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
}
