#include <GBlock.h>

Inheritance diagram for GClasses::GBlockConvolutional2D:

Classes
struct	Image
	Image abstraction to facilitate convolution. More...

Public Member Functions
	GBlockConvolutional2D (size_t width, size_t height, size_t channels, size_t kWidth, size_t kHeight, size_t kCount=0)
	General-purpose constructor. More...

	GBlockConvolutional2D (size_t kWidth, size_t kHeight, size_t kCount=0)
	Constructor that will automatically use the upstream convolutional block when added to a neural network. More...

	GBlockConvolutional2D (GDomNode *pNode)

void	addKernel ()

void	addKernels (size_t n)

virtual void	backProp (GContext &ctx, const GVec &input, const GVec &output, const GVec &outBlame, GVec &inBlame) const override
	Evaluates outBlame, and adds to inBlame. (Note that it "adds to" the inBlame because multiple blocks may fork from a common source.) More...

const GVec &	bias () const

GVec &	bias ()

virtual void	copyWeights (const GBlock *pSource) override
	Copy the weights from pSource to this block. (Assumes pSource is the same type of block.) More...

virtual void	diminishWeights (double amount, bool regularizeBiases) override
	Moves all weights in the direction of zero by the specified amount. More...

virtual void	forwardProp (GContext &ctx, const GVec &input, GVec &output) const override
	Evaluate the input, set the output. More...

size_t	inputChannels () const

size_t	inputHeight () const

virtual size_t	inputs () const override
	Returns the number of inputs this block consumes. More...

size_t	inputWidth () const

size_t	kernelChannels () const

size_t	kernelCount () const

size_t	kernelHeight () const

const GMatrix &	kernels () const

GMatrix &	kernels ()

size_t	kernelWidth () const

virtual void	maxNorm (double min, double max) override
	Scales weights if necessary such that the manitude of the weights (not including the bias) feeding into each unit are >= min and <= max. More...

virtual std::string	name () const override
	Returns the name of this block. More...

size_t	outputChannels () const

size_t	outputHeight () const

virtual size_t	outputs () const override
	Returns the number of outputs this block produces. More...

size_t	outputWidth () const

virtual void	perturbWeights (GRand &rand, double deviation) override
	Perturbs the weights that feed into the specifed units with Gaussian noise. The default values apply the perturbation to all units. More...

virtual void	resetWeights (GRand &rand) override
	Initialize the weights, usually with small random values. More...

virtual void	resize (size_t inputs, size_t outputs) override
	Resizes this block. More...

virtual void	scaleWeights (double factor, bool scaleBiases) override
	Multiplies all the weights by the specified factor. More...

virtual GDomNode *	serialize (GDom *pDoc) const override
	Marshall this block into a DOM. More...

void	setInputInterlaced (bool interlaced)

void	setInterlaced (bool interlaced)

void	setKernelsInterlaced (bool interlaced)

void	setOutputInterlaced (bool interlaced)

void	setPadding (size_t px, size_t py=none)

void	setStride (size_t sx, size_t sy=none)

virtual void	step (double learningRate, const GVec &gradient) override
	Add the weight and bias gradient to the weights. More...

virtual BlockType	type () const override
	Returns the type of this block. More...

virtual void	updateGradient (GContext &ctx, const GVec &input, const GVec &outBlame, GVec &gradient) const override
	Updates the gradient for updating the weights by gradient descent. (Assumes the error has already been computed and deactivated.) More...

virtual size_t	vectorToWeights (const double *pVector) override
	Deserialize from a vector to the weights in this block. Return the number of elements consumed. More...

virtual size_t	weightCount () const override
	Returns the number of double-precision elements necessary to serialize the weights of this block into a vector. More...

virtual size_t	weightsToVector (double *pOutVector) const override
	Serialize the weights in this block into a vector. Return the number of elements written. More...

Public Member Functions inherited from GClasses::GBlock
	GBlock ()

	GBlock (GDomNode *pNode)

virtual	~GBlock ()

virtual bool	elementWise () const
	Returns true iff this block operates only on individual elements. More...

size_t	inPos () const
	Returns the offset in the previous layer's output where values are fed as input to this block. More...

virtual bool	isRecurrent () const
	Returns true iff this block is recurrent. More...

void	setInPos (size_t n)
	Sets the starting offset in the previous layer's output where values will be fed as input to this block. More...

virtual std::string	to_str () const
	Returns a string representation of this block. More...

virtual bool	usesGPU ()
	Returns true iff this block does its computations in parallel on a GPU. More...

Static Public Attributes
static size_t	none

Protected Attributes
Image	m_actImage

GVec	m_bias
	Data. More...

