Class implementing a convolutional hebbian layer. More...

#include <ConvHebbian.hpp>

Inheritance diagram for mic::mlnn::experimental::ConvHebbian< eT >:

Collaboration diagram for mic::mlnn::experimental::ConvHebbian< eT >:

Public Member Functions
	ConvHebbian (size_t input_width, size_t input_height, size_t input_depth, size_t nfilters, size_t filter_size, size_t stride=1, std::string name_="ConvHebbian")

virtual	~ConvHebbian ()

void	forward (bool test_=false)

void	backward ()

void	update (eT alpha_, eT decay_=0.0f)

std::vector< std::shared_ptr < mic::types::Matrix< eT > > > &	getOutputActivations ()

std::vector< std::shared_ptr < mic::types::Matrix< eT > > > &	getOutputReconstruction ()

eT	getOutputReconstructionError ()
	getOutputReconstructionError More...

std::vector< std::shared_ptr < mic::types::Matrix< eT > > > &	getWeightActivations ()

std::vector< std::shared_ptr < mic::types::Matrix< eT > > > &	getWeightSimilarity (bool fillDiagonal=false)
	Returns cosine similarity matrix of filters. More...

std::vector< std::shared_ptr < mic::types::Matrix< eT > > > &	getWeightDissimilarity ()

Public Member Functions inherited from mic::mlnn::Layer< eT >
	Layer (size_t input_height_, size_t input_width_, size_t input_depth_, size_t output_height_, size_t output_width_, size_t output_depth_, LayerTypes layer_type_, std::string name_="layer")

virtual	~Layer ()

mic::types::MatrixPtr< eT >	forward (mic::types::MatrixPtr< eT > x_, bool test=false)

mic::types::MatrixPtr< eT >	backward (mic::types::MatrixPtr< eT > dy_)

virtual void	resizeBatch (size_t batch_size_)

template<typename loss >
mic::types::MatrixPtr< eT >	calculateNumericalGradient (mic::types::MatrixPtr< eT > x_, mic::types::MatrixPtr< eT > target_y_, mic::types::MatrixPtr< eT > param_, loss loss_, eT delta_)

virtual void	resetGrads ()

size_t	inputSize ()
	Returns size (length) of inputs. More...

size_t	outputSize ()
	Returns size (length) of outputs. More...

size_t	batchSize ()
	Returns size (length) of (mini)batch. More...

const std::string	name () const
	Returns name of the layer. More...

mic::types::MatrixPtr< eT >	getParam (std::string name_)

mic::types::MatrixPtr< eT >	getState (std::string name_)

mic::types::MatrixPtr< eT >	getGradient (std::string name_)

void	setState (std::string name_, mic::types::MatrixPtr< eT > mat_ptr_)

template<typename omT >
void	setOptimization ()

const std::string	type () const

virtual std::string	streamLayerParameters ()

mic::types::MatrixPtr< eT >	lazyReturnSampleFromBatch (mic::types::MatrixPtr< eT > batch_ptr_, mic::types::MatrixArray< eT > &array_, std::string id_, size_t sample_number_, size_t sample_size_)

mic::types::MatrixPtr< eT >	lazyReturnInputSample (mic::types::MatrixPtr< eT > batch_ptr_, size_t sample_number_)

mic::types::MatrixPtr< eT >	lazyReturnOutputSample (mic::types::MatrixPtr< eT > batch_ptr_, size_t sample_number_)

mic::types::MatrixPtr< eT >	lazyReturnChannelFromSample (mic::types::MatrixPtr< eT > sample_ptr_, mic::types::MatrixArray< eT > &array_, std::string id_, size_t sample_number_, size_t channel_number_, size_t height_, size_t width_)

mic::types::MatrixPtr< eT >	lazyReturnInputChannel (mic::types::MatrixPtr< eT > sample_ptr_, size_t sample_number_, size_t channel_number_)

