A subclass of PerceptronModel that differs only in the way that the ComputeStepSize method is implemented. More...

#include <mira-style-model.H>

Inheritance diagram for reranker::MiraStyleModel:

Public Member Functions
	MiraStyleModel ()

	MiraStyleModel (const string &name)

	MiraStyleModel (const string &name, KernelFunction *kernel_fn)

	MiraStyleModel (const string &name, KernelFunction kernel_fn, Symbols symbols)

virtual void	RegisterInitializers (Initializers &initializers)
	Registers one additional variable that may be initialized when this object is constructed via Factory::CreateOrDie. More...

void	set_mira_clip (double mira_clip)
	Sets the maximum value for a step size computed by ComputeStepSize. More...

virtual double	ComputeStepSize (const unordered_set< int > &gold_features, const unordered_set< int > &best_scoring_features, const CandidateSet &example)
	Computes the step size for the next update, and, as a side effect, caches this value in step_size_. More...

Public Member Functions inherited from reranker::PerceptronModel
	PerceptronModel ()
	Constructs a new instance with the empty string for its name and the DotProduct kernel function. More...

	PerceptronModel (const string &name)
	Constructs a new perceptron model with a DotProduct kernel function. More...

	PerceptronModel (const string &name, KernelFunction *kernel_fn)
	Constructs a new perceptron model with the specified kernel function. More...

	PerceptronModel (const string &name, KernelFunction kernel_fn, Symbols symbols)
	Constructs a new perceptron model with the specified kernel function and symbol table. More...

virtual	~PerceptronModel ()
	Destroys this perceptron model and all its data members. More...

virtual const string &	model_spec () const
	Returns the spec string for constructing a default instance of this model so it may be properly de-serialized by its ModelProtoReader. More...

virtual const string &	proto_reader_spec () const
	Returns the spec string for contructing an instance of a ModelProtoReader capable of de-serializing this Model implementation. More...

virtual const string &	proto_writer_spec () const
	Returns the spec string for contructing an instance of a ModelProtoWriter capable of serializing this Model implementation. More...

virtual int	best_model_epoch () const
	Returns the epoch of the best models seen so far during training. More...

virtual void	Init (const Environment *env, const string &arg)
	Initializes this instance. More...

virtual bool	NeedToKeepTraining ()
	Returns whether more training epochs are required for this model. More...

virtual void	Train (CandidateSetIterator &examples, CandidateSetIterator &development_test)
	Trains this model on a collection of training examples, where each training example is a set of candidates. More...

virtual void	NewEpoch ()

virtual void	EndOfEpoch ()

virtual void	TrainOneEpoch (CandidateSetIterator &examples)
	Trains this model for one epoch, i.e., a single pass through the specified set of training examples. More...

virtual void	TrainOnExample (CandidateSet &example)
	Trains this model on the specified training example. More...

virtual bool	NeedToUpdate (CandidateSet &example)
	Indicates whether the current model needs to be updated; the implementation here simply returns true if the best-scoring candidate is not equal to the gold or reference candidate. More...

virtual void	Update (CandidateSet &example)
	Updates the current model based on the specified set of candidates. More...

virtual double	Evaluate (CandidateSetIterator &development_test)
	Evaluates this model on the specified set of held-out development test data. More...

virtual void	ScoreCandidates (CandidateSet &candidates, bool training)
	Scores the specified set of candidates according to either the raw or averaged version of this perceptron model, keeping track of which candidate has the highest score and which candidate has the lowest loss with the best score. More...

virtual double	ScoreCandidate (Candidate &candidate, bool training)
	Scores a candidate according to either the raw or averaged version of this perceptron model. More...

virtual void	CompactifyFeatureUids ()
	Renumbers the potentially sparse feature uid’s so that they occupy the interval `[0,n-1]` densely, for `n` non-zero features in use by this model. More...

void	set_max_epochs_in_decline (int max_epochs_in_decline)
	Sets the maximum number of training epochs to keep training after the model starts to degrade (i.e., has more errors than the best model so far). More...

virtual const TrainingVectorSet &	models () const
	Returns the set of models and statistics used by this PerceptronModel instance. More...

Public Member Functions inherited from reranker::Model
	Model ()
	Constructs a new instance with the empty string for its name and a NULL kernel function. More...

