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main.cc
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/**
* Copyright (c) 2016-present, Facebook, Inc.
* All rights reserved.
*
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree. An additional grant
* of patent rights can be found in the PATENTS file in the same directory.
*/
#include <iostream>
#include "fasttext.h"
#include "args.h"
using namespace fasttext;
void printUsage() {
std::cerr
<< "usage: fasttext <command> <args>\n\n"
<< "The commands supported by fasttext are:\n\n"
<< " supervised train a supervised classifier\n"
<< " sent2vec train unsupervised sentence embeddings\n"
<< " quantize quantize a model to reduce the memory usage\n"
<< " test evaluate a supervised classifier\n"
<< " predict predict most likely labels\n"
<< " predict-prob predict most likely labels with probabilities\n"
<< " skipgram train a skipgram model\n"
<< " cbow train a cbow model\n"
<< " cbow-c+w-ngrams train a cbow model augmented with character and word ngrams\n"
<< " print-word-vectors print word vectors given a trained model\n"
<< " print-sentence-vectors print sentence vectors given a trained model\n"
<< " print-vocabulary-vectors print unigram vectors in vocabulary\n"
<< " print-vocabulary print word in vocabulary with count\n"
<< " nn query for nearest neighbors\n"
<< " nnSent query for nearest neighbors for sentences\n"
<< " analogies query for analogies\n"
<< " analogiesSent query for analogies for Sentences\n"
<< std::endl;
}
void printQuantizeUsage() {
std::cerr
<< "usage: fasttext quantize <args>"
<< std::endl;
}
void printTestUsage() {
std::cerr
<< "usage: fasttext test <model> <test-data> [<k>]\n\n"
<< " <model> model filename\n"
<< " <test-data> test data filename (if -, read from stdin)\n"
<< " <k> (optional; 1 by default) predict top k labels\n"
<< std::endl;
}
void printPredictUsage() {
std::cerr
<< "usage: fasttext predict[-prob] <model> <test-data> [<k>]\n\n"
<< " <model> model filename\n"
<< " <test-data> test data filename (if -, read from stdin)\n"
<< " <k> (optional; 1 by default) predict top k labels\n"
<< std::endl;
}
void printPrintWordVectorsUsage() {
std::cerr
<< "usage: fasttext print-word-vectors <model>\n\n"
<< " <model> model filename\n"
<< std::endl;
}
void printPrintSentenceVectorsUsage() {
std::cerr
<< "usage: fasttext print-sentence-vectors <model>\n\n"
<< " <model> model filename\n"
<< std::endl;
}
void printPrintVocabularyVectorsUsage() {
std::cerr
<< "usage: fasttext print-vocabulary-vectors <model>\n\n"
<< " <model> model filename\n"
<< " <matrix> embedding matrix: input|output\n"
<< std::endl;
}
void printPrintVocabularyUsage() {
std::cerr
<< "usage: fasttext print-vocabulary <model>\n\n"
<< " <model> model filename\n"
<< std::endl;
}
void printPrintNgramsUsage() {
std::cerr
<< "usage: fasttext print-ngrams <model> <word>\n\n"
<< " <model> model filename\n"
<< " <word> word to print\n"
<< std::endl;
}
void quantize(int argc, char** argv) {
std::shared_ptr<Args> a = std::make_shared<Args>();
if (argc < 3) {
printQuantizeUsage();
a->printHelp();
exit(EXIT_FAILURE);
}
a->parseArgs(argc, argv);
FastText fasttext;
fasttext.quantize(a);
exit(0);
}
void printNNUsage() {
std::cout
<< "usage: fasttext nn <model> <k>\n\n"
<< " <model> model filename\n"
<< " <k> (optional; 10 by default) predict top k labels\n"
<< std::endl;
}
void printNNSentUsage() {
std::cerr
<< "usage: fasttext nnSent <model> <corpus> <k>\n\n"
<< " <model> model filename\n"
<< " <corpus> corpus filename \n"
<< " <k> (optional; 10 by default) predict top k labels\n"
<< std::endl;
std::cout<<"NOTE : A corpus file is required to find similar sentences."<<std::endl;
}
void printAnalogiesUsage() {
std::cout
<< "usage: fasttext analogies <model> <k>\n\n"
<< " <model> model filename\n"
<< " <k> (optional; 10 by default) predict top k labels\n"
<< std::endl;
}
void printAnalogiesSentUsage() {
std::cout
<< "usage: fasttext analogiesSent <model> <corpus> <k>\n\n"
<< " <model> model filename\n"
<< " <corpus> corpus filename \n"
<< " <k> (optional; 10 by default) predict top k labels\n"
<< std::endl;
std::cout<<"NOTE : A corpus file is required to find similar sentences."<<std::endl;
}
void test(int argc, char** argv) {
if (argc < 4 || argc > 5) {
printTestUsage();
exit(EXIT_FAILURE);
}
int32_t k = 1;
if (argc >= 5) {
k = atoi(argv[4]);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
std::string infile(argv[3]);
if (infile == "-") {
fasttext.test(std::cin, k);
} else {
std::ifstream ifs(infile);
if (!ifs.is_open()) {
std::cerr << "Test file cannot be opened!" << std::endl;
exit(EXIT_FAILURE);
}
fasttext.test(ifs, k);
