Apply clang-format

1 files changed, 80 insertions, 67 deletions

diff --git a/utils/synutils/maxent-3.0/sgd.cpp b/utils/synutils/maxent-3.0/sgd.cpp
index 6d28c23f..8613edca 100644
--- a/utils/synutils/maxent-3.0/sgd.cpp
+++ b/utils/synutils/maxent-3.0/sgd.cpp
@@ -4,23 +4,20 @@
 
 using namespace std;
 
-//const double SGD_ETA0 = 1;
-//const double SGD_ITER = 30;
-//const double SGD_ALPHA = 0.85;
-
+// 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];
+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) { 
+  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));
@@ -28,31 +25,29 @@ apply_l1_penalty(const int i, const double u,
   qi += w - z;
 }
 
-static double
-l1norm(const vector<double>& v)
-{
+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)
-{
+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);
+  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()
-{
+int ME_Model::perform_SGD() {
   if (_l2reg > 0) {
-    cerr << "error: L2 regularization is currently not supported in SGD mode." << endl;
+    cerr << "error: L2 regularization is currently not supported in SGD mode."
+         << endl;
     exit(1);
   }
 
@@ -85,95 +80,113 @@ ME_Model::perform_SGD()
     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]];
+      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);
-	}
+      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());
+      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;
+      //      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;
+      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);
+          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;
+      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);
+          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);
+        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);
+//    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);
+        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 << " ";
+      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;
+      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 = %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);
+    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, "  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;