mic::types::MatrixPtr< eT >	lazyReturnOutputChannel (mic::types::MatrixPtr< eT > sample_ptr_, size_t sample_number_, size_t channel_number_)

void	lazyAllocateMatrixVector (std::vector< std::shared_ptr< mic::types::Matrix< eT > > > &vector_, size_t vector_size_, size_t matrix_height_, size_t matrix_width_)

virtual std::vector < std::shared_ptr < mic::types::Matrix< eT > > > &	getInputActivations ()

virtual std::vector < std::shared_ptr < mic::types::Matrix< eT > > > &	getInputGradientActivations ()

virtual std::vector < std::shared_ptr < mic::types::Matrix< eT > > > &	getOutputGradientActivations ()

Protected Attributes
size_t	nfilters = 0

size_t	filter_size = 0

size_t	stride = 0

std::vector< std::vector < mic::types::Matrix< eT > > >	W

mic::types::MatrixPtr< eT >	x2col

mic::types::MatrixPtr< eT >	conv2col

Protected Attributes inherited from mic::mlnn::Layer< eT >
size_t	input_height
	Height of the input (e.g. 28 for MNIST). More...

size_t	input_width
	Width of the input (e.g. 28 for MNIST). More...

size_t	input_depth
	Number of channels of the input (e.g. 3 for RGB images). More...

size_t	output_height
	Number of receptive fields in a single channel - vertical direction. More...

size_t	output_width
	Number of receptive fields in a single channel - horizontal direction. More...

size_t	output_depth
	Number of filters = number of output channels. More...

size_t	batch_size
	Size (length) of (mini)batch. More...

LayerTypes	layer_type
	Type of the layer. More...

std::string	layer_name
	Name (identifier of the type) of the layer. More...

mic::types::MatrixArray< eT >	s
	States - contains input [x] and output [y] matrices. More...

mic::types::MatrixArray< eT >	g
	Gradients - contains input [x] and output [y] matrices. More...

mic::types::MatrixArray< eT >	p
	Parameters - parameters of the layer, to be used by the derived classes. More...

mic::types::MatrixArray< eT >	m
	Memory - a list of temporal parameters, to be used by the derived classes. More...

mic::neural_nets::optimization::OptimizationArray < eT >	opt
	Array of optimization functions. More...

std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	x_activations
	Vector containing activations of input neurons - used in visualization. More...

std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	dx_activations
	Vector containing activations of gradients of inputs (dx) - used in visualization. More...

std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	y_activations
	Vector containing activations of output neurons - used in visualization. More...

std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	dy_activations
	Vector containing activations of gradients of outputs (dy) - used in visualization. More...

Private Member Functions
	ConvHebbian ()

Private Attributes
std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	w_activations
	Vector containing activations of neurons. More...

std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	o_activations

std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	o_reconstruction

bool	o_reconstruction_updated = false

std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	w_similarity

std::vector< std::shared_ptr < mic::types::Matrix< eT > > >	w_dissimilarity

Friends
template<typename tmp >
class	mic::mlnn::MultiLayerNeuralNetwork

Additional Inherited Members
Protected Member Functions inherited from mic::mlnn::Layer< eT >
	Layer ()

Detailed Description

template<typename eT = float>
class mic::mlnn::experimental::ConvHebbian< eT >

Class implementing a convolutional hebbian layer.

Template Parameters

eT	Template parameter denoting precision of variables (float for calculations/double for testing).

Definition at line 40 of file ConvHebbian.hpp.

Constructor & Destructor Documentation

template<typename eT = float>

mic::mlnn::experimental::ConvHebbian< eT >::ConvHebbian	(	size_t	input_width,
		size_t	input_height,
		size_t	input_depth,
		size_t	nfilters,
		size_t	filter_size,
		size_t	stride = `1`,
		std::string	name_ = `"ConvHebbian< eT >"`
	)

inline

Creates the convolutional hebbian layer.

