starting an mpi version.

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@253 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 169 insertions, 0 deletions

diff --git a/gi/pyp-topics/src/mpi-train-contexts.cc b/gi/pyp-topics/src/mpi-train-contexts.cc
new file mode 100644
index 00000000..6309fe93
--- /dev/null
+++ b/gi/pyp-topics/src/mpi-train-contexts.cc
@@ -0,0 +1,169 @@
+// STL
+#include <iostream>
+#include <fstream>
+#include <algorithm>
+#include <iterator>
+
+// Boost
+#include <boost/program_options/parsers.hpp>
+#include <boost/program_options/variables_map.hpp>
+#include <boost/scoped_ptr.hpp>
+
+// Local
+#include "mpi-pyp-topics.hh"
+#include "corpus.hh"
+#include "contexts_corpus.hh"
+#include "gzstream.hh"
+
+static const char *REVISION = "$Rev: 170 $";
+
+// Namespaces
+using namespace boost;
+using namespace boost::program_options;
+using namespace std;
+
+int main(int argc, char **argv)
+{
+ cout << "Pitman Yor topic models: Copyright 2010 Phil Blunsom\n";
+ cout << REVISION << '\n' <<endl;
+
+  ////////////////////////////////////////////////////////////////////////////////////////////
+  // Command line processing
+  variables_map vm; 
+
+  // Command line processing
+  {
+    options_description cmdline_specific("Command line specific options");
+    cmdline_specific.add_options()
+      ("help,h", "print help message")
+      ("config,c", value<string>(), "config file specifying additional command line options")
+      ;
+    options_description config_options("Allowed options");
+    config_options.add_options()
+      ("help,h", "print help message")
+      ("data,d", value<string>(), "file containing the documents and context terms")
+      ("topics,t", value<int>()->default_value(50), "number of topics")
+      ("document-topics-out,o", value<string>(), "file to write the document topics to")
+      ("default-topics-out", value<string>(), "file to write default term topic assignments.")
+      ("topic-words-out,w", value<string>(), "file to write the topic word distribution to")
+      ("samples,s", value<int>()->default_value(10), "number of sampling passes through the data")
+      ("backoff-type", value<string>(), "backoff type: none|simple")
+//      ("filter-singleton-contexts", "filter singleton contexts")
+      ("hierarchical-topics", "Use a backoff hierarchical PYP as the P0 for the document topics distribution.")
+      ("freq-cutoff-start", value<int>()->default_value(0), "initial frequency cutoff.")
+      ("freq-cutoff-end", value<int>()->default_value(0), "final frequency cutoff.")
+      ("freq-cutoff-interval", value<int>()->default_value(0), "number of iterations between frequency decrement.")
+      ("max-threads", value<int>()->default_value(1), "maximum number of simultaneous threads allowed")
+      ("max-contexts-per-document", value<int>()->default_value(0), "Only sample the n most frequent contexts for a document.")
+      ;
+
+    cmdline_specific.add(config_options);
+
+    store(parse_command_line(argc, argv, cmdline_specific), vm); 
+    notify(vm);
+
+    if (vm.count("config") > 0) {
+      ifstream config(vm["config"].as<string>().c_str());
+      store(parse_config_file(config, config_options), vm); 
+    }
+
+    if (vm.count("help")) { 
+      cout << cmdline_specific << "\n"; 
+      return 1; 
+    }
+  }
+  ////////////////////////////////////////////////////////////////////////////////////////////
+
+  if (!vm.count("data")) {
+    cerr << "Please specify a file containing the data." << endl;
+    return 1;
+  }
+
+  // seed the random number generator: 0 = automatic, specify value otherwise
+  unsigned long seed = 0; 
+  PYPTopics model(vm["topics"].as<int>(), vm.count("hierarchical-topics"), seed, vm["max-threads"].as<int>());
+
+  // read the data
+  BackoffGenerator* backoff_gen=0;
+  if (vm.count("backoff-type")) {
+    if (vm["backoff-type"].as<std::string>() == "none") {
+      backoff_gen = 0;
+    }
+    else if (vm["backoff-type"].as<std::string>() == "simple") {
+      backoff_gen = new SimpleBackoffGenerator();
+    }
+    else {
+     cerr << "Backoff type (--backoff-type) must be one of none|simple." <<endl;
+      return(1);
+    }
+  }
+
+  ContextsCorpus contexts_corpus;
+  contexts_corpus.read_contexts(vm["data"].as<string>(), backoff_gen, /*vm.count("filter-singleton-contexts")*/ false);
+  model.set_backoff(contexts_corpus.backoff_index());
+
+  if (backoff_gen) 
+    delete backoff_gen;
+
+  // train the sampler
+  model.sample_corpus(contexts_corpus, vm["samples"].as<int>(),
+                      vm["freq-cutoff-start"].as<int>(),
+                      vm["freq-cutoff-end"].as<int>(),
+                      vm["freq-cutoff-interval"].as<int>(),
+                      vm["max-contexts-per-document"].as<int>());
+
+  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;
+    }
+    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;
+      }
+    }
+  }
+
+  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();
+  }
+
+ cout <<endl;
+
+  return 0;
+}