]

◆ rotate_180() [2/2]

◆ upd_buf_size()

◆ update()

◆ weights2img()

Member Data Documentation

◆ C

◆ Cbp

◆ N_filter_size

◆ N_pad

◆ N_stride