Normalizes the (non-negative) input by dividing by the overall sum. More...

#include <shark/Models/LinearNorm.h>

Inheritance diagram for shark::LinearNorm:

Public Member Functions
SHARK_EXPORT_SYMBOL	LinearNorm ()

SHARK_EXPORT_SYMBOL	LinearNorm (std::size_t inputSize)

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

RealVector	parameterVector () const
	Return the parameter vector. More...

void	setParameterVector (RealVector const &newParameters)
	Set the parameter vector. More...

std::size_t	inputSize () const

std::size_t	outputSize () const

std::size_t	numberOfParameters () const
	Return the number of parameters. More...

void	setStructure (std::size_t inputDimension)

boost::shared_ptr< State >	createState () const
	Creates an internal state of the model. More...

SHARK_EXPORT_SYMBOL void	eval (BatchInputType const &patterns, BatchOutputType &output) const
	Standard interface for evaluating the response of the model to a batch of patterns. More...

SHARK_EXPORT_SYMBOL void	eval (BatchInputType const &patterns, BatchOutputType &output, State &state) const
	Standard interface for evaluating the response of the model to a batch of patterns. More...

void	weightedParameterDerivative (BatchInputType const &patterns, BatchOutputType const &coefficients, State const &state, RealVector &gradient) const
	calculates the weighted sum of derivatives w.r.t the parameters. More...

SHARK_EXPORT_SYMBOL void	weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, BatchOutputType &gradient) const

SHARK_EXPORT_SYMBOL void	read (InArchive &archive)
	From ISerializable, reads a model from an archive. More...

SHARK_EXPORT_SYMBOL void	write (OutArchive &archive) const
	From ISerializable, writes a model to an archive. More...

Public Member Functions inherited from shark::AbstractModel< RealVector, RealVector >
	AbstractModel ()

virtual	~AbstractModel ()

const Features &	features () const

virtual void	updateFeatures ()

bool	hasFirstParameterDerivative () const
	Returns true when the first parameter derivative is implemented. More...

bool	hasSecondParameterDerivative () const
	Returns true when the second parameter derivative is implemented. More...

bool	hasFirstInputDerivative () const
	Returns true when the first input derivative is implemented. More...

bool	hasSecondInputDerivative () const
	Returns true when the second parameter derivative is implemented. More...

bool	isSequential () const

virtual void	eval (InputType const &pattern, OutputType &output) const
	Standard interface for evaluating the response of the model to a single pattern. More...

Data< OutputType >	operator() (Data< InputType > const &patterns) const
	Model evaluation as an operator for a whole dataset. This is a convenience function. More...

OutputType	operator() (InputType const &pattern) const
	Model evaluation as an operator for a single pattern. This is a convenience function. More...

BatchOutputType	operator() (BatchInputType const &patterns) const
	Model evaluation as an operator for a single pattern. This is a convenience function. More...

virtual void	weightedParameterDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, Batch< RealMatrix >::type const &errorHessian, State const &state, RealVector &derivative, RealMatrix &hessian) const
	calculates the weighted sum of derivatives w.r.t the parameters More...

virtual void	weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, BatchInputType &derivative) const
	calculates the weighted sum of derivatives w.r.t the inputs More...

virtual void	weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, typename Batch< RealMatrix >::type const &errorHessian, State const &state, RealMatrix &derivative, Batch< RealMatrix >::type &hessian) const
	calculates the weighted sum of derivatives w.r.t the inputs More...

virtual void	weightedDerivatives (BatchInputType const &patterns, BatchOutputType const &coefficients, State const &state, RealVector &parameterDerivative, BatchInputType &inputDerivative) const
	calculates weighted input and parameter derivative at the same time More...

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

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

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 Attributes
std::size_t	m_inputSize

Protected Attributes inherited from shark::AbstractModel< RealVector, RealVector >
Features	m_features

Additional Inherited Members
Public Types inherited from shark::AbstractModel< RealVector, RealVector >
enum	Feature

typedef RealVector	InputType
	Defines the input type of the model. More...

typedef RealVector	OutputType
	Defines the output type of the model. More...

typedef Batch< InputType >::type	BatchInputType
	defines the batch type of the input type. More...

typedef Batch< OutputType >::type	BatchOutputType
	defines the batch type of the output type More...

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Detailed Description

Normalizes the (non-negative) input by dividing by the overall sum.

Definition at line 37 of file LinearNorm.h.

Constructor & Destructor Documentation

◆ LinearNorm() [1/2]

SHARK_EXPORT_SYMBOL shark::LinearNorm::LinearNorm ( )

◆ LinearNorm() [2/2]

SHARK_EXPORT_SYMBOL shark::LinearNorm::LinearNorm ( std::size_t inputSize )

Member Function Documentation

◆ createState()

boost::shared_ptr<State> shark::LinearNorm::createState ( ) const

inlinevirtual

Creates an internal state of the model.

