another feature, another POS

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@664 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 11 insertions, 7 deletions

diff --git a/training/mpi_online_optimize.cc b/training/mpi_online_optimize.cc
index 0c032c01..d662e8bd 100644
--- a/training/mpi_online_optimize.cc
+++ b/training/mpi_online_optimize.cc
@@ -215,10 +215,9 @@ int main(int argc, char** argv) {
   mpi::communicator world;
   const int size = world.size(); 
   const int rank = world.rank();
-  SetSilent(true);  // turn off verbose decoder output
-  cerr << "MPI: I am " << rank << '/' << size << endl;
+  if (size > 1) SetSilent(true);  // turn off verbose decoder output
   register_feature_functions();
-  MT19937* rng = NULL;
+  std::tr1::shared_ptr<MT19937> rng;
 
   po::variables_map conf;
   InitCommandLine(argc, argv, &conf);
@@ -272,9 +271,9 @@ int main(int argc, char** argv) {
     for (unsigned i = 0; i < order.size(); ++i) order[i]=i;
     // randomize corpus
     if (conf.count("random_seed"))
-      rng = new MT19937(conf["random_seed"].as<uint32_t>());
+      rng.reset(new MT19937(conf["random_seed"].as<uint32_t>()));
     else
-      rng = new MT19937;
+      rng.reset(new MT19937);
   }
   SparseVector<double> x;
   weights.InitSparseVector(&x);
@@ -283,6 +282,7 @@ int main(int argc, char** argv) {
   double objective = 0;
   bool converged = false;
 
+  int write_weights_every_ith = 100; // TODO configure
   int iter = -1;
   vector<double> lambdas;
   while (!converged) {
@@ -296,6 +296,10 @@ int main(int argc, char** argv) {
       ShowLargestFeatures(lambdas);
       string fname = "weights.cur.gz";
       if (converged) { fname = "weights.final.gz"; }
+      if (iter % write_weights_every_ith == 0) {
+        ostringstream o; o << "weights." << iter << ".gz";
+        fname = o.str();
+      }
       ostringstream vv;
       vv << "Objective = " << objective; // << "  (eval count=" << o->EvaluationCount() << ")";
       const string svv = vv.str();
@@ -304,12 +308,12 @@ int main(int argc, char** argv) {
 
     if (fully_random || size * size_per_proc * miter > corpus.size()) {
       if (rank == 0)
-        Shuffle(&order, rng);
+        Shuffle(&order, rng.get());
       miter = 0;
       broadcast(world, order, 0);
     }
     if (rank == 0)
-      cerr << "iter=" << iter << "   minibatch=" << size_per_proc << " sentences/proc x " << size << " procs. num_feats=" << x.size() << "   passes_thru_data=" << (iter * batch_size / static_cast<double>(corpus.size())) << "   eta=" << lr->eta(iter) << endl;
+      cerr << "iter=" << iter << "   minibatch=" << size_per_proc << " sentences/proc x " << size << " procs.   num_feats=" << x.size() << '/' << FD::NumFeats() << "   passes_thru_data=" << (iter * batch_size / static_cast<double>(corpus.size())) << "   eta=" << lr->eta(iter) << endl;
 
     const int beg = size * miter * size_per_proc + rank * size_per_proc;
     const int end = beg + size_per_proc;