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Diffstat (limited to 'training/mr_em_adapted_reduce.cc')
| -rw-r--r-- | training/mr_em_adapted_reduce.cc | 194 |
1 files changed, 194 insertions, 0 deletions
diff --git a/training/mr_em_adapted_reduce.cc b/training/mr_em_adapted_reduce.cc new file mode 100644 index 00000000..52387e7f --- /dev/null +++ b/training/mr_em_adapted_reduce.cc @@ -0,0 +1,194 @@ +#include <iostream> +#include <vector> +#include <cassert> +#include <cmath> + +#include <boost/program_options.hpp> +#include <boost/program_options/variables_map.hpp> + +#include "config.h" +#ifdef HAVE_BOOST_DIGAMMA +#include <boost/math/special_functions/digamma.hpp> +using boost::math::digamma; +#endif + +#include "filelib.h" +#include "fdict.h" +#include "weights.h" +#include "sparse_vector.h" + +using namespace std; +namespace po = boost::program_options; + +#ifndef HAVE_BOOST_DIGAMMA +#warning Using Mark Johnsons digamma() +double digamma(double x) { + double result = 0, xx, xx2, xx4; + assert(x > 0); + for ( ; x < 7; ++x) + result -= 1/x; + x -= 1.0/2.0; + xx = 1.0/x; + xx2 = xx*xx; + xx4 = xx2*xx2; + result += log(x)+(1./24.)*xx2-(7.0/960.0)*xx4+(31.0/8064.0)*xx4*xx2-(127.0/30720.0)*xx4*xx4; + return result; +} +#endif + +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.num_active()); + + 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 = 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(digamma(it->second + alpha) - ltot)); + } else { + pc->set_value(it->first, NoZero(log(it->second) - ltot)); + } + } +#if 0 + if (counts.num_active() < 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.num_active(), &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.num_active(), &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; +} |