The state is needed when the derivatives are to be calculated. Eval can store a state which is then reused to speed up the calculations of the derivatives. This also allows eval to be evaluated in parallel!

Reimplemented from shark::AbstractModel< RealVector, RealVector >.

Definition at line 74 of file LinearNorm.h.

References eval(), and SHARK_EXPORT_SYMBOL.

◆ eval() [1/2]

SHARK_EXPORT_SYMBOL void shark::LinearNorm::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	outputs
	)		const

virtual

Standard interface for evaluating the response of the model to a batch of patterns.

Parameters

patterns	the inputs of the model
outputs	the predictions or response of the model to every pattern

Reimplemented from shark::AbstractModel< RealVector, RealVector >.

Referenced by createState().

◆ eval() [2/2]

SHARK_EXPORT_SYMBOL void shark::LinearNorm::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	outputs,
		State &	state
	)		const

virtual

Standard interface for evaluating the response of the model to a batch of patterns.

Parameters

patterns	the inputs of the model
outputs	the predictions or response of the model to every pattern
state	intermediate results stored by eval which can be reused for derivative computation.

Implements shark::AbstractModel< RealVector, RealVector >.

◆ inputSize()

std::size_t shark::LinearNorm::inputSize ( ) const

inline

Definition at line 60 of file LinearNorm.h.

References m_inputSize.

◆ name()

std::string shark::LinearNorm::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 52 of file LinearNorm.h.

◆ numberOfParameters()

std::size_t shark::LinearNorm::numberOfParameters ( ) const

inlinevirtual

Return the number of parameters.

Reimplemented from shark::IParameterizable.

Definition at line 66 of file LinearNorm.h.

◆ outputSize()

std::size_t shark::LinearNorm::outputSize ( ) const

inline

Definition at line 63 of file LinearNorm.h.

References m_inputSize.

◆ parameterVector()

RealVector shark::LinearNorm::parameterVector ( ) const

inlinevirtual

Return the parameter vector.

Reimplemented from shark::IParameterizable.

Definition at line 55 of file LinearNorm.h.

◆ read()

SHARK_EXPORT_SYMBOL void shark::LinearNorm::read ( InArchive & archive )

virtual

From ISerializable, reads a model from an archive.

Reimplemented from shark::AbstractModel< RealVector, RealVector >.

Referenced by weightedParameterDerivative().

◆ setParameterVector()

void shark::LinearNorm::setParameterVector ( RealVector const & newParameters )

inlinevirtual

Set the parameter vector.

Reimplemented from shark::IParameterizable.

Definition at line 58 of file LinearNorm.h.

◆ setStructure()

void shark::LinearNorm::setStructure ( std::size_t inputDimension )

inline

Definition at line 70 of file LinearNorm.h.

References shark::inputDimension(), and m_inputSize.

◆ weightedInputDerivative()

SHARK_EXPORT_SYMBOL void shark::LinearNorm::weightedInputDerivative	(	BatchInputType const &	pattern,
		BatchOutputType const &	coefficients,
		State const &	state,
		BatchOutputType &	gradient
	)		const

Referenced by weightedParameterDerivative().

◆ weightedParameterDerivative()

void shark::LinearNorm::weightedParameterDerivative	(	BatchInputType const &	pattern,
		BatchOutputType const &	coefficients,
		State const &	state,
		RealVector &	derivative
	)		const

inlinevirtual

calculates the weighted sum of derivatives w.r.t the parameters.

Parameters

pattern	the patterns to evaluate
coefficients	the coefficients which are used to calculate the weighted sum for every pattern
state	intermediate results stored by eval to speed up calculations of the derivatives
derivative	the calculated derivative as sum over all derivates of all patterns

Reimplemented from shark::AbstractModel< RealVector, RealVector >.

Definition at line 82 of file LinearNorm.h.

References read(), SHARK_EXPORT_SYMBOL, SIZE_CHECK, weightedInputDerivative(), and write().

◆ write()

SHARK_EXPORT_SYMBOL void shark::LinearNorm::write ( OutArchive & archive ) const

virtual

From ISerializable, writes a model to an archive.

Reimplemented from shark::AbstractModel< RealVector, RealVector >.

Referenced by weightedParameterDerivative().

Member Data Documentation

◆ m_inputSize

std::size_t shark::LinearNorm::m_inputSize

protected

Definition at line 99 of file LinearNorm.h.

Referenced by inputSize(), outputSize(), and setStructure().

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

include/shark/Models/LinearNorm.h

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ LinearNorm() [1/2]

◆ LinearNorm() [2/2]

Member Function Documentation

◆ createState()

◆ eval() [1/2]

◆ eval() [2/2]

◆ inputSize()

◆ name()

◆ numberOfParameters()

◆ outputSize()

◆ parameterVector()

◆ read()

◆ setParameterVector()

◆ setStructure()

◆ weightedInputDerivative()

◆ weightedParameterDerivative()

◆ write()

Member Data Documentation

◆ m_inputSize