Parameters

inputs_	Length of the input vector.
outputs_	Length of the output vector.
name_	Name of the layer.

Definition at line 49 of file ConvHebbian.hpp.

References mic::mlnn::experimental::ConvHebbian< eT >::nfilters, mic::mlnn::Layer< eT >::p, and mic::mlnn::experimental::ConvHebbian< eT >::W.

template<typename eT = float>

virtual mic::mlnn::experimental::ConvHebbian< eT >::~ConvHebbian ( )

inlinevirtual

Virtual destructor - empty.

Definition at line 79 of file ConvHebbian.hpp.

template<typename eT = float>

mic::mlnn::experimental::ConvHebbian< eT >::ConvHebbian ( )

inlineprivate

Private constructor, used only during the serialization.

Definition at line 357 of file ConvHebbian.hpp.

Member Function Documentation

template<typename eT = float>

void mic::mlnn::experimental::ConvHebbian< eT >::backward ( )

inlinevirtual

Backward pass.

Implements mic::mlnn::Layer< eT >.

Definition at line 114 of file ConvHebbian.hpp.

template<typename eT = float>

void mic::mlnn::experimental::ConvHebbian< eT >::forward ( bool test_ = false )

inlinevirtual

Forward pass.

Parameters

test_ It is set to true in test mode (network verification).

Implements mic::mlnn::Layer< eT >.

Definition at line 85 of file ConvHebbian.hpp.

References mic::mlnn::experimental::ConvHebbian< eT >::filter_size, mic::mlnn::Layer< eT >::input_width, mic::mlnn::experimental::ConvHebbian< eT >::o_reconstruction_updated, mic::mlnn::Layer< eT >::output_height, mic::mlnn::Layer< eT >::output_width, mic::mlnn::Layer< eT >::p, mic::mlnn::Layer< eT >::s, mic::mlnn::experimental::ConvHebbian< eT >::stride, mic::mlnn::experimental::ConvHebbian< eT >::W, and mic::mlnn::experimental::ConvHebbian< eT >::x2col.

template<typename eT = float>

std::vector< std::shared_ptr <mic::types::Matrix<eT> > >& mic::mlnn::experimental::ConvHebbian< eT >::getOutputActivations ( )

inlinevirtual

Returns activations of weights.

Reimplemented from mic::mlnn::Layer< eT >.

Definition at line 132 of file ConvHebbian.hpp.

References mic::mlnn::Layer< eT >::lazyAllocateMatrixVector(), mic::mlnn::experimental::ConvHebbian< eT >::nfilters, mic::mlnn::experimental::ConvHebbian< eT >::o_activations, mic::mlnn::Layer< eT >::output_height, mic::mlnn::Layer< eT >::output_width, mic::mlnn::Layer< eT >::s, and mic::mlnn::experimental::ConvHebbian< eT >::W.

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template<typename eT = float>

std::vector< std::shared_ptr <mic::types::Matrix<eT> > >& mic::mlnn::experimental::ConvHebbian< eT >::getOutputReconstruction ( )

inline

Returns reconstruction from feature maps and filters

Definition at line 157 of file ConvHebbian.hpp.

References mic::mlnn::experimental::ConvHebbian< eT >::conv2col, mic::mlnn::experimental::ConvHebbian< eT >::filter_size, mic::mlnn::Layer< eT >::input_height, mic::mlnn::Layer< eT >::input_width, mic::mlnn::Layer< eT >::lazyAllocateMatrixVector(), mic::mlnn::experimental::ConvHebbian< eT >::nfilters, mic::mlnn::experimental::ConvHebbian< eT >::o_reconstruction, mic::mlnn::experimental::ConvHebbian< eT >::o_reconstruction_updated, mic::mlnn::Layer< eT >::output_height, mic::mlnn::Layer< eT >::output_width, mic::mlnn::Layer< eT >::p, mic::mlnn::Layer< eT >::s, and mic::mlnn::experimental::ConvHebbian< eT >::stride.

