lmngram.h

强化学习算法（R-Learning）难得的珍贵资料

// Copyright (C) 2003 Darren Moore ([e-mail])
//                
// This file is part of Torch 3.
//
// All rights reserved.
// 
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions
// are met:
// 1. Redistributions of source code must retain the above copyright
//    notice, this list of conditions and the following disclaimer.
// 2. Redistributions in binary form must reproduce the above copyright
//    notice, this list of conditions and the following disclaimer in the
//    documentation and/or other materials provided with the distribution.
// 3. The name of the author may not be used to endorse or promote products
//    derived from this software without specific prior written permission.
// 
// THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
// OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
// IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
// NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
// THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

#ifndef LMNGRAM_INC
#define LMNGRAM_INC

#include "general.h"
#include "log_add.h"
#include "LMInteriorLevelWordList.h"
#include "Vocabulary.h"
#include "LMCache.h"

namespace Torch {


/**
    This class is the main class for N-gram language modelling.
    After language model entries have been added, lookups with full
    backoff can be performed.
      
    @author Darren Moore ([e-mail])
*/

class LMNGram
{
public:
    /// The order of the N-Gram
    int n ;
    Vocabulary *vocab ;
    
    /// The unigram probability entries, 1 for every vocab word.
    real *unigrams ;

    /// Points to the start of the language model tree structure.
    LMInteriorLevelWordList *next_level ;

    /// The cache used for fast LM lookup.
    LMCache *cache ;

    /* Constructors / destructor */

    /// Creates an empty N-Gram data structure. 'n_' is the N-gram order.
    LMNGram( int n_ , Vocabulary *vocab_ ) ;
    virtual ~LMNGram() ;

    /* Methods */

    /// Adds a new entry to the N-gram.
    /// 'order' is the order of the entry (ie. 2 for a bigram entry).
    /// The 'words' array needs to be in oldest-word-first order.
    ///   ([w1 w2 w3] for trigram entry).
    /// 'prob' is the log probability for the entry
    /// 'bo_wt' is the log back-off weight for the entry. If order is
    ///   equal to the LMNGram order (n), then 'bo_wt' is ignored.
    void addEntry( int order , int *words , real prob , real bo_wt=LOG_ZERO ) ;

    /// Finds the N-gram probability of a given word sequence, with full
    ///   backoff.
    /// 'order' is the number of words in the 'words' array.
    /// The ordering in 'words' is W3,W2,W1,W4 for a 4-gram query.
    ///   (ie. for the query : what is P(W4|W1,W2,W3)?)
    real getLogProbBackoff( int order , int *words ) ;

#ifdef DEBUG
    void outputText() ;
#endif
};


}

#endif