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#ifndef NEURALTM_H
#define NEURALTM_H
#include <vector>
#include <cctype>
#include <cstdlib>
#include <boost/shared_ptr.hpp>
#include <Eigen/Dense>
#include "util.h"
#include "vocabulary.h"
#include "neuralNetwork.h"
#include "replace_digits.hpp"
namespace nplm
{
class neuralTM : public neuralNetwork, graehl::replace_digits
{
boost::shared_ptr<vocabulary> input_vocab, output_vocab;
int start, null;
public:
neuralTM()
: neuralNetwork(),
graehl::replace_digits(0),
input_vocab(new vocabulary()),
output_vocab(new vocabulary())
{
}
void set_map_digits(char value) { map_digits = value; }
void set_input_vocabulary(const vocabulary &vocab)
{
*(this->input_vocab) = vocab;
start = vocab.lookup_word("<s>");
null = vocab.lookup_word("<null>");
}
void set_output_vocabulary(const vocabulary &vocab)
{
*(this->output_vocab) = vocab;
}
const vocabulary &get_input_vocabulary() const { return *(this->input_vocab); }
const vocabulary &get_output_vocabulary() const { return *(this->output_vocab); }
int lookup_word(const std::string &word, vocabulary const& vocab) const
{
if (map_digits)
for (int i=0, n=word.size(); i<n; ++i)
if (graehl::ascii_digit(word[i])) {
std::string mapped_word(word);
replace(mapped_word, i);
return vocab->lookup_word(mapped_word);
}
return vocab->lookup_word(word);
}
int lookup_word(std::pair<char const*, char const*> slice, vocabulary const& vocab) const
{
if (map_digits)
for (char const* i = slice.first; i != slice.second; ++i)
if (graehl::ascii_digit(*i)) {
std::string mapped_word(slice.first, slice.second);
replace(mapped_word, i - slice.first);
return vocab->lookup_word(mapped_word);
}
return vocab->lookup_word(slice);
}
int lookup_input_word(const std::string &word) const
{
return lookup_word(word, *input_vocab);
}
int lookup_output_word(const std::string &word) const
{
return lookup_word(word, *output_vocab);
}
int lookup_input_word(std::pair<char const*, char const*> word) const
{
return lookup_word(word, *input_vocab);
}
int lookup_output_word(std::pair<char const*, char const*> word) const
{
return lookup_word(word, *output_vocab);
}
double lookup_ngram(const int *ngram_a, int n)
{
Eigen::Matrix<int,Eigen::Dynamic,1> ngram(m->ngram_size);
for (int i=0; i<m->ngram_size; i++)
{
if (i-m->ngram_size+n < 0)
{
if (ngram_a[0] == start)
ngram(i) = start;
else
ngram(i) = null;
}
else
{
ngram(i) = ngram_a[i-m->ngram_size+n];
}
}
return neuralNetwork::lookup_ngram(ngram);
}
double lookup_ngram(const std::vector<int> &ngram_v)
{
return lookup_ngram(ngram_v.data(), ngram_v.size());
}
template <typename Derived>
double lookup_ngram(const Eigen::MatrixBase<Derived> &ngram)
{
return neuralNetwork::lookup_ngram(ngram);
}
template <typename DerivedA, typename DerivedB>
void lookup_ngram(const Eigen::MatrixBase<DerivedA> &ngram, const Eigen::MatrixBase<DerivedB> &log_probs_const)
{
return neuralNetwork::lookup_ngram(ngram, log_probs_const);
}
void read(const std::string &filename)
{
std::vector<std::string> input_words;
std::vector<std::string> output_words;
m->read(filename, input_words, output_words);
set_input_vocabulary(vocabulary(input_words));
set_output_vocabulary(vocabulary(output_words));
resize();
// this is faster but takes more memory
//m->premultiply();
}
};
} // namespace nplm
#endif
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