get rid of bad Weights class so it no longer keeps a copy of a vector inside it

2 files changed, 9 insertions, 15 deletions

diff --git a/pro-train/mr_pro_map.cc b/pro-train/mr_pro_map.cc
index 4324e8de..bc59285b 100644
--- a/pro-train/mr_pro_map.cc
+++ b/pro-train/mr_pro_map.cc
@@ -301,12 +301,8 @@ int main(int argc, char** argv) {
   const unsigned gamma = conf["candidate_pairs"].as<unsigned>();
   const unsigned xi = conf["best_pairs"].as<unsigned>();
   string weightsf = conf["weights"].as<string>();
-  vector<double> weights;
-  {
-    Weights w;
-    w.InitFromFile(weightsf);
-    w.InitVector(&weights);
-  }
+  vector<weight_t> weights;
+  Weights::InitFromFile(weightsf, &weights);
   string kbest_repo = conf["kbest_repository"].as<string>();
   MkDirP(kbest_repo);
   while(in) {
diff --git a/pro-train/mr_pro_reduce.cc b/pro-train/mr_pro_reduce.cc
index 9b422f33..9caaa1d1 100644
--- a/pro-train/mr_pro_reduce.cc
+++ b/pro-train/mr_pro_reduce.cc
@@ -194,7 +194,7 @@ int main(int argc, char** argv) {
   InitCommandLine(argc, argv, &conf);
   string line;
   vector<pair<bool, SparseVector<double> > > training, testing;
-  SparseVector<double> old_weights;
+  SparseVector<weight_t> old_weights;
   const bool tune_regularizer = conf.count("tune_regularizer");
   if (tune_regularizer && !conf.count("testset")) {
     cerr << "--tune_regularizer requires --testset to be set\n";
@@ -210,9 +210,9 @@ int main(int argc, char** argv) {
   const double psi = conf["interpolation"].as<double>();
   if (psi < 0.0 || psi > 1.0) { cerr << "Invalid interpolation weight: " << psi << endl; }
   if (conf.count("weights")) {
-    Weights w;
-    w.InitFromFile(conf["weights"].as<string>());
-    w.InitSparseVector(&old_weights);
+    vector<weight_t> dt;
+    Weights::InitFromFile(conf["weights"].as<string>(), &dt);
+    Weights::InitSparseVector(dt, &old_weights);
   }
   ReadCorpus(&cin, &training);
   if (conf.count("testset")) {
@@ -220,8 +220,8 @@ int main(int argc, char** argv) {
     ReadCorpus(rf.stream(), &testing);
   }
   cerr << "Number of features: " << FD::NumFeats() << endl;
-  vector<double> x(FD::NumFeats(), 0.0);  // x[0] is bias
-  for (SparseVector<double>::const_iterator it = old_weights.begin();
+  vector<weight_t> x(FD::NumFeats(), 0.0);  // x[0] is bias
+  for (SparseVector<weight_t>::const_iterator it = old_weights.begin();
        it != old_weights.end(); ++it)
     x[it->first] = it->second;
   double tppl = 0.0;
@@ -257,7 +257,6 @@ int main(int argc, char** argv) {
     sigsq = sp[best_i].first;
     tppl = LearnParameters(training, testing, sigsq, conf["memory_buffers"].as<unsigned>(), &x);
   }
-  Weights w;
   if (conf.count("weights")) {
     for (int i = 1; i < x.size(); ++i)
       x[i] = (x[i] * psi) + old_weights.get(i) * (1.0 - psi);
@@ -271,7 +270,6 @@ int main(int argc, char** argv) {
       cout << "# " << sp[i].first << "\t" << sp[i].second << "\t" << smoothed[i] << endl;
     }
   }
-  w.InitFromVector(x);
-  w.WriteToFile("-");
+  Weights::WriteToFile("-", x);
   return 0;
 }