From 73dbb0343a895345a80d49da9d48edac8858e87a Mon Sep 17 00:00:00 2001
From: philblunsom <philblunsom@ec762483-ff6d-05da-a07a-a48fb63a330f>
Date: Mon, 19 Jul 2010 18:33:29 +0000
Subject: Vaguely working distributed implementation. Hierarchical topics
 doesn't yet work correctly.

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@317 ec762483-ff6d-05da-a07a-a48fb63a330f
---
 gi/pyp-topics/src/mpi-train-contexts.cc | 113 ++++++++++++++++++--------------
 1 file changed, 64 insertions(+), 49 deletions(-)

(limited to 'gi/pyp-topics/src/mpi-train-contexts.cc')

diff --git a/gi/pyp-topics/src/mpi-train-contexts.cc b/gi/pyp-topics/src/mpi-train-contexts.cc
index 0651ecac..6e1e78a5 100644
--- a/gi/pyp-topics/src/mpi-train-contexts.cc
+++ b/gi/pyp-topics/src/mpi-train-contexts.cc
@@ -10,6 +10,7 @@
 #include <boost/scoped_ptr.hpp>
 #include <boost/mpi/environment.hpp>
 #include <boost/mpi/communicator.hpp>
+#include <boost/lexical_cast.hpp>
 
 // Local
 #include "mpi-pyp-topics.hh"
@@ -28,9 +29,10 @@ int main(int argc, char **argv)
 {
   mpi::environment env(argc, argv);
   mpi::communicator world;
-  bool am_root = (world.rank() == 0);
-  if (am_root) std::cout << "I am process " << world.rank() << " of " << world.size() << "." << std::endl;
+  int rank = world.rank();
+  bool am_root = rank;
   if (am_root) cout << "Pitman Yor topic models: Copyright 2010 Phil Blunsom\n";
+  if (am_root) std::cout << "I am process " << world.rank() << " of " << world.size() << "." << std::endl;
   if (am_root) cout << REVISION << '\n' <<endl;
 
   ////////////////////////////////////////////////////////////////////////////////////////////
@@ -117,60 +119,73 @@ int main(int argc, char **argv)
                       vm["freq-cutoff-interval"].as<int>(),
                       vm["max-contexts-per-document"].as<int>());
 
