int main(int argc, char* argv[]) { std::string trainFile = "", devFile = "", testFile = "", modelFile = ""; std::string wordEmbFile = "", charEmbFile = "", optionFile = ""; std::string outputFile = ""; bool bTrain = false; dsr::Argument_helper ah; ah.new_flag("l", "learn", "train or test", bTrain); ah.new_named_string("train", "trainCorpus", "named_string", "training corpus to train a model, must when training", trainFile); ah.new_named_string("dev", "devCorpus", "named_string", "development corpus to train a model, optional when training", devFile); ah.new_named_string("test", "testCorpus", "named_string", "testing corpus to train a model or input file to test a model, optional when training and must when testing", testFile); ah.new_named_string("model", "modelFile", "named_string", "model file, must when training and testing", modelFile); ah.new_named_string("word", "wordEmbFile", "named_string", "pretrained word embedding file to train a model, optional when training", wordEmbFile); ah.new_named_string("char", "charEmbFile", "named_string", "pretrained char embedding file to train a model, optional when training", charEmbFile); ah.new_named_string("option", "optionFile", "named_string", "option file to train a model, optional when training", optionFile); ah.new_named_string("output", "outputFile", "named_string", "output file to test, must when testing", outputFile); ah.process(argc, argv); Labeler tagger; if (bTrain) { tagger.train(trainFile, devFile, testFile, modelFile, optionFile, wordEmbFile, charEmbFile); } else { tagger.test(testFile, outputFile, modelFile); } }
int main(int argc, char* argv[]) { #if USE_CUDA==1 InitTensorEngine(); #else InitTensorEngine<cpu>(); #endif std::string trainFile = "", devFile = "", testFile = "", modelFile = ""; std::string wordEmbFile = "", charEmbFile = "", optionFile = ""; std::string outputFile = ""; bool bTrain = false; dsr::Argument_helper ah; ah.new_flag("l", "learn", "train or test", bTrain); ah.new_named_string("train", "trainCorpus", "named_string", "training corpus to train a model, must when training", trainFile); ah.new_named_string("dev", "devCorpus", "named_string", "development corpus to train a model, optional when training", devFile); ah.new_named_string("test", "testCorpus", "named_string", "testing corpus to train a model or input file to test a model, optional when training and must when testing", testFile); ah.new_named_string("model", "modelFile", "named_string", "model file, must when training and testing", modelFile); ah.new_named_string("word", "wordEmbFile", "named_string", "pretrained word embedding file to train a model, optional when training", wordEmbFile); ah.new_named_string("char", "charEmbFile", "named_string", "pretrained char embedding file to train a model, optional when training", charEmbFile); ah.new_named_string("option", "optionFile", "named_string", "option file to train a model, optional when training", optionFile); ah.new_named_string("output", "outputFile", "named_string", "output file to test, must when testing", outputFile); ah.process(argc, argv); Labeler tagger; if (bTrain) { tagger.train(trainFile, devFile, testFile, modelFile, optionFile, wordEmbFile, charEmbFile); } else { tagger.test(testFile, outputFile, modelFile); } //test(argv); //ah.write_values(std::cout); #if USE_CUDA==1 ShutdownTensorEngine(); #else ShutdownTensorEngine<cpu>(); #endif }