diff options
| -rw-r--r-- | training/dtrain/dtrain_net_interface.cc | 7 | ||||
| -rw-r--r-- | training/dtrain/dtrain_net_interface.h | 1 | ||||
| -rw-r--r-- | training/dtrain/sample.h | 3 |
3 files changed, 10 insertions, 1 deletions
diff --git a/training/dtrain/dtrain_net_interface.cc b/training/dtrain/dtrain_net_interface.cc index 38fad160..e21920d0 100644 --- a/training/dtrain/dtrain_net_interface.cc +++ b/training/dtrain/dtrain_net_interface.cc @@ -27,6 +27,7 @@ main(int argc, char** argv) vector<string> dense_features; boost::split(dense_features, conf["dense_features"].as<string>(), boost::is_any_of(" ")); + const bool output_derivation = conf["output_derivation"].as<bool>(); // setup decoder register_feature_functions(); @@ -125,7 +126,11 @@ main(int argc, char** argv) vector<ScoredHyp>* samples = observer->GetSamples(); ostringstream os; cerr << "[dtrain] 1best features " << (*samples)[0].f << endl; - PrintWordIDVec((*samples)[0].w, os); + if (output_derivation) { + os << observer->GetViterbiTreeString() << endl; + } else { + PrintWordIDVec((*samples)[0].w, os); + } sock.send(os.str().c_str(), os.str().size()+1, 0); cerr << "[dtrain] done translating, looping again" << endl; continue; diff --git a/training/dtrain/dtrain_net_interface.h b/training/dtrain/dtrain_net_interface.h index eb0aa668..3c7665a2 100644 --- a/training/dtrain/dtrain_net_interface.h +++ b/training/dtrain/dtrain_net_interface.h @@ -64,6 +64,7 @@ dtrain_net_init(int argc, char** argv, po::variables_map* conf) ("input_weights,w", po::value<string>(), "input weights file") ("learning_rate,l", po::value<weight_t>()->default_value(1.0), "learning rate") ("learning_rate_sparse,l", po::value<weight_t>()->default_value(1.0), "learning rate for sparse features") + ("output_derivation,E", po::bool_switch()->default_value(false), "output derivation, not viterbi str") ("dense_features,D", po::value<string>()->default_value("EgivenFCoherent SampleCountF CountEF MaxLexFgivenE MaxLexEgivenF IsSingletonF IsSingletonFE Glue WordPenalty PassThrough LanguageModel LanguageModel_OOV Shape_S01111_T11011 Shape_S11110_T11011 Shape_S11100_T11000 Shape_S01110_T01110 Shape_S01111_T01111 Shape_S01100_T11000 Shape_S10000_T10000 Shape_S11100_T11100 Shape_S11110_T11110 Shape_S11110_T11010 Shape_S01100_T11100 Shape_S01000_T01000 Shape_S01010_T01010 Shape_S01111_T01011 Shape_S01100_T01100 Shape_S01110_T11010 Shape_S11000_T11000 Shape_S11000_T01100 IsSupportedOnline ForceRule"), "dense features") ("debug_output,d", po::value<string>()->default_value(""), "file for debug output"); diff --git a/training/dtrain/sample.h b/training/dtrain/sample.h index 03cc82c3..e24b65cf 100644 --- a/training/dtrain/sample.h +++ b/training/dtrain/sample.h @@ -16,6 +16,7 @@ struct ScoredKbest : public DecoderObserver PerSentenceBleuScorer* scorer_; vector<Ngrams>* ref_ngs_; vector<size_t>* ref_ls_; + string viterbi_tree_str; ScoredKbest(const size_t k, PerSentenceBleuScorer* scorer) : k_(k), scorer_(scorer) {} @@ -40,6 +41,7 @@ struct ScoredKbest : public DecoderObserver samples_.push_back(h); effective_sz_++; feature_count_ += h.f.size(); + viterbi_tree_str = hg->show_viterbi_tree(false); } } @@ -51,6 +53,7 @@ struct ScoredKbest : public DecoderObserver } inline size_t GetFeatureCount() { return feature_count_; } inline size_t GetSize() { return effective_sz_; } + inline string GetViterbiTreeString() { return viterbi_tree_str; } }; } // namespace |