Wrapper for training schemes based on (iterative) optimization. More...

#include <shark/Algorithms/Trainers/OptimizationTrainer.h>

Inheritance diagram for shark::OptimizationTrainer< Model, LabelTypeT >:

Public Types
typedef base_type::InputType	InputType

typedef Model::OutputType	OutputType

typedef base_type::LabelType	LabelType

typedef Model	ModelType

typedef ModelType::ParameterVectorType	ParameterVectorType

typedef AbstractSingleObjectiveOptimizer< ParameterVectorType >	OptimizerType

typedef AbstractLoss< LabelType, OutputType >	LossType

typedef AbstractStoppingCriterion< SingleObjectiveResultSet< ParameterVectorType > >	StoppingCriterionType

Public Types inherited from shark::AbstractTrainer< Model, LabelTypeT >
typedef Model	ModelType

typedef ModelType::InputType	InputType

typedef LabelTypeT	LabelType

typedef LabeledData< InputType, LabelType >	DatasetType

Public Member Functions
	OptimizationTrainer (LossType loss, OptimizerType optimizer, StoppingCriterionType *stoppingCriterion)

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

void	train (ModelType &model, LabeledData< InputType, LabelType > const &dataset)

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

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

Public Member Functions inherited from shark::AbstractTrainer< Model, LabelTypeT >
virtual void	train (ModelType &model, DatasetType const &dataset)=0
	Core of the Trainer interface.

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 ()

Protected Attributes
LossType *	mep_loss

OptimizerType *	mep_optimizer

StoppingCriterionType *	mep_stoppingCriterion

Detailed Description

template<class Model, class LabelTypeT = typename Model::OutputType>
class shark::OptimizationTrainer< Model, LabelTypeT >

Wrapper for training schemes based on (iterative) optimization.

: The OptimizationTrainer class is designed to allow for model training via iterative minimization of a loss function, such as in neural network "backpropagation" training.

Definition at line 58 of file OptimizationTrainer.h.

Member Typedef Documentation

◆ InputType

template<class Model , class LabelTypeT = typename Model::OutputType>

typedef base_type::InputType shark::OptimizationTrainer< Model, LabelTypeT >::InputType

Definition at line 63 of file OptimizationTrainer.h.

◆ LabelType

template<class Model , class LabelTypeT = typename Model::OutputType>

typedef base_type::LabelType shark::OptimizationTrainer< Model, LabelTypeT >::LabelType

Definition at line 65 of file OptimizationTrainer.h.

◆ LossType

template<class Model , class LabelTypeT = typename Model::OutputType>

typedef AbstractLoss< LabelType, OutputType > shark::OptimizationTrainer< Model, LabelTypeT >::LossType

Definition at line 70 of file OptimizationTrainer.h.

◆ ModelType

template<class Model , class LabelTypeT = typename Model::OutputType>

typedef Model shark::OptimizationTrainer< Model, LabelTypeT >::ModelType

Definition at line 66 of file OptimizationTrainer.h.

◆ OptimizerType

template<class Model , class LabelTypeT = typename Model::OutputType>

typedef AbstractSingleObjectiveOptimizer< ParameterVectorType > shark::OptimizationTrainer< Model, LabelTypeT >::OptimizerType

Definition at line 69 of file OptimizationTrainer.h.

◆ OutputType

template<class Model , class LabelTypeT = typename Model::OutputType>

typedef Model::OutputType shark::OptimizationTrainer< Model, LabelTypeT >::OutputType

Definition at line 64 of file OptimizationTrainer.h.

◆ ParameterVectorType

template<class Model , class LabelTypeT = typename Model::OutputType>

typedef ModelType::ParameterVectorType shark::OptimizationTrainer< Model, LabelTypeT >::ParameterVectorType

Definition at line 67 of file OptimizationTrainer.h.

◆ StoppingCriterionType

template<class Model , class LabelTypeT = typename Model::OutputType>

typedef AbstractStoppingCriterion<SingleObjectiveResultSet<ParameterVectorType> > shark::OptimizationTrainer< Model, LabelTypeT >::StoppingCriterionType

Definition at line 71 of file OptimizationTrainer.h.

