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-rw-r--r--training/mr_em_map_adapter.cc160
1 files changed, 160 insertions, 0 deletions
diff --git a/training/mr_em_map_adapter.cc b/training/mr_em_map_adapter.cc
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+#include <iostream>
+#include <fstream>
+#include <cassert>
+#include <cmath>
+
+#include <boost/utility.hpp>
+#include <boost/program_options.hpp>
+#include <boost/program_options/variables_map.hpp>
+#include "boost/tuple/tuple.hpp"
+
+#include "fdict.h"
+#include "sparse_vector.h"
+
+using namespace std;
+namespace po = boost::program_options;
+
+// useful for EM models parameterized by a bunch of multinomials
+// this converts event counts (returned from cdec as feature expectations)
+// into different keys and values (which are lists of all the events,
+// conditioned on the key) for summing and normalization by a reducer
+
+void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
+ po::options_description opts("Configuration options");
+ opts.add_options()
+ ("buffer_size,b", po::value<int>()->default_value(1), "Buffer size (in # of counts) before emitting counts")
+ ("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);
+ }
+}
+
+struct EventMapper {
+ int Map(int fid) {
+ int& cv = map_[fid];
+ if (!cv) {
+ cv = GetConditioningVariable(fid);
+ }
+ return cv;
+ }
+ void Clear() { map_.clear(); }
+ protected:
+ virtual int GetConditioningVariable(int fid) const = 0;
+ private:
+ map<int, int> map_;
+};
+
+struct LexAlignEventMapper : public EventMapper {
+ protected:
+ virtual int GetConditioningVariable(int fid) const {
+ const string& str = FD::Convert(fid);
+ size_t pos = str.rfind("_");
+ if (pos == string::npos || pos == 0 || pos >= str.size() - 1) {
+ cerr << "Bad feature for EM adapter: " << str << endl;
+ abort();
+ }
+ return FD::Convert(str.substr(0, pos));
+ }
+};
+
+int main(int argc, char** argv) {
+ po::variables_map conf;
+ InitCommandLine(argc, argv, &conf);
+
+ const bool use_b64 = conf["format"].as<string>() == "b64";
+ const int buffer_size = conf["buffer_size"].as<int>();
+
+ const string s_obj = "**OBJ**";
+ // 0<TAB>**OBJ**=12.2;Feat1=2.3;Feat2=-0.2;
+ // 0<TAB>**OBJ**=1.1;Feat1=1.0;
+
+ EventMapper* event_mapper = new LexAlignEventMapper;
+ map<int, SparseVector<double> > counts;
+ size_t total = 0;
+ while(cin) {
+ string line;
+ getline(cin, line);
+ if (line.empty()) continue;
+ int feat;
+ double val;
+ size_t i = line.find("\t");
+ assert(i != string::npos);
+ ++i;
+ SparseVector<double> g;
+ double obj = 0;
+ if (use_b64) {
+ if (!B64::Decode(&obj, &g, &line[i], line.size() - i)) {
+ cerr << "B64 decoder returned error, skipping!\n";
+ continue;
+ }
+ } 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) {
+ obj = val;
+ } else {
+ g.set_value(feat, val);
+ }
+ }
+ }
+ //cerr << "OBJ: " << obj << endl;
+ const SparseVector<double>& cg = g;
+ for (SparseVector<double>::const_iterator it = cg.begin(); it != cg.end(); ++it) {
+ const int cond_var = event_mapper->Map(it->first);
+ SparseVector<double>& cond_counts = counts[cond_var];
+ int delta = cond_counts.num_active();
+ cond_counts.add_value(it->first, it->second);
+ delta = cond_counts.num_active() - delta;
+ total += delta;
+ }
+ if (total > buffer_size) {
+ for (map<int, SparseVector<double> >::iterator it = counts.begin();
+ it != counts.end(); ++it) {
+ const SparseVector<double>& cc = it->second;
+ cout << FD::Convert(it->first) << '\t';
+ if (use_b64) {
+ B64::Encode(0.0, cc, &cout);
+ } else {
+ abort();
+ }
+ cout << endl;
+ }
+ cout << flush;
+ total = 0;
+ counts.clear();
+ }
+ }
+
+ return 0;
+}
+