	Model (const string &name)
	Constructs a new instance with a NULL kernel function. More...

	Model (const string &name, KernelFunction *kernel_fn)
	Constructs a new instance with the specified kernel function. More...

	Model (const string &name, KernelFunction kernel_fn, Symbols symbols)
	Constructs a new instance with the specified kernel function and symbol table. More...

virtual	~Model ()
	Destroys this model and its associated kernel function. More...

const string &	name () const
	Returns the unique name for this model instance. More...

Symbols *	symbols () const
	Returns the symbol table for this model. More...

const Time &	time () const
	Returns the current training time of this model: number of epochs, number of time steps in the current epoch and total number of time steps (which is equal to the total number of training examples seen). More...

int	num_updates () const
	Returns the number of updates made by this model. More...

const vector< int > &	num_training_errors_per_epoch ()
	Returns the number of training errors made for each epoch. More...

int	num_training_errors () const
	Returns the number of training errors made by this model. More...

int	min_epochs () const
	Returns the minimum number of epochs to train. More...

int	max_epochs () const
	Returns the maximum number of epochs to train. More...

const vector< double > &	loss_per_epoch ()
	Returns the loss per epoch for epoch of training that was evaluated. More...

virtual shared_ptr < Candidate::Comparator >	score_comparator ()
	Returns a pointer to the score comparator used by this model. More...

virtual shared_ptr < Candidate::Comparator >	gold_comparator ()
	Returns a pointer to the gold comparator used by this model. More...

virtual void	set_min_epochs (int min_epochs)
	Sets the minimum number of epochs to train. More...

virtual void	set_max_epochs (int max_epochs)
	Sets the maximum number of epochs to train. More...

virtual void	set_end_of_epoch_hook (Hook *end_of_epoch_hook)

virtual bool	use_weighted_loss ()

virtual void	set_use_weighted_loss (bool use_weighted_loss)

virtual void	set_symbols (Symbols *symbols)
	Sets the Symbols instance for this Model to be the specified instance. More...

Public Member Functions inherited from reranker::FactoryConstructible
virtual	~FactoryConstructible ()

Additional Inherited Members
Protected Member Functions inherited from reranker::PerceptronModel
void	SetDefaultObjects ()

virtual void	ComputeFeaturesToUpdate (const CandidateSet &example, unordered_set< int > &gold_features_to_update, unordered_set< int > &best_scoring_features_to_update) const
	Computes the features to be updated for the gold candidate and the best-scoring candidate. More...

Protected Member Functions inherited from reranker::Model
void	set_name (const string &name)
	Sets the name of this Model instance. More...

void	set_kernel_fn (KernelFunction *kernel_fn)
	Sets the kernel function for this model. More...

void	set_score_comparator (shared_ptr< Candidate::Comparator > score_comparator)

void	set_gold_comparator (shared_ptr< Candidate::Comparator > gold_comparator)

void	SetDefaultObjects ()

void	SetDefaultComparators ()

void	SetDefaultCandidateSetScorer ()

shared_ptr< Candidate::Comparator >	GetComparator (const string &spec) const

shared_ptr< CandidateSet::Scorer >	GetCandidateSetScorer (const string &spec) const

shared_ptr< UpdatePredicate >	GetUpdatePredicate (const string &spec) const

shared_ptr< Updater >	GetUpdater (const string &spec) const

virtual void	CheckNumberOfTokens (const string &arg, const vector< string > &tokens, size_t min_expected_number, size_t max_expected_number, const string &class_name) const
	A helper method for implementing the Init method: throws a std::runtime_error if the number of tokens in the argument string is not the expected number. More...

Protected Attributes inherited from reranker::PerceptronModel
TrainingVectorSet	models_
	The feature vectors representing this model. More...

TrainingVectorSet	best_models_
	The best models seen so far during training, according to evaluation on the held-out development test data. More...

int	best_model_epoch_
	The epoch of the best models seen so far during training. More...

int	max_epochs_in_decline_
	The maximum number of training epochs to keep training after the model starts to degrade (i.e., has more errors than the best model so far). More...

int	num_epochs_in_decline_
	The current number of training epochs in which the model has been degrading in development set performance (i.e., has been having more errors than best model so far). More...

double	step_size_
	The last value computed by the ComputeStepSize method. More...

string	model_spec_

Protected Attributes inherited from reranker::Model
string	name_
	This model’s unique name. More...