-  if (world.rank() == 0) {
-    if (vm.count("document-topics-out")) {
-      ogzstream documents_out(vm["document-topics-out"].as<string>().c_str());
-
-      int document_id=0;
-      map<int,int> all_terms;
-      for (Corpus::const_iterator corpusIt=contexts_corpus.begin(); 
-           corpusIt != contexts_corpus.end(); ++corpusIt, ++document_id) {
-        vector<int> unique_terms;
-        for (Document::const_iterator docIt=corpusIt->begin();
-             docIt != corpusIt->end(); ++docIt) {
-          if (unique_terms.empty() || *docIt != unique_terms.back())
-            unique_terms.push_back(*docIt);
-          // increment this terms frequency
-          pair<map<int,int>::iterator,bool> insert_result = all_terms.insert(make_pair(*docIt,1));
-          if (!insert_result.second) 
-            all_terms[*docIt] = all_terms[*docIt] + 1;
-          //insert_result.first++;
-        }
-        documents_out << contexts_corpus.key(document_id) << '\t';
-        documents_out << model.max(document_id) << " " << corpusIt->size() << " ||| ";
-        for (std::vector<int>::const_iterator termIt=unique_terms.begin();
-             termIt != unique_terms.end(); ++termIt) {
-          if (termIt != unique_terms.begin())
-            documents_out << " ||| ";
-          vector<std::string> strings = contexts_corpus.context2string(*termIt);
-          copy(strings.begin(), strings.end(),ostream_iterator<std::string>(documents_out, " "));
-          documents_out << "||| C=" << model.max(document_id, *termIt);
-
-        }
-        documents_out <<endl;
+  if (vm.count("document-topics-out")) {
+    std::ofstream documents_out((vm["document-topics-out"].as<string>() + ".pyp-process-" + boost::lexical_cast<std::string>(rank)).c_str());
+    int documents = contexts_corpus.num_documents();
+    int mpi_start = 0, mpi_end = documents;
+    if (world.size() != 1) {
+      mpi_start = (documents / world.size()) * rank;
+      if (rank == world.size()-1) mpi_end = documents;
+      else mpi_end = (documents / world.size())*(rank+1);
+    }
+
+    map<int,int> all_terms;
+    for (int document_id=mpi_start; document_id<mpi_end; ++document_id) {
+      assert (document_id < contexts_corpus.num_documents());
+      const Document& doc = contexts_corpus.at(document_id);
+      vector<int> unique_terms;
+      for (Document::const_iterator docIt=doc.begin(); docIt != doc.end(); ++docIt) {
+        if (unique_terms.empty() || *docIt != unique_terms.back())
+          unique_terms.push_back(*docIt);
+        // increment this terms frequency
+        pair<map<int,int>::iterator,bool> insert_result = all_terms.insert(make_pair(*docIt,1));
+        if (!insert_result.second) 
+          all_terms[*docIt] = all_terms[*docIt] + 1;
       }
-      documents_out.close();
-
-      if (vm.count("default-topics-out")) {
-        ofstream default_topics(vm["default-topics-out"].as<string>().c_str());
-        default_topics << model.max_topic() <<endl;
-        for (std::map<int,int>::const_iterator termIt=all_terms.begin(); termIt != all_terms.end(); ++termIt) {
-          vector<std::string> strings = contexts_corpus.context2string(termIt->first);
-          default_topics << model.max(-1, termIt->first) << " ||| " << termIt->second << " ||| ";
-          copy(strings.begin(), strings.end(),ostream_iterator<std::string>(default_topics, " "));
-          default_topics <<endl;
-        }
+      documents_out << contexts_corpus.key(document_id) << '\t';
+      documents_out << model.max(document_id) << " " << doc.size() << " ||| ";
+      for (std::vector<int>::const_iterator termIt=unique_terms.begin(); termIt != unique_terms.end(); ++termIt) {
+        if (termIt != unique_terms.begin())
+          documents_out << " ||| ";
+        vector<std::string> strings = contexts_corpus.context2string(*termIt);
+        copy(strings.begin(), strings.end(),ostream_iterator<std::string>(documents_out, " "));
+        documents_out << "||| C=" << model.max(document_id, *termIt);
       }
+      documents_out <<endl;
+    }
+    documents_out.close();
+
+    if (am_root) {
+      ogzstream root_documents_out(vm["document-topics-out"].as<string>().c_str());
+      for (int p=0; p < world.size(); ++p) {
+        std::string rank_p_prefix((vm["document-topics-out"].as<string>() + ".pyp-process-" + boost::lexical_cast<std::string>(p)).c_str());
+        std::ifstream rank_p_trees_istream(rank_p_prefix.c_str(), std::ios_base::binary);
+        root_documents_out << rank_p_trees_istream.rdbuf();
+        rank_p_trees_istream.close();
+        remove((rank_p_prefix).c_str());
+      }
+      root_documents_out.close();
     }
 
-    if (vm.count("topic-words-out")) {
-      ogzstream topics_out(vm["topic-words-out"].as<string>().c_str());
-      model.print_topic_terms(topics_out);
-      topics_out.close();
+    if (am_root && vm.count("default-topics-out")) {
+      ofstream default_topics(vm["default-topics-out"].as<string>().c_str());
+      default_topics << model.max_topic() <<endl;
+      for (std::map<int,int>::const_iterator termIt=all_terms.begin(); termIt != all_terms.end(); ++termIt) {
+        vector<std::string> strings = contexts_corpus.context2string(termIt->first);
+        default_topics << model.max(-1, termIt->first) << " ||| " << termIt->second << " ||| ";
+        copy(strings.begin(), strings.end(),ostream_iterator<std::string>(default_topics, " "));
+        default_topics <<endl;
+      }
     }
+  }
 
-    cout <<endl;
+  if (am_root && vm.count("topic-words-out")) {
+    ogzstream topics_out(vm["topic-words-out"].as<string>().c_str());
+    model.print_topic_terms(topics_out);
+    topics_out.close();
   }
 
+  cout <<endl;
+
   return 0;
 }
-- 
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