Constructor & Destructor Documentation

◆ OptimizationTrainer()

template<class Model , class LabelTypeT = typename Model::OutputType>

shark::OptimizationTrainer< Model, LabelTypeT >::OptimizationTrainer	(	LossType *	loss,
		OptimizerType *	optimizer,
		StoppingCriterionType *	stoppingCriterion
	)

inline

Definition at line 73 of file OptimizationTrainer.h.

References SHARK_RUNTIME_CHECK.

Member Function Documentation

◆ name()

template<class Model , class LabelTypeT = typename Model::OutputType>

std::string shark::OptimizationTrainer< Model, LabelTypeT >::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 85 of file OptimizationTrainer.h.

References shark::OptimizationTrainer< Model, LabelTypeT >::mep_loss, shark::OptimizationTrainer< Model, LabelTypeT >::mep_optimizer, and shark::INameable::name().

◆ read()

template<class Model , class LabelTypeT = typename Model::OutputType>

void shark::OptimizationTrainer< Model, LabelTypeT >::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 104 of file OptimizationTrainer.h.

◆ train()

template<class Model , class LabelTypeT = typename Model::OutputType>

void shark::OptimizationTrainer< Model, LabelTypeT >::train	(	ModelType &	model,
		LabeledData< InputType, LabelType > const &	dataset
	)

inline

Definition at line 92 of file OptimizationTrainer.h.

References shark::ErrorFunction< SearchPointType >::init(), shark::AbstractSingleObjectiveOptimizer< PointType >::init(), shark::OptimizationTrainer< Model, LabelTypeT >::mep_loss, shark::OptimizationTrainer< Model, LabelTypeT >::mep_optimizer, shark::OptimizationTrainer< Model, LabelTypeT >::mep_stoppingCriterion, shark::ResultSet< SearchPointT, ResultT >::point, shark::AbstractStoppingCriterion< ResultSetT >::reset(), shark::AbstractSingleObjectiveOptimizer< PointType >::solution(), shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::step(), and shark::AbstractStoppingCriterion< ResultSetT >::stop().

Referenced by experiment().

◆ write()

template<class Model , class LabelTypeT = typename Model::OutputType>

void shark::OptimizationTrainer< Model, LabelTypeT >::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 107 of file OptimizationTrainer.h.

Member Data Documentation

◆ mep_loss

template<class Model , class LabelTypeT = typename Model::OutputType>

LossType* shark::OptimizationTrainer< Model, LabelTypeT >::mep_loss

protected

Definition at line 111 of file OptimizationTrainer.h.

Referenced by shark::OptimizationTrainer< Model, LabelTypeT >::name(), and shark::OptimizationTrainer< Model, LabelTypeT >::train().

◆ mep_optimizer

template<class Model , class LabelTypeT = typename Model::OutputType>

OptimizerType* shark::OptimizationTrainer< Model, LabelTypeT >::mep_optimizer

protected

Definition at line 112 of file OptimizationTrainer.h.

Referenced by shark::OptimizationTrainer< Model, LabelTypeT >::name(), and shark::OptimizationTrainer< Model, LabelTypeT >::train().

◆ mep_stoppingCriterion

template<class Model , class LabelTypeT = typename Model::OutputType>

StoppingCriterionType* shark::OptimizationTrainer< Model, LabelTypeT >::mep_stoppingCriterion

protected

Definition at line 113 of file OptimizationTrainer.h.

Referenced by shark::OptimizationTrainer< Model, LabelTypeT >::train().

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

include/shark/Algorithms/Trainers/OptimizationTrainer.h

Public Types

Public Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ InputType

◆ LabelType

◆ LossType

◆ ModelType

◆ OptimizerType

◆ OutputType

◆ ParameterVectorType

◆ StoppingCriterionType

Constructor & Destructor Documentation

◆ OptimizationTrainer()

Member Function Documentation

◆ name()

◆ read()

◆ train()

◆ write()

Member Data Documentation

◆ mep_loss

◆ mep_optimizer

◆ mep_stoppingCriterion