Merge branch 'const_reorder_2' into softsyn_2

1 files changed, 67 insertions, 0 deletions

diff --git a/training/const_reorder/trainer.cc b/training/const_reorder/trainer.cc
new file mode 100644
index 00000000..89bd7479
--- /dev/null
+++ b/training/const_reorder/trainer.cc
@@ -0,0 +1,67 @@
+#include "trainer.h"
+
+Tsuruoka_Maxent_Trainer::Tsuruoka_Maxent_Trainer()
+    : const_reorder::Tsuruoka_Maxent(NULL) {}
+
+void Tsuruoka_Maxent_Trainer::fnTrain(const char* pszInstanceFName,
+                                      const char* pszAlgorithm,
+                                      const char* pszModelFName) {
+  assert(strcmp(pszAlgorithm, "l1") == 0 || strcmp(pszAlgorithm, "l2") == 0 ||
+         strcmp(pszAlgorithm, "sgd") == 0 || strcmp(pszAlgorithm, "SGD") == 0);
+  FILE* fpIn = fopen(pszInstanceFName, "r");
+
+  maxent::ME_Model* pModel = new maxent::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++;
+
+    maxent::ME_Sample* pmes = new maxent::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;
+}