summaryrefslogtreecommitdiff
path: root/training/mr_em_adapted_reduce.cc
blob: f65b5440dc076526a542ca12337012718ae213e4 (plain)
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
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
#include <iostream>
#include <vector>
#include <cassert>
#include <cmath>

#include <boost/program_options.hpp>
#include <boost/program_options/variables_map.hpp>

#include "filelib.h"
#include "fdict.h"
#include "weights.h"
#include "sparse_vector.h"
#include "m.h"

using namespace std;
namespace po = boost::program_options;

void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
  po::options_description opts("Configuration options");
  opts.add_options()
        ("optimization_method,m", po::value<string>()->default_value("em"), "Optimization method (em, vb)")
        ("input_format,f",po::value<string>()->default_value("b64"),"Encoding of the input (b64 or text)");
  po::options_description clo("Command line options");
  clo.add_options()
        ("config", po::value<string>(), "Configuration file")
        ("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);
  if (conf->count("config")) {
    ifstream config((*conf)["config"].as<string>().c_str());
    po::store(po::parse_config_file(config, dconfig_options), *conf);
  }
  po::notify(*conf);

  if (conf->count("help")) {
    cerr << dcmdline_options << endl;
    exit(1);
  }
}

double NoZero(const double& x) {
  if (x) return x;
  return 1e-35;
}

void Maximize(const bool use_vb,
              const double& alpha,
              const int total_event_types,
              SparseVector<double>* pc) {
  const SparseVector<double>& counts = *pc;

  if (use_vb)
    assert(total_event_types >= counts.size());

  double tot = 0;
  for (SparseVector<double>::const_iterator it = counts.begin();
       it != counts.end(); ++it)
    tot += it->second;
//  cerr << " = " << tot << endl;
  assert(tot > 0.0);
  double ltot = log(tot);
  if (use_vb)
    ltot = Md::digamma(tot + total_event_types * alpha);
  for (SparseVector<double>::const_iterator it = counts.begin();
       it != counts.end(); ++it) {
    if (use_vb) {
      pc->set_value(it->first, NoZero(Md::digamma(it->second + alpha) - ltot));
    } else {
      pc->set_value(it->first, NoZero(log(it->second) - ltot));
    }
  }
#if 0
  if (counts.size() < 50) {
    for (SparseVector<double>::const_iterator it = counts.begin();
         it != counts.end(); ++it) {
      cerr << " p(" << FD::Convert(it->first) << ")=" << exp(it->second);
    }
    cerr << endl;
  }
#endif
}

int main(int argc, char** argv) {
  po::variables_map conf;
  InitCommandLine(argc, argv, &conf);

  const bool use_b64 = conf["input_format"].as<string>() == "b64";
  const bool use_vb = conf["optimization_method"].as<string>() == "vb";
  const double alpha = 1e-09;
  if (use_vb)
    cerr << "Using variational Bayes, make sure alphas are set\n";

  const string s_obj = "**OBJ**";
  // E-step
  string cur_key = "";
  SparseVector<double> acc;
  double logprob = 0;
  while(cin) {
    string line;
    getline(cin, line);
    if (line.empty()) continue;
    int feat;
    double val;
    size_t i = line.find("\t");
    const string key = line.substr(0, i);
    assert(i != string::npos);
    ++i;
    if (key != cur_key) {
      if  (cur_key.size() > 0) {
        // TODO shouldn't be num_active, should be total number
        // of events
        Maximize(use_vb, alpha, acc.size(), &acc);
        cout << cur_key << '\t';
        if (use_b64)
          B64::Encode(0.0, acc, &cout);
        else
          cout << acc;
        cout << endl;
        acc.clear();
      }
      cur_key = key;
    }
    if (use_b64) {
      SparseVector<double> g;
      double obj;
      if (!B64::Decode(&obj, &g, &line[i], line.size() - i)) {
        cerr << "B64 decoder returned error, skipping!\n";
        continue;
      }
      logprob += obj;
      acc += g;
    } else {       // text encoding - your counts will not be accurate!
      while (i < line.size()) {
        size_t start = i;
        while (line[i] != '=' && i < line.size()) ++i;
        if (i == line.size()) { cerr << "FORMAT ERROR\n"; break; }
        string fname = line.substr(start, i - start);
        if (fname == s_obj) {
          feat = -1;
        } else {
          feat = FD::Convert(line.substr(start, i - start));
        }
        ++i;
        start = i;
        while (line[i] != ';' && i < line.size()) ++i;
        if (i - start == 0) continue;
        val = atof(line.substr(start, i - start).c_str());
        ++i;
        if (feat == -1) {
          logprob += val;
        } else {
          acc.add_value(feat, val);
        }
      }
    }
  }
  // TODO shouldn't be num_active, should be total number
  // of events
  Maximize(use_vb, alpha, acc.size(), &acc);
  cout << cur_key << '\t';
  if (use_b64)
    B64::Encode(0.0, acc, &cout);
  else
    cout << acc;
  cout << endl << flush;

  cerr << "LOGPROB: " << logprob << endl;

  return 0;
}