GVec	m_biasDelta

size_t	m_channels

Image	m_deltaImage

Image	m_errImage

size_t	m_height

Image	m_inputImage

Image	m_kernelImage
	Data as images. More...

GMatrix	m_kernels

size_t	m_kHeight

size_t	m_kWidth
	Kernel dimensions (kernel channels = input channels) More...

size_t	m_outputHeight

size_t	m_outputWidth
	Output dimensions (derived; output channels = kernel count) More...

Image	m_upStreamErrorImage

size_t	m_width
	Input dimensions. More...

Protected Attributes inherited from GClasses::GBlock
size_t	m_inPos

Additional Inherited Members
Public Types inherited from GClasses::GBlock
Static Public Member Functions inherited from GClasses::GBlock
static GBlock *	deserialize (GDomNode *pNode)
	Unmarshalls the specified DOM node into a block object. More...

Protected Member Functions inherited from GClasses::GBlock
GDomNode *	baseDomNode (GDom *pDoc) const

void	basicTest ()
	Exercises some basic functionality that all blocks have in common. More...

Constructor & Destructor Documentation

GClasses::GBlockConvolutional2D::GBlockConvolutional2D	(	size_t	width,
		size_t	height,
		size_t	channels,
		size_t	kWidth,
		size_t	kHeight,
		size_t	kCount = `0`
	)

General-purpose constructor.

GClasses::GBlockConvolutional2D::GBlockConvolutional2D	(	size_t	kWidth,
		size_t	kHeight,
		size_t	kCount = `0`
	)

Constructor that will automatically use the upstream convolutional block when added to a neural network.

GClasses::GBlockConvolutional2D::GBlockConvolutional2D ( GDomNode * pNode )

Member Function Documentation

void GClasses::GBlockConvolutional2D::addKernel ( )

void GClasses::GBlockConvolutional2D::addKernels ( size_t n )

virtual void GClasses::GBlockConvolutional2D::backProp	(	GContext &	ctx,
		const GVec &	input,
		const GVec &	output,
		const GVec &	outBlame,
		GVec &	inBlame
	)		const

overridevirtual

Evaluates outBlame, and adds to inBlame. (Note that it "adds to" the inBlame because multiple blocks may fork from a common source.)

Implements GClasses::GBlock.

const GVec& GClasses::GBlockConvolutional2D::bias ( ) const

inline

GVec& GClasses::GBlockConvolutional2D::bias ( )

inline

virtual void GClasses::GBlockConvolutional2D::copyWeights ( const GBlock * pSource )

overridevirtual

Copy the weights from pSource to this block. (Assumes pSource is the same type of block.)

Implements GClasses::GBlock.

virtual void GClasses::GBlockConvolutional2D::diminishWeights	(	double	amount,
		bool	regularizeBiases
	)

overridevirtual

Moves all weights in the direction of zero by the specified amount.

Implements GClasses::GBlock.

virtual void GClasses::GBlockConvolutional2D::forwardProp	(	GContext &	ctx,
		const GVec &	input,
		GVec &	output
	)		const

overridevirtual

Evaluate the input, set the output.

Implements GClasses::GBlock.

size_t GClasses::GBlockConvolutional2D::inputChannels ( ) const

inline

size_t GClasses::GBlockConvolutional2D::inputHeight ( ) const

inline

virtual size_t GClasses::GBlockConvolutional2D::inputs ( ) const

inlineoverridevirtual

Returns the number of inputs this block consumes.

Implements GClasses::GBlock.

size_t GClasses::GBlockConvolutional2D::inputWidth ( ) const

inline

size_t GClasses::GBlockConvolutional2D::kernelChannels ( ) const

inline

size_t GClasses::GBlockConvolutional2D::kernelCount ( ) const

inline

size_t GClasses::GBlockConvolutional2D::kernelHeight ( ) const

inline

const GMatrix& GClasses::GBlockConvolutional2D::kernels ( ) const

inline

GMatrix& GClasses::GBlockConvolutional2D::kernels ( )

inline

size_t GClasses::GBlockConvolutional2D::kernelWidth ( ) const

inline

virtual void GClasses::GBlockConvolutional2D::maxNorm	(	double	min,
		double	max
	)

overridevirtual

Scales weights if necessary such that the manitude of the weights (not including the bias) feeding into each unit are >= min and <= max.

Implements GClasses::GBlock.

virtual std::string GClasses::GBlockConvolutional2D::name ( ) const

inlineoverridevirtual

Returns the name of this block.

Implements GClasses::GBlock.

size_t GClasses::GBlockConvolutional2D::outputChannels ( ) const

inline

size_t GClasses::GBlockConvolutional2D::outputHeight ( ) const

inline

virtual size_t GClasses::GBlockConvolutional2D::outputs ( ) const

inlineoverridevirtual

Returns the number of outputs this block produces.

