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-rw-r--r--word-aligner/da.h75
-rw-r--r--word-aligner/fast_align.cc64
2 files changed, 104 insertions, 35 deletions
diff --git a/word-aligner/da.h b/word-aligner/da.h
new file mode 100644
index 00000000..add64a5b
--- /dev/null
+++ b/word-aligner/da.h
@@ -0,0 +1,75 @@
+#ifndef _DA_H_
+#define _DA_H_
+
+#include <cmath>
+#include <cassert>
+
+// m = trg len
+// n = src len
+// i = trg index
+// j = src index
+struct DiagonalAlignment {
+
+ static double UnnormalizedProb(const unsigned i, const unsigned j, const unsigned m, const unsigned n, const double alpha) {
+ assert(i > 0);
+ assert(n > 0);
+ assert(m >= i);
+ assert(n >= j);
+ return exp(feat(i, j, m, n) * alpha);
+ }
+
+ static double ComputeZ(const unsigned i, const unsigned m, const unsigned n, const double alpha) {
+ assert(i > 0);
+ assert(n > 0);
+ assert(m >= i);
+ const double split = double(i) * n / m;
+ const unsigned floor = split;
+ unsigned ceil = floor + 1;
+ const double ratio = exp(-alpha / n);
+ const unsigned num_top = n - floor;
+ double ezt = 0;
+ double ezb = 0;
+ if (num_top)
+ ezt = UnnormalizedProb(i, ceil, m, n, alpha) * (1.0 - pow(ratio, num_top)) / (1.0 - ratio);
+ if (floor)
+ ezb = UnnormalizedProb(i, floor, m, n, alpha) * (1.0 - pow(ratio, floor)) / (1.0 - ratio);
+ return ezb + ezt;
+ }
+
+ static double ComputeDLogZ(const unsigned i, const unsigned m, const unsigned n, const double alpha) {
+ const double z = ComputeZ(i, n, m, alpha);
+ const double split = double(i) * n / m;
+ const unsigned floor = split;
+ const unsigned ceil = floor + 1;
+ const double ratio = exp(-alpha / n);
+ const double d = -1.0 / n;
+ const unsigned num_top = n - floor;
+ double pct = 0;
+ double pcb = 0;
+ if (num_top) {
+ pct = arithmetico_geometric_series(feat(i, ceil, m, n), UnnormalizedProb(i, ceil, m, n, alpha), ratio, d, num_top);
+ //cerr << "PCT = " << pct << endl;
+ }
+ if (floor) {
+ pcb = arithmetico_geometric_series(feat(i, floor, m, n), UnnormalizedProb(i, floor, m, n, alpha), ratio, d, floor);
+ //cerr << "PCB = " << pcb << endl;
+ }
+ return (pct + pcb) / z;
+ }
+
+ private:
+ inline static double feat(const unsigned i, const unsigned j, const unsigned m, const unsigned n) {
+ return -fabs(double(j) / n - double(i) / m);
+ }
+
+ inline static double arithmetico_geometric_series(const double a_1, const double g_1, const double r, const double d, const unsigned n) {
+ const double g_np1 = g_1 * pow(r, n);
+ const double a_n = d * (n - 1) + a_1;
+ const double x_1 = a_1 * g_1;
+ const double g_2 = g_1 * r;
+ const double rm1 = r - 1;
+ return (a_n * g_np1 - x_1) / rm1 - d*(g_np1 - g_2) / (rm1 * rm1);
+ }
+};
+
+#endif
diff --git a/word-aligner/fast_align.cc b/word-aligner/fast_align.cc
index 7492d26f..14f7cac8 100644
--- a/word-aligner/fast_align.cc
+++ b/word-aligner/fast_align.cc
@@ -10,6 +10,7 @@
#include "filelib.h"
#include "ttables.h"
#include "tdict.h"
+#include "da.h"
namespace po = boost::program_options;
using namespace std;
@@ -68,11 +69,11 @@ int main(int argc, char** argv) {
const bool variational_bayes = (conf.count("variational_bayes") > 0);
const bool write_alignments = (conf.count("output_parameters") == 0);
const double diagonal_tension = conf["diagonal_tension"].as<double>();
- const double prob_align_null = conf["prob_align_null"].as<double>();
const bool hide_training_alignments = (conf.count("hide_training_alignments") > 0);
string testset;
if (conf.count("testset")) testset = conf["testset"].as<string>();
- const double prob_align_not_null = 1.0 - prob_align_null;
+ double prob_align_null = conf["prob_align_null"].as<double>();
+ double prob_align_not_null = 1.0 - prob_align_null;
const double alpha = conf["alpha"].as<double>();
const bool favor_diagonal = conf.count("favor_diagonal");
if (variational_bayes && alpha <= 0.0) {
@@ -84,7 +85,6 @@ int main(int argc, char** argv) {
TTable::Word2Word2Double s2t_viterbi;
double tot_len_ratio = 0;
double mean_srclen_multiplier = 0;
- vector<double> unnormed_a_i;
for (int iter = 0; iter < ITERATIONS; ++iter) {
const bool final_iteration = (iter == (ITERATIONS - 1));
cerr << "ITERATION " << (iter + 1) << (final_iteration ? " (FINAL)" : "") << endl;
@@ -97,6 +97,8 @@ int main(int argc, char** argv) {
string line;
string ssrc, strg;
vector<WordID> src, trg;
+ double c0 = 0;
+ double toks = 0;
while(true) {
getline(in, line);
if (!in) break;
@@ -110,17 +112,15 @@ int main(int argc, char** argv) {
cerr << "Error: " << lc << "\n" << line << endl;
return 1;
}
- if (src.size() > unnormed_a_i.size())
- unnormed_a_i.resize(src.size());
if (iter == 0)
tot_len_ratio += static_cast<double>(trg.size()) / static_cast<double>(src.size());
denom += trg.size();
vector<double> probs(src.size() + 1);
bool first_al = true; // used for write_alignments
- for (int j = 0; j < trg.size(); ++j) {
+ toks += trg.size();
+ for (unsigned j = 0; j < trg.size(); ++j) {
const WordID& f_j = trg[j];
double sum = 0;
- const double j_over_ts = double(j) / trg.size();
double prob_a_i = 1.0 / (src.size() + use_null); // uniform (model 1)
if (use_null) {
if (favor_diagonal) prob_a_i = prob_align_null;
@@ -128,16 +128,11 @@ int main(int argc, char** argv) {
sum += probs[0];
}
double az = 0;
- if (favor_diagonal) {
- for (int ta = 0; ta < src.size(); ++ta) {
- unnormed_a_i[ta] = exp(-fabs(double(ta) / src.size() - j_over_ts) * diagonal_tension);
- az += unnormed_a_i[ta];
- }
- az /= prob_align_not_null;
- }
- for (int i = 1; i <= src.size(); ++i) {
+ if (favor_diagonal)
+ az = DiagonalAlignment::ComputeZ(j+1, trg.size(), src.size(), diagonal_tension) / prob_align_not_null;
+ for (unsigned i = 1; i <= src.size(); ++i) {
if (favor_diagonal)
- prob_a_i = unnormed_a_i[i-1] / az;
+ prob_a_i = DiagonalAlignment::UnnormalizedProb(j + 1, i, trg.size(), src.size(), diagonal_tension) / az;
probs[i] = s2t.prob(src[i-1], f_j) * prob_a_i;
sum += probs[i];
}
@@ -151,7 +146,7 @@ int main(int argc, char** argv) {
max_index = 0;
max_p = probs[0];
}
- for (int i = 1; i <= src.size(); ++i) {
+ for (unsigned i = 1; i <= src.size(); ++i) {
if (probs[i] > max_p) {
max_index = i;
max_p = probs[i];
@@ -170,9 +165,12 @@ int main(int argc, char** argv) {
s2t_viterbi[max_i][f_j] = 1.0;
}
} else {
- if (use_null)
- s2t.Increment(kNULL, f_j, probs[0] / sum);
- for (int i = 1; i <= src.size(); ++i)
+ if (use_null) {
+ double count = probs[0] / sum;
+ c0 += count;
+ s2t.Increment(kNULL, f_j, count);
+ }
+ for (unsigned i = 1; i <= src.size(); ++i)
s2t.Increment(src[i-1], f_j, probs[i] / sum);
}
likelihood += log(sum);
@@ -190,13 +188,17 @@ int main(int argc, char** argv) {
}
cerr << " log_e likelihood: " << likelihood << endl;
cerr << " log_2 likelihood: " << base2_likelihood << endl;
- cerr << " cross entropy: " << (-base2_likelihood / denom) << endl;
- cerr << " perplexity: " << pow(2.0, -base2_likelihood / denom) << endl;
+ cerr << " cross entropy: " << (-base2_likelihood / denom) << endl;
+ cerr << " perplexity: " << pow(2.0, -base2_likelihood / denom) << endl;
if (!final_iteration) {
if (variational_bayes)
s2t.NormalizeVB(alpha);
else
s2t.Normalize();
+ cerr << " p0: " << c0 / toks << endl;
+ //prob_align_null *= 0.8;
+ //prob_align_null += (c0 / toks) * 0.2;
+ prob_align_not_null = 1.0 - prob_align_null;
}
}
if (testset.size()) {
@@ -212,16 +214,13 @@ int main(int argc, char** argv) {
cout << TD::GetString(src) << " ||| " << TD::GetString(trg) << " |||";
if (reverse) swap(src, trg);
double log_prob = Md::log_poisson(trg.size(), 0.05 + src.size() * mean_srclen_multiplier);
- if (src.size() > unnormed_a_i.size())
- unnormed_a_i.resize(src.size());
// compute likelihood
- for (int j = 0; j < trg.size(); ++j) {
+ for (unsigned j = 0; j < trg.size(); ++j) {
const WordID& f_j = trg[j];
double sum = 0;
int a_j = 0;
double max_pat = 0;
- const double j_over_ts = double(j) / trg.size();
double prob_a_i = 1.0 / (src.size() + use_null); // uniform (model 1)
if (use_null) {
if (favor_diagonal) prob_a_i = prob_align_null;
@@ -229,16 +228,11 @@ int main(int argc, char** argv) {
sum += max_pat;
}
double az = 0;
- if (favor_diagonal) {
- for (int ta = 0; ta < src.size(); ++ta) {
- unnormed_a_i[ta] = exp(-fabs(double(ta) / src.size() - j_over_ts) * diagonal_tension);
- az += unnormed_a_i[ta];
- }
- az /= prob_align_not_null;
- }
- for (int i = 1; i <= src.size(); ++i) {
+ if (favor_diagonal)
+ az = DiagonalAlignment::ComputeZ(j+1, trg.size(), src.size(), diagonal_tension) / prob_align_not_null;
+ for (unsigned i = 1; i <= src.size(); ++i) {
if (favor_diagonal)
- prob_a_i = unnormed_a_i[i-1] / az;
+ prob_a_i = DiagonalAlignment::UnnormalizedProb(j + 1, i, trg.size(), src.size(), diagonal_tension) / az;
double pat = s2t.prob(src[i-1], f_j) * prob_a_i;
if (pat > max_pat) { max_pat = pat; a_j = i; }
sum += pat;
generated by cgit v1.2.3 (git 2.39.1) at 2024-11-11 02:09:42 +0000