Referenced by mic::mlnn::experimental::ConvHebbian< eT >::getOutputReconstructionError().

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template<typename eT = float>

eT mic::mlnn::experimental::ConvHebbian< eT >::getOutputReconstructionError ( )

inline

getOutputReconstructionError

Returns: Squared reconstruction error

If the reconstruction hasn't been updated, will call getOutputReconstruction(). To avoid computing the reconstruction twice, remember to call getOutputReconstruction() first if you need it.

Definition at line 202 of file ConvHebbian.hpp.

References mic::mlnn::experimental::ConvHebbian< eT >::getOutputReconstruction(), mic::mlnn::experimental::ConvHebbian< eT >::o_reconstruction, mic::mlnn::experimental::ConvHebbian< eT >::o_reconstruction_updated, and mic::mlnn::Layer< eT >::s.

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template<typename eT = float>

std::vector< std::shared_ptr <mic::types::Matrix<eT> > >& mic::mlnn::experimental::ConvHebbian< eT >::getWeightActivations ( )

inline

Returns activations of weights.

Definition at line 218 of file ConvHebbian.hpp.

References mic::mlnn::experimental::ConvHebbian< eT >::filter_size, mic::mlnn::Layer< eT >::lazyAllocateMatrixVector(), mic::mlnn::experimental::ConvHebbian< eT >::nfilters, mic::mlnn::Layer< eT >::p, mic::mlnn::experimental::ConvHebbian< eT >::W, and mic::mlnn::experimental::ConvHebbian< eT >::w_activations.

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template<typename eT = float>

std::vector< std::shared_ptr <mic::types::Matrix<eT> > >& mic::mlnn::experimental::ConvHebbian< eT >::getWeightDissimilarity ( )

inline

Returns dissimilarity of filters.

Definition at line 281 of file ConvHebbian.hpp.

References mic::mlnn::Layer< eT >::lazyAllocateMatrixVector(), mic::mlnn::experimental::ConvHebbian< eT >::nfilters, mic::mlnn::Layer< eT >::p, mic::mlnn::experimental::ConvHebbian< eT >::W, and mic::mlnn::experimental::ConvHebbian< eT >::w_dissimilarity.

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template<typename eT = float>

std::vector< std::shared_ptr <mic::types::Matrix<eT> > >& mic::mlnn::experimental::ConvHebbian< eT >::getWeightSimilarity ( bool fillDiagonal = false )

inline

Returns cosine similarity matrix of filters.

Give only positive similarities above the diagonal, and negative ones below, else 0.

Parameters

fillDiagonal Fill the diagonal with alternating 1,-1 to 'calibrate' the visualization.

Definition at line 244 of file ConvHebbian.hpp.

References mic::mlnn::Layer< eT >::lazyAllocateMatrixVector(), mic::mlnn::experimental::ConvHebbian< eT >::nfilters, mic::mlnn::Layer< eT >::p, mic::mlnn::experimental::ConvHebbian< eT >::W, and mic::mlnn::experimental::ConvHebbian< eT >::w_similarity.

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template<typename eT = float>

void mic::mlnn::experimental::ConvHebbian< eT >::update	(	eT	alpha_,
		eT	decay_ = `0.0f`
	)

inlinevirtual

Applies the gradient update, using the selected hebbian rule.

Parameters

alpha_	Learning rate - passed to the optimization functions of all layers.
decay_	Weight decay rate (determining that the "unused/unupdated" weights will decay to 0) (DEFAULT=0.0 - no decay).

Implements mic::mlnn::Layer< eT >.

Definition at line 123 of file ConvHebbian.hpp.

References mic::mlnn::Layer< eT >::opt, mic::mlnn::Layer< eT >::p, mic::mlnn::Layer< eT >::s, and mic::mlnn::experimental::ConvHebbian< eT >::x2col.