mosesdecoder/mert/Scorer.cpp
Matous Machacek ba987c94ba Support for using factors in mert and evaluator
example:
Use --factor "0|2" to use only first and third factor from nbest list and from reference.
If you use interpolated scorer, separate records with comma (e.g. --factor "0|2,1").
2012-02-28 02:27:23 +01:00

254 lines
7.1 KiB
C++

#include "Scorer.h"
#include <limits>
#include "Util.h"
namespace {
//regularisation strategies
inline float score_min(const statscores_t& scores, size_t start, size_t end)
{
float min = numeric_limits<float>::max();
for (size_t i = start; i < end; ++i) {
if (scores[i] < min) {
min = scores[i];
}
}
return min;
}
inline float score_average(const statscores_t& scores, size_t start, size_t end)
{
if ((end - start) < 1) {
// this shouldn't happen
return 0;
}
float total = 0;
for (size_t j = start; j < end; ++j) {
total += scores[j];
}
return total / (end - start);
}
} // namespace
Scorer::Scorer(const string& name, const string& config)
: m_name(name),
m_encoder(new Encoder),
m_score_data(0),
m_enable_preserve_case(true) {
InitConfig(config);
}
Scorer::~Scorer() {
delete m_encoder;
}
void Scorer::InitConfig(const string& config) {
// cerr << "Scorer config string: " << config << endl;
size_t start = 0;
while (start < config.size()) {
size_t end = config.find(",", start);
if (end == string::npos) {
end = config.size();
}
string nv = config.substr(start, end - start);
size_t split = nv.find(":");
if (split == string::npos) {
throw runtime_error("Missing colon when processing scorer config: " + config);
}
const string name = nv.substr(0, split);
const string value = nv.substr(split + 1, nv.size() - split - 1);
cerr << "name: " << name << " value: " << value << endl;
m_config[name] = value;
start = end + 1;
}
}
Scorer::Encoder::Encoder() {}
Scorer::Encoder::~Encoder() {}
int Scorer::Encoder::Encode(const string& token) {
map<string, int>::iterator it = m_vocab.find(token);
int encoded_token;
if (it == m_vocab.end()) {
// Add an new entry to the vocaburary.
encoded_token = static_cast<int>(m_vocab.size());
m_vocab[token] = encoded_token;
} else {
encoded_token = it->second;
}
return encoded_token;
}
void Scorer::TokenizeAndEncode(const string& line, vector<int>& encoded) {
std::istringstream in(line);
std::string token;
while (in >> token) {
if (!m_enable_preserve_case) {
for (std::string::iterator it = token.begin();
it != token.end(); ++it) {
*it = tolower(*it);
}
}
encoded.push_back(m_encoder->Encode(token));
}
}
/**
* Set the factors, which should be used for this metric
*/
void Scorer::setFactors(const string& factors)
{
if (factors.empty()) return;
vector<string> factors_vec;
split(factors, '|', factors_vec);
for(vector<string>::iterator it = factors_vec.begin(); it != factors_vec.end(); ++it)
{
int factor = atoi(it->c_str());
m_factors.push_back(factor);
}
}
/**
* Take the factored sentence and return the desired factors
*/
string Scorer::applyFactors(const string& sentence)
{
if (m_factors.size() == 0) return sentence;
vector<string> tokens;
split(sentence, ' ', tokens);
stringstream sstream;
for (size_t i = 0; i < tokens.size(); ++i)
{
if (tokens[i] == "") continue;
vector<string> factors;
split(tokens[i], '|', factors);
int fsize = factors.size();
if (i>0) sstream << " ";
for (size_t j = 0; j < m_factors.size(); ++j)
{
int findex = m_factors[j];
if (findex < 0 || findex >= fsize) throw runtime_error("Factor index is out of range.");
if (j>0) sstream << "|";
sstream << factors[findex];
}
}
return sstream.str();
}
StatisticsBasedScorer::StatisticsBasedScorer(const string& name, const string& config)
: Scorer(name,config) {
//configure regularisation
static string KEY_TYPE = "regtype";
static string KEY_WINDOW = "regwin";
static string KEY_CASE = "case";
static string TYPE_NONE = "none";
static string TYPE_AVERAGE = "average";
static string TYPE_MINIMUM = "min";
static string TRUE = "true";
static string FALSE = "false";
string type = getConfig(KEY_TYPE,TYPE_NONE);
if (type == TYPE_NONE) {
m_regularization_type = NONE;
} else if (type == TYPE_AVERAGE) {
m_regularization_type = AVERAGE;
} else if (type == TYPE_MINIMUM) {
m_regularization_type = MINIMUM;
} else {
throw runtime_error("Unknown scorer regularisation strategy: " + type);
}
// cerr << "Using scorer regularisation strategy: " << type << endl;
const string& window = getConfig(KEY_WINDOW, "0");
m_regularization_window = atoi(window.c_str());
// cerr << "Using scorer regularisation window: " << m_regularization_window << endl;
const string& preserve_case = getConfig(KEY_CASE,TRUE);
if (preserve_case == TRUE) {
m_enable_preserve_case = true;
} else if (preserve_case == FALSE) {
m_enable_preserve_case = false;
}
// cerr << "Using case preservation: " << m_enable_preserve_case << endl;
}
void StatisticsBasedScorer::score(const candidates_t& candidates, const diffs_t& diffs,
statscores_t& scores) const
{
if (!m_score_data) {
throw runtime_error("Score data not loaded");
}
// calculate the score for the candidates
if (m_score_data->size() == 0) {
throw runtime_error("Score data is empty");
}
if (candidates.size() == 0) {
throw runtime_error("No candidates supplied");
}
int numCounts = m_score_data->get(0,candidates[0]).size();
vector<int> totals(numCounts);
for (size_t i = 0; i < candidates.size(); ++i) {
ScoreStats stats = m_score_data->get(i,candidates[i]);
if (stats.size() != totals.size()) {
stringstream msg;
msg << "Statistics for (" << "," << candidates[i] << ") have incorrect "
<< "number of fields. Found: " << stats.size() << " Expected: "
<< totals.size();
throw runtime_error(msg.str());
}
for (size_t k = 0; k < totals.size(); ++k) {
totals[k] += stats.get(k);
}
}
scores.push_back(calculateScore(totals));
candidates_t last_candidates(candidates);
// apply each of the diffs, and get new scores
for (size_t i = 0; i < diffs.size(); ++i) {
for (size_t j = 0; j < diffs[i].size(); ++j) {
size_t sid = diffs[i][j].first;
size_t nid = diffs[i][j].second;
size_t last_nid = last_candidates[sid];
for (size_t k = 0; k < totals.size(); ++k) {
int diff = m_score_data->get(sid,nid).get(k)
- m_score_data->get(sid,last_nid).get(k);
totals[k] += diff;
}
last_candidates[sid] = nid;
}
scores.push_back(calculateScore(totals));
}
// Regularisation. This can either be none, or the min or average as described in
// Cer, Jurafsky and Manning at WMT08.
if (m_regularization_type == NONE || m_regularization_window <= 0) {
// no regularisation
return;
}
// window size specifies the +/- in each direction
statscores_t raw_scores(scores); // copy scores
for (size_t i = 0; i < scores.size(); ++i) {
size_t start = 0;
if (i >= m_regularization_window) {
start = i - m_regularization_window;
}
const size_t end = min(scores.size(), i + m_regularization_window + 1);
if (m_regularization_type == AVERAGE) {
scores[i] = score_average(raw_scores,start,end);
} else {
scores[i] = score_min(raw_scores,start,end);
}
}
}