ifs.close();
}
exit(0);
}
void predict(int argc, char** argv) {
if (argc < 4 || argc > 5) {
printPredictUsage();
exit(EXIT_FAILURE);
}
int32_t k = 1;
if (argc >= 5) {
k = atoi(argv[4]);
}
bool print_prob = std::string(argv[1]) == "predict-prob";
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
std::string infile(argv[3]);
if (infile == "-") {
fasttext.predict(std::cin, k, print_prob);
} else {
std::ifstream ifs(infile);
if (!ifs.is_open()) {
std::cerr << "Input file cannot be opened!" << std::endl;
exit(EXIT_FAILURE);
}
fasttext.predict(ifs, k, print_prob);
ifs.close();
}
exit(0);
}
void printWordVectors(int argc, char** argv) {
if (argc != 3) {
printPrintWordVectorsUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
fasttext.printWordVectors();
exit(0);
}
void printSentenceVectors(int argc, char** argv) {
if (argc != 3) {
printPrintSentenceVectorsUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
fasttext.printSentenceVectors();
exit(0);
}
void printVocabularyVectors(int argc, char** argv) {
if (argc != 4) {
printPrintVocabularyVectorsUsage();
exit(EXIT_FAILURE);
}
std::string matrix_type = std::string(argv[3]);
if (matrix_type != "input" && matrix_type != "output") {
printPrintVocabularyVectorsUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
fasttext.printVocabularyVectors(matrix_type == "input");
exit(0);
}
void printVocabulary(int argc, char** argv) {
if (argc != 3) {
printPrintVocabularyUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
std::vector<std::string> vocabulary = fasttext.getVocab();
std::vector<int64_t> counts = fasttext.getUnigramsCounts();
for (int i = 0; i < vocabulary.size(); i++) {
std::cout << vocabulary[i] << " " << counts[i] << std::endl;
}
exit(0);
}
void printNgrams(int argc, char** argv) {
if (argc != 4) {
printPrintNgramsUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
fasttext.ngramVectors(std::string(argv[3]));
exit(0);
}
void nn(int argc, char** argv) {
int32_t k;
if (argc == 3) {
k = 10;
} else if (argc == 4) {
k = atoi(argv[3]);
} else {
printNNUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
fasttext.nn(k);
exit(0);
}
void nnSent(int argc, char** argv) {
int32_t k;
if (argc == 4) {
k = 10;
} else if (argc == 5) {
k = atoi(argv[4]);
} else {
printNNSentUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
fasttext.nnSent(k,std::string(argv[3]));
exit(0);
}
void analogies(int argc, char** argv) {
int32_t k;
if (argc == 3) {
k = 10;
} else if (argc == 4) {
k = atoi(argv[3]);
} else {
printAnalogiesUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
fasttext.analogies(k);
exit(0);
}
void analogiesSent(int argc, char** argv) {
int32_t k;
if (argc == 4) {
k = 10;
} else if (argc == 5) {
k = atoi(argv[4]);
} else {
printAnalogiesSentUsage();
exit(EXIT_FAILURE);
}
FastText fasttext;
fasttext.loadModel(std::string(argv[2]));
fasttext.analogiesSent(k,std::string(argv[3]));
exit(0);
}
void train(int argc, char** argv) {
std::shared_ptr<Args> a = std::make_shared<Args>();
a->parseArgs(argc, argv);
FastText fasttext;
fasttext.train(a);
}
void saveDict(int argc, char** argv) {
std::shared_ptr<Args> a = std::make_shared<Args>();
a->parseArgs(argc, argv);
FastText fasttext;
fasttext.trainDict(a);
}
void trainFromDict(int argc, char** argv) {
std::shared_ptr<Args> a = std::make_shared<Args>();
a->parseArgs(argc, argv);
FastText fasttext;
fasttext.savedDictTrain(a);
}
int main(int argc, char** argv) {
if (argc < 2) {
printUsage();
exit(EXIT_FAILURE);
}
std::string command(argv[1]);
if (command == "skipgram" || command == "cbow" || command == "supervised" ||
command == "sent2vec" || command == "cbow-c+w-ngrams") {
train(argc, argv);
} else if (command == "test") {
test(argc, argv);
} else if (command == "saveDict") {
saveDict(argc, argv);
} else if (command == "sent2vecFromDict") {
trainFromDict(argc, argv);
} else if (command == "quantize") {
quantize(argc, argv);
} else if (command == "print-word-vectors") {
printWordVectors(argc, argv);
} else if (command == "print-sentence-vectors") {
printSentenceVectors(argc, argv);
} else if (command == "print-vocabulary-vectors") {
printVocabularyVectors(argc, argv);
} else if (command == "print-vocabulary") {
printVocabulary(argc, argv);
} else if (command == "print-ngrams") {
printNgrams(argc, argv);
} else if (command == "nn") {
nn(argc, argv);
} else if (command == "nnSent") {
nnSent(argc, argv);
} else if (command == "analogies") {
analogies(argc, argv);
} else if (command == "analogiesSent") {
analogiesSent(argc, argv);
} else if (command == "predict" || command == "predict-prob" ) {
predict(argc, argv);
} else {
printUsage();
exit(EXIT_FAILURE);
}
return 0;
}