Implements GClasses::GBlock.

size_t GClasses::GBlockConvolutional2D::outputWidth ( ) const

inline

virtual void GClasses::GBlockConvolutional2D::perturbWeights	(	GRand &	rand,
		double	deviation
	)

overridevirtual

Perturbs the weights that feed into the specifed units with Gaussian noise. The default values apply the perturbation to all units.

Implements GClasses::GBlock.

virtual void GClasses::GBlockConvolutional2D::resetWeights ( GRand & rand )

overridevirtual

Initialize the weights, usually with small random values.

Implements GClasses::GBlock.

virtual void GClasses::GBlockConvolutional2D::resize	(	size_t	inputs,
		size_t	outputs
	)

overridevirtual

Resizes this block.

Implements GClasses::GBlock.

virtual void GClasses::GBlockConvolutional2D::scaleWeights	(	double	factor,
		bool	scaleBiases
	)

overridevirtual

Multiplies all the weights by the specified factor.

Implements GClasses::GBlock.

virtual GDomNode* GClasses::GBlockConvolutional2D::serialize ( GDom * pDoc ) const

overridevirtual

Marshall this block into a DOM.

Implements GClasses::GBlock.

void GClasses::GBlockConvolutional2D::setInputInterlaced ( bool interlaced )

void GClasses::GBlockConvolutional2D::setInterlaced ( bool interlaced )

void GClasses::GBlockConvolutional2D::setKernelsInterlaced ( bool interlaced )

void GClasses::GBlockConvolutional2D::setOutputInterlaced ( bool interlaced )

void GClasses::GBlockConvolutional2D::setPadding	(	size_t	px,
		size_t	py = `none`
	)

void GClasses::GBlockConvolutional2D::setStride	(	size_t	sx,
		size_t	sy = `none`
	)

virtual void GClasses::GBlockConvolutional2D::step	(	double	learningRate,
		const GVec &	gradient
	)

overridevirtual

Add the weight and bias gradient to the weights.

Implements GClasses::GBlock.

virtual BlockType GClasses::GBlockConvolutional2D::type ( ) const

inlineoverridevirtual

Returns the type of this block.

Implements GClasses::GBlock.

virtual void GClasses::GBlockConvolutional2D::updateGradient	(	GContext &	ctx,
		const GVec &	input,
		const GVec &	outBlame,
		GVec &	gradient
	)		const

overridevirtual

Updates the gradient for updating the weights by gradient descent. (Assumes the error has already been computed and deactivated.)

Implements GClasses::GBlock.

virtual size_t GClasses::GBlockConvolutional2D::vectorToWeights ( const double * pVector )

overridevirtual

Deserialize from a vector to the weights in this block. Return the number of elements consumed.

Implements GClasses::GBlock.

virtual size_t GClasses::GBlockConvolutional2D::weightCount ( ) const

overridevirtual

Returns the number of double-precision elements necessary to serialize the weights of this block into a vector.

Implements GClasses::GBlock.

virtual size_t GClasses::GBlockConvolutional2D::weightsToVector ( double * pOutVector ) const

overridevirtual

Serialize the weights in this block into a vector. Return the number of elements written.

Implements GClasses::GBlock.

Member Data Documentation

Image GClasses::GBlockConvolutional2D::m_actImage

protected

GVec GClasses::GBlockConvolutional2D::m_bias

protected

Data.

GVec GClasses::GBlockConvolutional2D::m_biasDelta

protected

size_t GClasses::GBlockConvolutional2D::m_channels

protected

Image GClasses::GBlockConvolutional2D::m_deltaImage

protected

Image GClasses::GBlockConvolutional2D::m_errImage

protected

size_t GClasses::GBlockConvolutional2D::m_height

protected

Image GClasses::GBlockConvolutional2D::m_inputImage

protected

Image GClasses::GBlockConvolutional2D::m_kernelImage

protected

Data as images.

GMatrix GClasses::GBlockConvolutional2D::m_kernels

protected

size_t GClasses::GBlockConvolutional2D::m_kHeight

protected

size_t GClasses::GBlockConvolutional2D::m_kWidth

protected

Kernel dimensions (kernel channels = input channels)

size_t GClasses::GBlockConvolutional2D::m_outputHeight

protected

size_t GClasses::GBlockConvolutional2D::m_outputWidth

protected

Output dimensions (derived; output channels = kernel count)

Image GClasses::GBlockConvolutional2D::m_upStreamErrorImage

protected

size_t GClasses::GBlockConvolutional2D::m_width

protected

Input dimensions.

size_t GClasses::GBlockConvolutional2D::none

static

Classes

Public Member Functions

Static Public Attributes

Protected Attributes

Additional Inherited Members

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation