Merge branch 'const_reorder_2' into softsyn_2

1 files changed, 0 insertions, 193 deletions

diff --git a/utils/sgd.cpp b/utils/sgd.cpp
deleted file mode 100644
index 8613edca..00000000
--- a/utils/sgd.cpp
+++ /dev/null
@@ -1,193 +0,0 @@
-#include "maxent.h"
-#include <cmath>
-#include <stdio.h>
-
-using namespace std;
-
-// const double SGD_ETA0 = 1;
-// const double SGD_ITER = 30;
-// const double SGD_ALPHA = 0.85;
-
-//#define FOLOS_NAIVE
-//#define FOLOS_LAZY
-#define SGD_CP
-
-inline void apply_l1_penalty(const int i, const double u, vector<double>& _vl,
-                             vector<double>& q) {
-  double& w = _vl[i];
-  const double z = w;
-  double& qi = q[i];
-  if (w > 0) {
-    w = max(0.0, w - (u + qi));
-  } else if (w < 0) {
-    w = min(0.0, w + (u - qi));
-  }
-  qi += w - z;
-}
-
-static double l1norm(const vector<double>& v) {
-  double sum = 0;
-  for (size_t i = 0; i < v.size(); i++) sum += abs(v[i]);
-  return sum;
-}
-
-inline void update_folos_lazy(const int iter_sample, const int k,
-                              vector<double>& _vl,
-                              const vector<double>& sum_eta,
-                              vector<int>& last_updated) {
-  const double penalty = sum_eta[iter_sample] - sum_eta[last_updated[k]];
-  double& x = _vl[k];
-  if (x > 0)
-    x = max(0.0, x - penalty);
-  else
-    x = min(0.0, x + penalty);
-  last_updated[k] = iter_sample;
-}
-
-int ME_Model::perform_SGD() {
-  if (_l2reg > 0) {
-    cerr << "error: L2 regularization is currently not supported in SGD mode."
-         << endl;
-    exit(1);
-  }
-
-  cerr << "performing SGD" << endl;
-
-  const double l1param = _l1reg;
-
-  const int d = _fb.Size();
-
-  vector<int> ri(_vs.size());
-  for (size_t i = 0; i < ri.size(); i++) ri[i] = i;
-
-  vector<double> grad(d);
-  int iter_sample = 0;
-  const double eta0 = SGD_ETA0;
-
-  //  cerr << "l1param = " << l1param << endl;
-  cerr << "eta0 = " << eta0 << " alpha = " << SGD_ALPHA << endl;
-
-  double u = 0;
-  vector<double> q(d, 0);
-  vector<int> last_updated(d, 0);
-  vector<double> sum_eta;
-  sum_eta.push_back(0);
-
-  for (int iter = 0; iter < SGD_ITER; iter++) {
-
-    random_shuffle(ri.begin(), ri.end());
-
-    double logl = 0;
-    int ncorrect = 0, ntotal = 0;
-    for (size_t i = 0; i < _vs.size(); i++, ntotal++, iter_sample++) {
-      const Sample& s = _vs[ri[i]];
-
-#ifdef FOLOS_LAZY
-      for (vector<int>::const_iterator j = s.positive_features.begin();
-           j != s.positive_features.end(); j++) {
-        for (vector<int>::const_iterator k = _feature2mef[*j].begin();
-             k != _feature2mef[*j].end(); k++) {
-          update_folos_lazy(iter_sample, *k, _vl, sum_eta, last_updated);
-        }
-      }
-#endif
-
-      vector<double> membp(_num_classes);
-      const int max_label = conditional_probability(s, membp);
-
-      const double eta =
-          eta0 * pow(SGD_ALPHA,
-                     (double)iter_sample / _vs.size());  // exponential decay
-      //      const double eta = eta0 / (1.0 + (double)iter_sample /
-      // _vs.size());
-
-      //      if (iter_sample % _vs.size() == 0) cerr << "eta = " << eta <<
-      // endl;
-      u += eta * l1param;
-
-      sum_eta.push_back(sum_eta.back() + eta * l1param);
-
-      logl += log(membp[s.label]);
-      if (max_label == s.label) ncorrect++;
-
-      // binary features
-      for (vector<int>::const_iterator j = s.positive_features.begin();
-           j != s.positive_features.end(); j++) {
-        for (vector<int>::const_iterator k = _feature2mef[*j].begin();
-             k != _feature2mef[*j].end(); k++) {
-          const double me = membp[_fb.Feature(*k).label()];
-          const double ee = (_fb.Feature(*k).label() == s.label ? 1.0 : 0);
-          const double grad = (me - ee);
-          _vl[*k] -= eta * grad;
-#ifdef SGD_CP
-          apply_l1_penalty(*k, u, _vl, q);
-#endif
-        }
-      }
-      // real-valued features
-      for (vector<pair<int, double> >::const_iterator j = s.rvfeatures.begin();
-           j != s.rvfeatures.end(); j++) {
-        for (vector<int>::const_iterator k = _feature2mef[j->first].begin();
-             k != _feature2mef[j->first].end(); k++) {
-          const double me = membp[_fb.Feature(*k).label()];
-          const double ee = (_fb.Feature(*k).label() == s.label ? 1.0 : 0);
-          const double grad = (me - ee) * j->second;
-          _vl[*k] -= eta * grad;
-#ifdef SGD_CP
-          apply_l1_penalty(*k, u, _vl, q);
-#endif
-        }
-      }
-
-#ifdef FOLOS_NAIVE
-      for (size_t j = 0; j < d; j++) {
-        double& x = _vl[j];
-        if (x > 0)
-          x = max(0.0, x - eta * l1param);
-        else
-          x = min(0.0, x + eta * l1param);
-      }
-#endif
-    }
-    logl /= _vs.size();
-//    fprintf(stderr, "%4d logl = %8.3f acc = %6.4f ", iter, logl,
-// (double)ncorrect / ntotal);
-
-#ifdef FOLOS_LAZY
-    if (l1param > 0) {
-      for (size_t j = 0; j < d; j++)
-        update_folos_lazy(iter_sample, j, _vl, sum_eta, last_updated);
-    }
-#endif
-
-    double f = logl;
-    if (l1param > 0) {
-      const double l1 =
-          l1norm(_vl);  // this is not accurate when lazy update is used
-      //      cerr << "f0 = " <<  update_model_expectation() - l1param * l1 << "
-      // ";
-      f -= l1param * l1;
-      int nonzero = 0;
-      for (int j = 0; j < d; j++)
-        if (_vl[j] != 0) nonzero++;
-      //      cerr << " f = " << f << " l1 = " << l1 << " nonzero_features = "
-      // << nonzero << endl;
-    }
-    //    fprintf(stderr, "%4d  obj = %7.3f acc = %6.4f", iter+1, f,
-    // (double)ncorrect/ntotal);
-    //    fprintf(stderr, "%4d  obj = %f", iter+1, f);
-    fprintf(stderr, "%3d  obj(err) = %f (%6.4f)", iter + 1, f,
-            1 - (double)ncorrect / ntotal);
-
-    if (_nheldout > 0) {
-      double heldout_logl = heldout_likelihood();
-      //      fprintf(stderr, "  heldout_logl = %f  acc = %6.4f\n",
-      // heldout_logl, 1 - _heldout_error);
-      fprintf(stderr, "  heldout_logl(err) = %f (%6.4f)", heldout_logl,
-              _heldout_error);
-    }
-    fprintf(stderr, "\n");
-  }
-
-  return 0;
-}