Standard steepest descent. More...

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

Inheritance diagram for shark::SteepestDescent< SearchPointType >:

Public Types
typedef AbstractObjectiveFunction< SearchPointType, double >	ObjectiveFunctionType

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

typedef PointType	SearchPointType

typedef double	ResultType

typedef SingleObjectiveResultSet< PointType >	SolutionType

typedef AbstractObjectiveFunction< PointType, ResultType >	ObjectiveFunctionType

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Public Member Functions
	SteepestDescent ()

std::string	name () const
	From INameable: return the class name.

void	init (ObjectiveFunctionType const &objectiveFunction, SearchPointType const &startingPoint)

double	learningRate () const
	get learning rate

void	setLearningRate (double learningRate)
	set learning rate

double	momentum () const
	get momentum parameter

void	setMomentum (double momentum)
	set momentum parameter

void	step (ObjectiveFunctionType const &objectiveFunction)
	updates searchdirection and then does simple gradient descent

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

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

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

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.

virtual void	init (ObjectiveFunctionType const &function, SearchPointType const &startingPoint)=0
	initializes the optimizer using a predefined starting point

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

Public Member Functions inherited from shark::AbstractOptimizer< PointType, double, SingleObjectiveResultSet< PointType > >
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.

virtual void	step (ObjectiveFunctionType const &function)=0
	Carry out one step of the optimizer for the supplied objective function.

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

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

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

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

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Additional Inherited Members
Protected Member Functions inherited from shark::AbstractOptimizer< PointType, double, SingleObjectiveResultSet< PointType > >
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.

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

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

Detailed Description

template<class SearchPointType = RealVector>
class shark::SteepestDescent< SearchPointType >

Standard steepest descent.

Definition at line 44 of file SteepestDescent.h.

Member Typedef Documentation

◆ ObjectiveFunctionType

template<class SearchPointType = RealVector>

typedef AbstractObjectiveFunction<SearchPointType,double> shark::SteepestDescent< SearchPointType >::ObjectiveFunctionType

Definition at line 47 of file SteepestDescent.h.

Constructor & Destructor Documentation

◆ SteepestDescent()

template<class SearchPointType = RealVector>

shark::SteepestDescent< SearchPointType >::SteepestDescent ( )

inline

Definition at line 48 of file SteepestDescent.h.

References shark::AbstractOptimizer< PointType, double, SingleObjectiveResultSet< PointType > >::m_features, and shark::AbstractOptimizer< PointType, double, SingleObjectiveResultSet< PointType > >::REQUIRES_FIRST_DERIVATIVE.

Member Function Documentation

◆ init()

template<class SearchPointType = RealVector>

void shark::SteepestDescent< SearchPointType >::init	(	ObjectiveFunctionType const &	objectiveFunction,
		SearchPointType const &	startingPoint
	)

inline

Definition at line 59 of file SteepestDescent.h.

References shark::AbstractOptimizer< PointType, double, SingleObjectiveResultSet< PointType > >::checkFeatures(), shark::AbstractObjectiveFunction< PointType, ResultT >::evalDerivative(), shark::AbstractSingleObjectiveOptimizer< PointType >::m_best, shark::AbstractObjectiveFunction< PointType, ResultT >::numberOfVariables(), shark::ResultSet< SearchPointT, ResultT >::point, SHARK_RUNTIME_CHECK, and shark::ResultSet< SearchPointT, ResultT >::value.

Referenced by main(), and trainRBM().

◆ learningRate()

template<class SearchPointType = RealVector>

double shark::SteepestDescent< SearchPointType >::learningRate ( ) const

inline

get learning rate

Definition at line 73 of file SteepestDescent.h.

Referenced by shark::SteepestDescent< SearchPointType >::setLearningRate().

◆ momentum()

template<class SearchPointType = RealVector>

double shark::SteepestDescent< SearchPointType >::momentum ( ) const

inline

get momentum parameter

Definition at line 87 of file SteepestDescent.h.

Referenced by shark::SteepestDescent< SearchPointType >::setMomentum().

◆ name()

template<class SearchPointType = RealVector>

std::string shark::SteepestDescent< SearchPointType >::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 56 of file SteepestDescent.h.

◆ read()

template<class SearchPointType = RealVector>

virtual void shark::SteepestDescent< SearchPointType >::read ( InArchive & archive )

inlinevirtual

Read the component from the supplied archive.

Parameters

[in,out] archive The archive to read from.

Reimplemented from shark::ISerializable.

Definition at line 105 of file SteepestDescent.h.

◆ setLearningRate()

template<class SearchPointType = RealVector>

void shark::SteepestDescent< SearchPointType >::setLearningRate ( double learningRate )

inline

set learning rate

Definition at line 80 of file SteepestDescent.h.

References shark::SteepestDescent< SearchPointType >::learningRate().

Referenced by main(), and trainRBM().

◆ setMomentum()

template<class SearchPointType = RealVector>

void shark::SteepestDescent< SearchPointType >::setMomentum ( double momentum )

inline

set momentum parameter

Definition at line 94 of file SteepestDescent.h.

References shark::SteepestDescent< SearchPointType >::momentum().

Referenced by main().

◆ step()

template<class SearchPointType = RealVector>

void shark::SteepestDescent< SearchPointType >::step ( ObjectiveFunctionType const & objectiveFunction )

inline

updates searchdirection and then does simple gradient descent

Definition at line 100 of file SteepestDescent.h.

References shark::AbstractObjectiveFunction< PointType, ResultT >::evalDerivative(), shark::AbstractSingleObjectiveOptimizer< PointType >::m_best, shark::ResultSet< SearchPointT, ResultT >::point, and shark::ResultSet< SearchPointT, ResultT >::value.

Referenced by main(), and trainRBM().

◆ write()

template<class SearchPointType = RealVector>

virtual void shark::SteepestDescent< SearchPointType >::write ( OutArchive & archive ) const

inlinevirtual

Write the component to the supplied archive.

Parameters

[in,out] archive The archive to write to.

Reimplemented from shark::ISerializable.

Definition at line 112 of file SteepestDescent.h.

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

include/shark/Algorithms/GradientDescent/SteepestDescent.h

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ ObjectiveFunctionType

Constructor & Destructor Documentation

◆ SteepestDescent()

Member Function Documentation

◆ init()

◆ learningRate()

◆ momentum()

◆ name()

◆ read()

◆ setLearningRate()

◆ setMomentum()

◆ step()

◆ write()