Layer::ConvolutionLayer Class Reference

#include <convolution.hpp>

Inheritance diagram for Layer::ConvolutionLayer:

Public Member Functions
	ConvolutionLayer (size_t nf, size_t ni, size_t nj, size_t p, size_t q, size_t mf)
	~ConvolutionLayer ()
void	init (Real mu, Real sigma)
Vector	feed_forward (Vector x) override
void	init_nabla () override
Vector	back_propagation (Vector e) override
void	update (Real eta) override
Public Member Functions inherited from Layer::Layer
	Layer (size_t n, size_t m)
	~Layer ()
size_t	get_input_size () const
size_t	get_output_size () const
Vector	get_output () const
virtual Vector	feed_forward (Vector x)=0
virtual void	init_nabla ()=0
virtual Vector	back_propagation (Vector e)=0
virtual void	update (Real eta)=0

Additional Inherited Members
Public Attributes inherited from Layer::Layer
string	name
size_t	n
size_t	m
Vector	x
Vector	y
Vector	d

Constructor & Destructor Documentation

ConvolutionLayer()

Layer::ConvolutionLayer::ConvolutionLayer	(	size_t	nf,
		size_t	ni,
		size_t	nj,
		size_t	p,
		size_t	q,
		size_t	mf
	)

~ConvolutionLayer()

Layer::ConvolutionLayer::~ConvolutionLayer

(

)

Member Function Documentation

back_propagation()

Vector Layer::ConvolutionLayer::back_propagation ( Vector  e )

overridevirtual

Apply back propagation algorithm on the delta output vector d. Used the input vector stored in x_in_ref during feedforward. Return a reference to the computed (and stored) input delta vector. Nabla vectors must be computed here.

Implements Layer::Layer.

feed_forward()

Vector Layer::ConvolutionLayer::feed_forward ( Vector  x )

overridevirtual

Apply the layer to the input vector x. Vectors x_in_ref and x_out must be updated in consequence. Return a reference to x_out.

Implements Layer::Layer.

init()

void Layer::ConvolutionLayer::init	(	Real	mu,
		Real	sigma
	)

init_nabla()

void Layer::ConvolutionLayer::init_nabla ( )

overridevirtual

Initialize nabla vectors which are used during gradient descent.

Implements Layer::Layer.

update()

void Layer::ConvolutionLayer::update ( Real  eta )

overridevirtual

Update layer parameters using gradient descent algorithm with learning rate eta.

Implements Layer::Layer.

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

• src/layers/convolution.hpp
• src/layers/convolution.cpp