Time	time_
	The tiny object that holds the "training time" for this model (epoch, index and absolute time index). More...

KernelFunction *	kernel_fn_
	Yes, this is an interface, but we add the kernel function as a data member. More...

Symbols *	symbols_
	The symbol table for this model (may be NULL). More...

shared_ptr< Candidate::Comparator >	score_comparator_
	A comparator to provide an ordering for candidates based on score when scoring all candidates in a set. More...

shared_ptr< Candidate::Comparator >	gold_comparator_
	A comparator to provide an ordering for candidates to find the gold candidate in a set. More...

shared_ptr< CandidateSet::Scorer >	candidate_set_scorer_
	A scorer for CandidateSet instances. More...

shared_ptr< UpdatePredicate >	update_predicate_
	The update predicate for this model. More...

shared_ptr< Updater >	updater_
	The updater for this model. More...

vector< double >	loss_per_epoch_
	The average loss per epoch. More...

vector< int >	num_testing_errors_per_epoch_
	The number of testing errors made on held-out development test data for each epoch. More...

vector< int >	num_training_errors_per_epoch_
	The number of errors made on training examples during each epoch. More...

int	num_training_errors_
	The number of errors made on training examples. More...

int	num_updates_
	The number of times an update was performed on this model during training. More...

int	min_epochs_
	The minimum number of training epochs to execute. More...

int	max_epochs_
	The maximum number of training epochs to execute. More...

Hook *	end_of_epoch_hook_
	A hook to be performed at the end of every epoch. More...

bool	use_weighted_loss_
	Indicates whether this model should weight each candidate’s loss by the value returned by CandidateSet::loss_weight. More...

Static Protected Attributes inherited from reranker::PerceptronModel
static string	proto_reader_spec_
	A string that specifies to construct a PerceptronModelProtoReader, which is capable of de-serializing an instance of this class. More...

static string	proto_writer_spec_
	A string that specifies to construct a PerceptronModelProtoWriter, which is capable of serializing an instance of this class. More...

Detailed Description

A subclass of PerceptronModel that differs only in the way that the ComputeStepSize method is implemented.

The overridden definition here provides a “MIRA-style” update, where the step size is related to the difference in losses and scores of the gold and best-scoring candidates.

Definition at line 78 of file mira-style-model.H.

Constructor & Destructor Documentation

reranker::MiraStyleModel::MiraStyleModel ( )

inline

Definition at line 80 of file mira-style-model.H.

reranker::MiraStyleModel::MiraStyleModel ( const string & name )

inline

Definition at line 81 of file mira-style-model.H.

reranker::MiraStyleModel::MiraStyleModel	(	const string &	name,
		KernelFunction *	kernel_fn
	)

inline

Definition at line 83 of file mira-style-model.H.

reranker::MiraStyleModel::MiraStyleModel	(	const string &	name,
		KernelFunction *	kernel_fn,
		Symbols *	symbols
	)

inline

Definition at line 86 of file mira-style-model.H.

Member Function Documentation

virtual double reranker::MiraStyleModel::ComputeStepSize	(	const unordered_set< int > &	gold_features,
		const unordered_set< int > &	best_scoring_features,
		const CandidateSet &	example
	)

inlinevirtual

Computes the step size for the next update, and, as a side effect, caches this value in step_size_.

The step size here is computed based on the loss and score difference between the best-scoring candidate and the gold candidate, to achieve a “MIRA-style” update.

Reimplemented from reranker::PerceptronModel.

Definition at line 125 of file mira-style-model.H.

virtual void reranker::MiraStyleModel::RegisterInitializers ( Initializers & initializers )

inlinevirtual

Registers one additional variable that may be initialized when this object is constructed via Factory::CreateOrDie.

The set of members includes all those handled by PerceptronModel::RegisterInitializers, as well as the following:

Variable name	Type	Required	Description	Default value
`mira_clip`	`double`	No	The maxmum value this model’s step size may attain.	0.1

Reimplemented from reranker::PerceptronModel.

Definition at line 112 of file mira-style-model.H.

void reranker::MiraStyleModel::set_mira_clip ( double mira_clip )

inline

Sets the maximum value for a step size computed by ComputeStepSize.

Definition at line 119 of file mira-style-model.H.

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

mira-style-model.H

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation