1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
|
#include <iostream>
#include <cmath>
#include <utility>
#ifndef HAVE_OLD_CPP
# include <unordered_map>
#else
# include <tr1/unordered_map>
namespace std { using std::tr1::unordered_map; }
#endif
#include <boost/functional/hash.hpp>
#include <boost/program_options.hpp>
#include <boost/program_options/variables_map.hpp>
#include "m.h"
#include "corpus_tools.h"
#include "stringlib.h"
#include "filelib.h"
#include "ttables.h"
#include "tdict.h"
#include "da.h"
#include <nanomsg/nn.h>
#include <nanomsg/pair.h>
#include "nn.hpp"
namespace po = boost::program_options;
using namespace std;
bool InitCommandLine(int argc, char** argv, po::variables_map* conf) {
po::options_description opts("Configuration options");
opts.add_options()
("diagonal_tension,T", po::value<double>()->default_value(4.0), "How sharp or flat around the diagonal is the alignment distribution (<1 = flat >1 = sharp)")
("mean_srclen_multiplier,m",po::value<double>()->default_value(1), "When --force_align, use this source length multiplier")
("force_align,f",po::value<string>(), "Load previously written parameters to 'force align' input. Set --diagonal_tension and --mean_srclen_multiplier as estimated during training.")
("favor_diagonal,d", "Use a static alignment distribution that assigns higher probabilities to alignments near the diagonal")
("prob_align_null", po::value<double>()->default_value(0.08), "When --favor_diagonal is set, what's the probability of a null alignment?")
("no_null_word,N","Do not generate from a null token")
("sock_url", po::value<string>()->default_value("tcp://127.0.0.1:60666"), "Socket url.");
po::options_description clo("Command line options");
clo.add_options()
("help,h", "Print this help message and exit");
po::options_description dconfig_options, dcmdline_options;
dconfig_options.add(opts);
dcmdline_options.add(opts).add(clo);
po::store(parse_command_line(argc, argv, dcmdline_options), *conf);
po::notify(*conf);
if (conf->count("help") || conf->count("force_align")==0) {
cerr << "Usage " << argv[0] << " [OPTIONS] -f params\n";
cerr << dcmdline_options << endl;
return false;
}
return true;
}
int main(int argc, char** argv) {
po::variables_map conf;
if (!InitCommandLine(argc, argv, &conf)) return 1;
const double diagonal_tension = conf["diagonal_tension"].as<double>();
const double mean_srclen_multiplier = conf["mean_srclen_multiplier"].as<double>();
const bool use_null = (conf.count("no_null_word") == 0);
const bool favor_diagonal = conf.count("favor_diagonal");
const double prob_align_null = conf["prob_align_null"].as<double>();
const double prob_align_not_null = 1.0 - prob_align_null;
const WordID kNULL = TD::Convert("<eps>");
ReadFile s2t_f(conf["force_align"].as<string>());
TTable s2t;
s2t.DeserializeLogProbsFromText(s2t_f.stream());
nn::socket sock(AF_SP, NN_PAIR);
string url = conf["sock_url"].as<string>();
sock.bind(url.c_str());
int to = 100;
sock.setsockopt(NN_SOL_SOCKET, NN_RCVTIMEO, &to, sizeof (to));
string hello = "hello";
sock.send(hello.c_str(), hello.size()+1, 0);
while (true)
{
char *buf = NULL;
size_t sz = sock.recv(&buf, NN_MSG, 0);
if (!buf)
continue;
string line(buf, buf+sz);
if (line == "shutdown") {
cerr << "[net_fa] shutting down" << endl;
string shutdown = "off";
sock.send(shutdown.c_str(), shutdown.size()+1, 0);
break;
}
cerr << "[net_fa] got '" << line << "'" << endl;
nn::freemsg(buf);
vector<WordID> src, trg;
CorpusTools::ReadLine(line, &src, &trg);
double log_prob = Md::log_poisson(trg.size(), 0.05 + src.size() * mean_srclen_multiplier);
// compute likelihood
ostringstream ss;
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;
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;
max_pat = s2t.prob(kNULL, f_j) * prob_a_i;
sum += max_pat;
}
double az = 0;
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 = 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;
}
log_prob += log(sum);
if (a_j > 0)
ss << ' ' << (a_j - 1) << '-' << j;
}
string a = ss.str();
cerr << "[net_fa] sending '" << a << "'" << endl;
sock.send(a.c_str(), a.size()+1, 0);
} // loop
return 0;
}
|
