move some functions to .hh file for easier integration with other products

2 files changed, 99 insertions, 89 deletions

diff --git a/lm/ngram_query.cc b/lm/ngram_query.cc
index 1b2cd5db3..19a63fb25 100644
--- a/lm/ngram_query.cc
+++ b/lm/ngram_query.cc
@@ -1,90 +1,9 @@
-#include "lm/enumerate_vocab.hh"
-#include "lm/model.hh"
+#include "lm/ngram_query.hh"
 
-#include <cstdlib>
-#include <fstream>
-#include <iostream>
-#include <string>
-
-#include <ctype.h>
-#if !defined(_WIN32) && !defined(_WIN64)
-#include <sys/resource.h>
-#include <sys/time.h>
-#endif
-
-#if !defined(_WIN32) && !defined(_WIN64)
-float FloatSec(const struct timeval &tv) {
-  return static_cast<float>(tv.tv_sec) + (static_cast<float>(tv.tv_usec) / 1000000000.0);
-}
-#endif
-
-void PrintUsage(const char *message) {
-#if !defined(_WIN32) && !defined(_WIN64)
-  struct rusage usage;
-  if (getrusage(RUSAGE_SELF, &usage)) {
-    perror("getrusage");
-    return;
-  }
-  std::cerr << message;
-  std::cerr << "user\t" << FloatSec(usage.ru_utime) << "\nsys\t" << FloatSec(usage.ru_stime) << '\n';
-
-  // Linux doesn't set memory usage :-(.  
-  std::ifstream status("/proc/self/status", std::ios::in);
-  std::string line;
-  while (getline(status, line)) {
-    if (!strncmp(line.c_str(), "VmRSS:\t", 7)) {
-      std::cerr << "rss " << (line.c_str() + 7) << '\n';
-      break;
-    }
-  }
-#endif
-}
-
-template <class Model> void Query(const Model &model, bool sentence_context) {
-  PrintUsage("Loading statistics:\n");
-  typename Model::State state, out;
-  lm::FullScoreReturn ret;
-  std::string word;
-
-  while (std::cin) {
-    state = sentence_context ? model.BeginSentenceState() : model.NullContextState();
-    float total = 0.0;
-    bool got = false;
-    unsigned int oov = 0;
-    while (std::cin >> word) {
-      got = true;
-      lm::WordIndex vocab = model.GetVocabulary().Index(word);
-      if (vocab == 0) ++oov;
-      ret = model.FullScore(state, vocab, out);
-      total += ret.prob;
-      std::cout << word << '=' << vocab << ' ' << static_cast<unsigned int>(ret.ngram_length)  << ' ' << ret.prob << '\t';
-      state = out;
-      char c;
-      while (true) {
-        c = std::cin.get();
-        if (!std::cin) break;
-        if (c == '\n') break;
-        if (!isspace(c)) {
-          std::cin.unget();
-          break;
-        }
-      }
-      if (c == '\n') break;
-    }
-    if (!got && !std::cin) break;
-    if (sentence_context) {
-      ret = model.FullScore(state, model.GetVocabulary().EndSentence(), out);
-      total += ret.prob;
-      std::cout << "</s>=" << model.GetVocabulary().EndSentence() << ' ' << static_cast<unsigned int>(ret.ngram_length)  << ' ' << ret.prob << '\t';
-    }
-    std::cout << "Total: " << total << " OOV: " << oov << '\n';
-  }
-  PrintUsage("After queries:\n");
-}
 
 template <class Model> void Query(const char *name) {
   lm::ngram::Config config;
-  Model model(name, config);
+  Model model(name, config, std::cin, std::cout);
   Query(model);
 }
 
