diff options
Diffstat (limited to 'training/mira/kbest_cut_mira.cc')
| -rw-r--r-- | training/mira/kbest_cut_mira.cc | 8 |
1 files changed, 6 insertions, 2 deletions
diff --git a/training/mira/kbest_cut_mira.cc b/training/mira/kbest_cut_mira.cc index 56206593..724b1853 100644 --- a/training/mira/kbest_cut_mira.cc +++ b/training/mira/kbest_cut_mira.cc @@ -95,7 +95,8 @@ bool InitCommandLine(int argc, char** argv, po::variables_map* conf) { ("stream,t", "Stream mode (used for realtime)") ("weights_output,O",po::value<string>(),"Directory to write weights to") ("output_dir,D",po::value<string>(),"Directory to place output in") - ("decoder_config,c",po::value<string>(),"Decoder configuration file"); + ("decoder_config,c",po::value<string>(),"Decoder configuration file") + ("verbose,v",po::value<bool>()->zero_tokens(),"verbose stderr output"); po::options_description clo("Command line options"); clo.add_options() ("config", po::value<string>(), "Configuration file") @@ -621,6 +622,7 @@ int main(int argc, char** argv) { vector<string> corpus; + const bool VERBOSE = conf.count("verbose"); const string metric_name = conf["mt_metric"].as<string>(); optimizer = conf["optimizer"].as<int>(); fear_select = conf["fear"].as<int>(); @@ -783,7 +785,8 @@ int main(int argc, char** argv) { double margin = cur_bad.features.dot(dense_weights) - cur_good.features.dot(dense_weights); double mt_loss = (cur_good.mt_metric - cur_bad.mt_metric); const double loss = margin + mt_loss; - cerr << "LOSS: " << loss << " Margin:" << margin << " BLEUL:" << mt_loss << " " << cur_bad.features.dot(dense_weights) << " " << cur_good.features.dot(dense_weights) <<endl; + cerr << "LOSS: " << loss << " Margin:" << margin << " BLEUL:" << mt_loss << endl; + if (VERBOSE) cerr << cur_bad.features.dot(dense_weights) << " " << cur_good.features.dot(dense_weights) << endl; if (loss > 0.0 || !checkloss) { SparseVector<double> diff = cur_good.features; diff -= cur_bad.features; @@ -920,6 +923,7 @@ int main(int argc, char** argv) { lambdas += (cur_pair[1]->features) * step_size; lambdas -= (cur_pair[0]->features) * step_size; + if (VERBOSE) cerr << " Lambdas " << lambdas << endl; //reload weights based on update dense_weights.clear(); |