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authorWu, Ke <wuke@cs.umd.edu>2014-12-17 15:41:32 -0500
committerWu, Ke <wuke@cs.umd.edu>2014-12-17 15:41:32 -0500
commit62249e8de1be27057649aa787b715af5727f8a7c (patch)
treedefd66b26121d2c9043efa9459ad9e7298d06c47 /decoder
parent0867694ffd2b2c8c7a23691ab74f8548c4baac72 (diff)
Move training routine out of ff_const_reorder_common.h
Diffstat (limited to 'decoder')
-rw-r--r--decoder/ff_const_reorder_common.h93
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();