Move training routine out of ff_const_reorder_common.h

1 files changed, 0 insertions, 93 deletions

diff --git a/decoder/ff_const_reorder_common.h b/decoder/ff_const_reorder_common.h
index 7c111de3..b124ce47 100644
--- a/decoder/ff_const_reorder_common.h
+++ b/decoder/ff_const_reorder_common.h
@@ -1091,99 +1091,6 @@ struct Tsuruoka_Maxent {
     if (m_pModel != NULL) delete m_pModel;
   }
 
-  void fnTrain(const char* pszInstanceFName, const char* pszAlgorithm,
-               const char* pszModelFName, int /*iNumIteration*/) {
-    assert(strcmp(pszAlgorithm, "l1") == 0 || strcmp(pszAlgorithm, "l2") == 0 ||
-           strcmp(pszAlgorithm, "sgd") == 0 ||
-           strcmp(pszAlgorithm, "SGD") == 0);
-    FILE* fpIn = fopen(pszInstanceFName, "r");
-
-    ME_Model* pModel = new ME_Model();
-
-    char* pszLine = new char[100001];
-    int iNumInstances = 0;
-    int iLen;
-    while (!feof(fpIn)) {
-      pszLine[0] = '\0';
-      fgets(pszLine, 20000, fpIn);
-      if (strlen(pszLine) == 0) {
-        continue;
-      }
-
-      iLen = strlen(pszLine);
-      while (iLen > 0 && pszLine[iLen - 1] > 0 && pszLine[iLen - 1] < 33) {
-        pszLine[iLen - 1] = '\0';
-        iLen--;
-      }
-
-      iNumInstances++;
-
-      ME_Sample* pmes = new ME_Sample();
-
-      char* p = strrchr(pszLine, ' ');
-      assert(p != NULL);
-      p[0] = '\0';
-      p++;
-      std::vector<std::string> vecContext;
-      SplitOnWhitespace(std::string(pszLine), &vecContext);
-
-      pmes->label = std::string(p);
-      for (size_t i = 0; i < vecContext.size(); i++)
-        pmes->add_feature(vecContext[i]);
-      pModel->add_training_sample((*pmes));
-      if (iNumInstances % 100000 == 0)
-        fprintf(stdout, "......Reading #Instances: %1d\n", iNumInstances);
-      delete pmes;
-    }
-    fprintf(stdout, "......Reading #Instances: %1d\n", iNumInstances);
-    fclose(fpIn);
-
-    if (strcmp(pszAlgorithm, "l1") == 0)
-      pModel->use_l1_regularizer(1.0);
-    else if (strcmp(pszAlgorithm, "l2") == 0)
-      pModel->use_l2_regularizer(1.0);
-    else
-      pModel->use_SGD();
-
-    pModel->train();
-    pModel->save_to_file(pszModelFName);
-
-    delete pModel;
-    fprintf(stdout, "......Finished Training\n");
-    fprintf(stdout, "......Model saved as %s\n", pszModelFName);
-    delete[] pszLine;
-  }
-
-  double fnEval(const char* pszContext, const char* pszOutcome) const {
-    std::vector<std::string> vecContext;
-    ME_Sample* pmes = new ME_Sample();
-    SplitOnWhitespace(std::string(pszContext), &vecContext);
-
-    for (size_t i = 0; i < vecContext.size(); i++)
-      pmes->add_feature(vecContext[i]);
-    std::vector<double> vecProb = m_pModel->classify(*pmes);
-    delete pmes;
-    int iLableID = m_pModel->get_class_id(pszOutcome);
-    return vecProb[iLableID];
-  }
-  void fnEval(const char* pszContext,
-              std::vector<std::pair<std::string, double> >& vecOutput) const {
-    std::vector<std::string> vecContext;
-    ME_Sample* pmes = new ME_Sample();
-    SplitOnWhitespace(std::string(pszContext), &vecContext);
-
-    vecOutput.clear();
-
-    for (size_t i = 0; i < vecContext.size(); i++)
-      pmes->add_feature(vecContext[i]);
-    std::vector<double> vecProb = m_pModel->classify(*pmes);
-
-    for (size_t i = 0; i < vecProb.size(); i++) {
-      std::string label = m_pModel->get_class_label(i);
-      vecOutput.push_back(make_pair(label, vecProb[i]));
-    }
-    delete pmes;
-  }
   void fnEval(const char* pszContext, std::vector<double>& vecOutput) const {
     std::vector<std::string> vecContext;
     ME_Sample* pmes = new ME_Sample();