@@ -100,19 +19,19 @@ int main(int argc, char *argv[]) {
     if (lm::ngram::RecognizeBinary(argv[1], model_type)) {
       switch(model_type) {
         case lm::ngram::HASH_PROBING:
-          Query<lm::ngram::ProbingModel>(argv[1], sentence_context);
+          Query<lm::ngram::ProbingModel>(argv[1], sentence_context, std::cin, std::cout);
           break;
         case lm::ngram::TRIE_SORTED:
-          Query<lm::ngram::TrieModel>(argv[1], sentence_context);
+          Query<lm::ngram::TrieModel>(argv[1], sentence_context, std::cin, std::cout);
           break;
         case lm::ngram::QUANT_TRIE_SORTED:
-          Query<lm::ngram::QuantTrieModel>(argv[1], sentence_context);
+          Query<lm::ngram::QuantTrieModel>(argv[1], sentence_context, std::cin, std::cout);
           break;
         case lm::ngram::ARRAY_TRIE_SORTED:
-          Query<lm::ngram::ArrayTrieModel>(argv[1], sentence_context);
+          Query<lm::ngram::ArrayTrieModel>(argv[1], sentence_context, std::cin, std::cout);
           break;
         case lm::ngram::QUANT_ARRAY_TRIE_SORTED:
-          Query<lm::ngram::QuantArrayTrieModel>(argv[1], sentence_context);
+          Query<lm::ngram::QuantArrayTrieModel>(argv[1], sentence_context, std::cin, std::cout);
           break;
         case lm::ngram::HASH_SORTED:
         default:
@@ -120,7 +39,7 @@ int main(int argc, char *argv[]) {
           abort();
       }
     } else {
-      Query<lm::ngram::ProbingModel>(argv[1], sentence_context);
+      Query<lm::ngram::ProbingModel>(argv[1], sentence_context, std::cin, std::cout);
     }
 
     PrintUsage("Total time including destruction:\n");
diff --git a/lm/ngram_query.hh b/lm/ngram_query.hh
new file mode 100644
index 000000000..6bf6ec48b
--- /dev/null
+++ b/lm/ngram_query.hh
@@ -0,0 +1,91 @@
+#ifndef LM_NGRAM_QUERY__
+#define LM_NGRAM_QUERY__
+
+#include "lm/enumerate_vocab.hh"
+#include "lm/model.hh"
+
+#include <cstdlib>
+#include <fstream>
+#include <iostream>
+#include <string>
+
+#include <ctype.h>
+#if !defined(_WIN32) && !defined(_WIN64)
+#include <sys/resource.h>
+#include <sys/time.h>
+#endif
+
+#if !defined(_WIN32) && !defined(_WIN64)
+float FloatSec(const struct timeval &tv) {
+  return static_cast<float>(tv.tv_sec) + (static_cast<float>(tv.tv_usec) / 1000000000.0);
+}
+#endif
+
+void PrintUsage(const char *message) {
+#if !defined(_WIN32) && !defined(_WIN64)
+  struct rusage usage;
+  if (getrusage(RUSAGE_SELF, &usage)) {
+    perror("getrusage");
+    return;
+  }
+  std::cerr << message;
+  std::cerr << "user\t" << FloatSec(usage.ru_utime) << "\nsys\t" << FloatSec(usage.ru_stime) << '\n';
+
+  // Linux doesn't set memory usage :-(.  
+  std::ifstream status("/proc/self/status", std::ios::in);
+  std::string line;
+  while (getline(status, line)) {
+    if (!strncmp(line.c_str(), "VmRSS:\t", 7)) {
+      std::cerr << "rss " << (line.c_str() + 7) << '\n';
+      break;
+    }
+  }
+#endif
+}
+
+template <class Model> void Query(const Model &model, bool sentence_context, std::istream &inStream, std::ostream &outStream) {
+  PrintUsage("Loading statistics:\n");
+  typename Model::State state, out;
+  lm::FullScoreReturn ret;
+  std::string word;
+
+  while (inStream) {
+    state = sentence_context ? model.BeginSentenceState() : model.NullContextState();
+    float total = 0.0;
+    bool got = false;
+    unsigned int oov = 0;
+    while (inStream >> word) {
+      got = true;
+      lm::WordIndex vocab = model.GetVocabulary().Index(word);
+      if (vocab == 0) ++oov;
+      ret = model.FullScore(state, vocab, out);
+      total += ret.prob;
+      outStream << word << '=' << vocab << ' ' << static_cast<unsigned int>(ret.ngram_length)  << ' ' << ret.prob << '\t';
+      state = out;
+      char c;
+      while (true) {
+        c = inStream.get();
+        if (!inStream) break;
+        if (c == '\n') break;
+        if (!isspace(c)) {
+          inStream.unget();
+          break;
+        }
+      }
+      if (c == '\n') break;
+    }
+    if (!got && !inStream) break;
+    if (sentence_context) {
+      ret = model.FullScore(state, model.GetVocabulary().EndSentence(), out);
+      total += ret.prob;
+      outStream << "</s>=" << model.GetVocabulary().EndSentence() << ' ' << static_cast<unsigned int>(ret.ngram_length)  << ' ' << ret.prob << '\t';
+    }
+    outStream << "Total: " << total << " OOV: " << oov << '\n';
+  }
+  PrintUsage("After queries:\n");
+}
+
+
+#endif // LM_NGRAM_QUERY__
+
+