new multi-epoch online optimizer

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@675 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 69 insertions, 9 deletions

diff --git a/training/mpi_batch_optimize.cc b/training/mpi_batch_optimize.cc
index 7953513e..f1ee9fb4 100644
--- a/training/mpi_batch_optimize.cc
+++ b/training/mpi_batch_optimize.cc
@@ -1,6 +1,5 @@
 #include <sstream>
 #include <iostream>
-#include <fstream>
 #include <vector>
 #include <cassert>
 #include <cmath>
@@ -61,6 +60,7 @@ void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
         ("input_weights,w",po::value<string>(),"Input feature weights file")
         ("training_data,t",po::value<string>(),"Training data")
         ("decoder_config,d",po::value<string>(),"Decoder configuration file")
+        ("sharded_input,s",po::value<string>(), "Corpus and grammar files are 'sharded' so each processor loads its own input and grammar file. Argument is the directory containing the shards.")
         ("output_weights,o",po::value<string>()->default_value("-"),"Output feature weights file")
         ("optimization_method,m", po::value<string>()->default_value("lbfgs"), "Optimization method (sgd, lbfgs, rprop)")
 	("correction_buffers,M", po::value<int>()->default_value(10), "Number of gradients for LBFGS to maintain in memory")
@@ -82,11 +82,16 @@ void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
   }
   po::notify(*conf);
 
-  if (conf->count("help") || !conf->count("input_weights") || !conf->count("training_data") || !conf->count("decoder_config")) {
+  if (conf->count("help") || !conf->count("input_weights") || !(conf->count("training_data") | conf->count("sharded_input")) || !conf->count("decoder_config")) {
     cerr << dcmdline_options << endl;
     MPI::Finalize();
     exit(1);
   }
+  if (conf->count("training_data") && conf->count("sharded_input")) {
+    cerr << "Cannot specify both --training_data and --sharded_input\n";
+    MPI::Finalize();
+    exit(1);
+  }
 }
 
 void ReadTrainingCorpus(const string& fname, int rank, int size, vector<string>* c) {
@@ -183,32 +188,79 @@ struct TrainingObserver : public DecoderObserver {
   int state;
 };
 
+void ReadConfig(const string& ini, vector<string>* out) {
+  ReadFile rf(ini);
+  istream& in = *rf.stream();
+  while(in) {
+    string line;
+    getline(in, line);
+    if (!in) continue;
+    out->push_back(line);
+  }
+}
+
+void StoreConfig(const vector<string>& cfg, istringstream* o) {
+  ostringstream os;
+  for (int i = 0; i < cfg.size(); ++i) { os << cfg[i] << endl; }
+  o->str(os.str());
+}
+
 int main(int argc, char** argv) {
   MPI::Init(argc, argv);
   const int size = MPI::COMM_WORLD.Get_size(); 
   const int rank = MPI::COMM_WORLD.Get_rank();
   SetSilent(true);  // turn off verbose decoder output
-  cerr << "MPI: I am " << rank << '/' << size << endl;
   register_feature_functions();
 
   po::variables_map conf;
   InitCommandLine(argc, argv, &conf);
 
+  string shard_dir;
+  if (conf.count("sharded_input")) {
+    shard_dir = conf["sharded_input"].as<string>();
+    if (!DirectoryExists(shard_dir)) {
+      if (rank == 0) cerr << "Can't find shard directory: " << shard_dir << endl;
+      MPI::Finalize();
+      return 1;
+    }
+    if (rank == 0)
+      cerr << "Shard directory: " << shard_dir << endl;
+  }
+
   // load initial weights
   Weights weights;
+  if (rank == 0) { cerr << "Loading weights...\n"; }
   weights.InitFromFile(conf["input_weights"].as<string>());
+  if (rank == 0) { cerr << "Done loading weights.\n"; }
 
   // freeze feature set (should be optional?)
   const bool freeze_feature_set = true;
   if (freeze_feature_set) FD::Freeze();
 
   // load cdec.ini and set up decoder
-  ReadFile ini_rf(conf["decoder_config"].as<string>());
-  Decoder decoder(ini_rf.stream());
-  if (decoder.GetConf()["input"].as<string>() != "-") {
+  vector<string> cdec_ini;
+  ReadConfig(conf["decoder_config"].as<string>(), &cdec_ini);
+  if (shard_dir.size()) {
+    if (rank == 0) {
+      for (int i = 0; i < cdec_ini.size(); ++i) {
+        if (cdec_ini[i].find("grammar=") == 0) {
+          cerr << "!!! using sharded input and " << conf["decoder_config"].as<string>() << " contains a grammar specification:\n" << cdec_ini[i] << "\n  VERIFY THAT THIS IS CORRECT!\n";
+        }
+      }
+    }
+    ostringstream g;
+    g << "grammar=" << shard_dir << "/grammar." << rank << "_of_" << size << ".gz";
+    cdec_ini.push_back(g.str());
+  }
+  istringstream ini;
+  StoreConfig(cdec_ini, &ini);
+  if (rank == 0) cerr << "Loading grammar...\n";
+  Decoder* decoder = new Decoder(&ini);
+  if (decoder->GetConf()["input"].as<string>() != "-") {
     cerr << "cdec.ini must not set an input file\n";
     MPI::COMM_WORLD.Abort(1);
   }
+  if (rank == 0) cerr << "Done loading grammar!\n";
 
   const int num_feats = FD::NumFeats();
   if (rank == 0) cerr << "Number of features: " << num_feats << endl;
@@ -247,8 +299,16 @@ int main(int argc, char** argv) {
   vector<double> gradient(num_feats, 0.0);
   vector<double> rcv_grad(num_feats, 0.0);
   bool converged = false;
+
   vector<string> corpus;
-  ReadTrainingCorpus(conf["training_data"].as<string>(), rank, size, &corpus);
+  if (shard_dir.size()) {
+    ostringstream os; os << shard_dir << "/corpus." << rank << "_of_" << size;
+    ReadTrainingCorpus(os.str(), 0, 1, &corpus);
+    cerr << os.str() << " has " << corpus.size() << " training examples. " << endl;
+    if (corpus.size() > 500) { corpus.resize(500); cerr << "  TRUNCATING\n"; }
+  } else {
+    ReadTrainingCorpus(conf["training_data"].as<string>(), rank, size, &corpus);
+  }
   assert(corpus.size() > 0);
 
   TrainingObserver observer;
@@ -257,9 +317,9 @@ int main(int argc, char** argv) {
     if (rank == 0) {
       cerr << "Starting decoding... (~" << corpus.size() << " sentences / proc)\n";
     }
-    decoder.SetWeights(lambdas);
+    decoder->SetWeights(lambdas);
     for (int i = 0; i < corpus.size(); ++i)
-      decoder.Decode(corpus[i], &observer);
+      decoder->Decode(corpus[i], &observer);
 
     fill(gradient.begin(), gradient.end(), 0);
     fill(rcv_grad.begin(), rcv_grad.end(), 0);