Basis class for line search methods. More...

#include <shark/Algorithms/GradientDescent/AbstractLineSearchOptimizer.h>

Inheritance diagram for shark::AbstractLineSearchOptimizer:

Public Member Functions
SHARK_EXPORT_SYMBOL	AbstractLineSearchOptimizer ()

SHARK_EXPORT_SYMBOL void	init (ObjectiveFunctionType const &objectiveFunction, SearchPointType const &startingPoint)
	initializes the optimizer using a predefined starting point More...

SHARK_EXPORT_SYMBOL void	step (ObjectiveFunctionType const &objectiveFunction)
	Carry out one step of the optimizer for the supplied objective function. More...

SHARK_EXPORT_SYMBOL void	read (InArchive &archive)
	Read the component from the supplied archive. More...

SHARK_EXPORT_SYMBOL void	write (OutArchive &archive) const
	Write the component to the supplied archive. More...

LineSearch const &	lineSearch () const

LineSearch &	lineSearch ()

RealVector const &	derivative () const
	Returns the derivative at the current point. Can be used for stopping criteria. More...

Public Member Functions inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
std::size_t	numInitPoints () const
	By default most single objective optimizers only require a single point. More...

virtual void	init (ObjectiveFunctionType const &function, std::vector< SearchPointType > const &initPoints)
	Initialize the optimizer for the supplied objective function using a set of initialisation points. More...

virtual const SolutionType &	solution () const
	returns the current solution of the optimizer More...

Public Member Functions inherited from shark::AbstractOptimizer< RealVector, double, SingleObjectiveResultSet< RealVector > >
const Features &	features () const

virtual void	updateFeatures ()

bool	requiresValue () const

bool	requiresFirstDerivative () const

bool	requiresSecondDerivative () const

bool	canSolveConstrained () const

bool	requiresClosestFeasible () const

virtual	~AbstractOptimizer ()

virtual void	init (ObjectiveFunctionType const &function)
	Initialize the optimizer for the supplied objective function. More...

Public Member Functions inherited from shark::INameable
virtual	~INameable ()

virtual std::string	name () const
	returns the name of the object More...

Public Member Functions inherited from shark::ISerializable
virtual	~ISerializable ()
	Virtual d'tor. More...

void	load (InArchive &archive, unsigned int version)
	Versioned loading of components, calls read(...). More...

void	save (OutArchive &archive, unsigned int version) const
	Versioned storing of components, calls write(...). More...

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Protected Member Functions
virtual void	initModel ()=0
	Initializes the internal model. More...

virtual void	computeSearchDirection (ObjectiveFunctionType const &objectiveFunction)=0
	Updates the Model and computes the next search direction. More...

Protected Member Functions inherited from shark::AbstractOptimizer< RealVector, double, SingleObjectiveResultSet< RealVector > >
void	checkFeatures (ObjectiveFunctionType const &objectiveFunction)
	Convenience function that checks whether the features of the supplied objective function match with the required features of the optimizer. More...

Protected Attributes
LineSearch	m_linesearch
	used line search method. More...

std::size_t	m_dimension
	number of parameters More...

double	m_initialStepLength
	Initial step length to begin with the line search. More...

RealVector	m_derivative
	gradient of m_best.point More...

RealVector	m_searchDirection
	search direction of next step More...

RealVector	m_lastPoint
	previous point More...

RealVector	m_lastDerivative
	gradient of the previous point More...

double	m_lastValue
	value of the previous point More...

Protected Attributes inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
SolutionType	m_best
	Current solution of the optimizer. More...

Protected Attributes inherited from shark::AbstractOptimizer< RealVector, double, SingleObjectiveResultSet< RealVector > >
Features	m_features

Additional Inherited Members
Public Types inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
typedef base_type::SearchPointType	SearchPointType

typedef base_type::SolutionType	SolutionType

typedef base_type::ResultType	ResultType

typedef base_type::ObjectiveFunctionType	ObjectiveFunctionType

Public Types inherited from shark::AbstractOptimizer< RealVector, double, SingleObjectiveResultSet< RealVector > >
enum	Feature
	Models features that the optimizer requires from the objective function. More...

typedef RealVector	SearchPointType

typedef double	ResultType

typedef SingleObjectiveResultSet< RealVector >	SolutionType

typedef AbstractObjectiveFunction< RealVector, ResultType >	ObjectiveFunctionType

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Detailed Description

Basis class for line search methods.

Line Search optimizer find an iterative optimum by starting from some point, choosing a search direction and than performing a line search in that direction. To choose the search direction a local model of the function is often used. This class is a base class for all line search method which implement the general behaviour of line search methods. Derived classes only need to implement initModel() and computeSearchDirection() to initializee and update the model and find a new line search direction. The remaining functionality is implemented by the optimizer.

Also derived classes should specialise read() and write() methods for serialization if they have additional members as well as choose a name() for the optimizer.

Definition at line 55 of file AbstractLineSearchOptimizer.h.

Constructor & Destructor Documentation

◆ AbstractLineSearchOptimizer()

SHARK_EXPORT_SYMBOL shark::AbstractLineSearchOptimizer::AbstractLineSearchOptimizer ( )

Member Function Documentation

◆ computeSearchDirection()

virtual void shark::AbstractLineSearchOptimizer::computeSearchDirection ( ObjectiveFunctionType const & objectiveFunction )

protectedpure virtual

Updates the Model and computes the next search direction.

After a step was performed, this method is called to compute the next search direction. This usually involves updating the internal model using the new and old step information. Afterwards m_searchDirection should contain the next search direction.

Implemented in shark::LBFGS, shark::CG, and shark::BFGS.