// Copyright 2013 Google Inc. All Rights Reserved.

//

// Licensed under the Apache License, Version 2.0 (the "License");

// you may not use this file except in compliance with the License.

// You may obtain a copy of the License at

//

// http://www.apache.org/licenses/LICENSE-2.0

//

// Unless required by applicable law or agreed to in writing, software

// distributed under the License is distributed on an "AS IS" BASIS,

// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

// See the License for the specific language governing permissions and

// limitations under the License.

#include <stdio.h>

#include <stdlib.h>

#include <string.h>

#include <math.h>

#include <pthread.h>

#define MAX_STRING 60

const int vocab_hash_size = 500000000; // Maximum 500M entries in the vocabulary

typedef float real; // Precision of float numbers

struct vocab_word {

long long cn;

char *word;

};

char train_file[MAX_STRING], output_file[MAX_STRING];

struct vocab_word *vocab;

int debug_mode = 2, min_count = 5, *vocab_hash, min_reduce = 1;

long long vocab_max_size = 10000, vocab_size = 0;

long long train_words = 0;

real threshold = 100;

unsigned long long next_random = 1;

// Reads a single word from a file, assuming space + tab + EOL to be word boundaries

void ReadWord(char *word, FILE *fin) {

int a = 0, ch;

while (!feof(fin)) {

ch = fgetc(fin);

if (ch == 13) continue;

if ((ch == ' ') || (ch == '\t') || (ch == '\n')) {

if (a > 0) {

if (ch == '\n') ungetc(ch, fin);

break;

}

if (ch == '\n') {

strcpy(word, (char *)"</s>");

return;

} else continue;

}

word[a] = ch;

a++;

if (a >= MAX_STRING - 1) a--; // Truncate too long words

}

word[a] = 0;

}

// Returns hash value of a word

int GetWordHash(char *word) {

unsigned long long a, hash = 1;

for (a = 0; a < strlen(word); a++) hash = hash * 257 + word[a];

hash = hash % vocab_hash_size;

return hash;

}

// Returns position of a word in the vocabulary; if the word is not found, returns -1

int SearchVocab(char *word) {

unsigned int hash = GetWordHash(word);

while (1) {

if (vocab_hash[hash] == -1) return -1;

if (!strcmp(word, vocab[vocab_hash[hash]].word)) return vocab_hash[hash];

hash = (hash + 1) % vocab_hash_size;

}

return -1;

}

// Reads a word and returns its index in the vocabulary

int ReadWordIndex(FILE *fin) {

char word[MAX_STRING];

ReadWord(word, fin);

if (feof(fin)) return -1;

return SearchVocab(word);

}

// Adds a word to the vocabulary

int AddWordToVocab(char *word) {

unsigned int hash, length = strlen(word) + 1;

if (length > MAX_STRING) length = MAX_STRING;

vocab[vocab_size].word = (char *)calloc(length, sizeof(char));

strcpy(vocab[vocab_size].word, word);

vocab[vocab_size].cn = 0;

vocab_size++;

// Reallocate memory if needed

if (vocab_size + 2 >= vocab_max_size) {

vocab_max_size += 10000;

vocab=(struct vocab_word *)realloc(vocab, vocab_max_size * sizeof(struct vocab_word));

}

hash = GetWordHash(word);

while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;

vocab_hash[hash]=vocab_size - 1;

return vocab_size - 1;

}

// Used later for sorting by word counts

int VocabCompare(const void *a, const void *b) {

return ((struct vocab_word *)b)->cn - ((struct vocab_word *)a)->cn;

}

// Sorts the vocabulary by frequency using word counts

void SortVocab() {

int a;

unsigned int hash;

// Sort the vocabulary and keep </s> at the first position

qsort(&vocab[1], vocab_size - 1, sizeof(struct vocab_word), VocabCompare);

for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;

for (a = 0; a < vocab_size; a++) {

// Words occuring less than min_count times will be discarded from the vocab

if (vocab[a].cn < min_count) {

vocab_size--;

free(vocab[vocab_size].word);

} else {

// Hash will be re-computed, as after the sorting it is not actual

hash = GetWordHash(vocab[a].word);

while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;

vocab_hash[hash] = a;

}

}

vocab = (struct vocab_word *)realloc(vocab, vocab_size * sizeof(struct vocab_word));

}

// Reduces the vocabulary by removing infrequent tokens

void ReduceVocab() {

int a, b = 0;

unsigned int hash;

for (a = 0; a < vocab_size; a++) if (vocab[a].cn > min_reduce) {

vocab[b].cn = vocab[a].cn;

vocab[b].word = vocab[a].word;

b++;

} else free(vocab[a].word);

vocab_size = b;

for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;

for (a = 0; a < vocab_size; a++) {

// Hash will be re-computed, as it is not actual

hash = GetWordHash(vocab[a].word);

while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;

vocab_hash[hash] = a;

}

fflush(stdout);

min_reduce++;

}

void LearnVocabFromTrainFile() {

char word[MAX_STRING], last_word[MAX_STRING], bigram_word[MAX_STRING * 2];

FILE *fin;

long long a, i, start = 1;

for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;

fin = fopen(train_file, "rb");

if (fin == NULL) {

printf("ERROR: training data file not found!\n");

exit(1);

}

vocab_size = 0;

AddWordToVocab((char *)"</s>");

while (1) {

ReadWord(word, fin);

if (feof(fin)) break;

if (!strcmp(word, "</s>")) {

start = 1;

continue;

} else start = 0;

train_words++;

if ((debug_mode > 1) && (train_words % 100000 == 0)) {

printf("Words processed: %lldK Vocab size: %lldK %c", train_words / 1000, vocab_size / 1000, 13);

fflush(stdout);

}

i = SearchVocab(word);

if (i == -1) {

a = AddWordToVocab(word);

vocab[a].cn = 1;

} else vocab[i].cn++;

if (start) continue;

sprintf(bigram_word, "%s_%s", last_word, word);

bigram_word[MAX_STRING - 1] = 0;

strcpy(last_word, word);

i = SearchVocab(bigram_word);

if (i == -1) {

a = AddWordToVocab(bigram_word);

vocab[a].cn = 1;

} else vocab[i].cn++;

if (vocab_size > vocab_hash_size * 0.7) ReduceVocab();

}

SortVocab();

if (debug_mode > 0) {

printf("\nVocab size (unigrams + bigrams): %lld\n", vocab_size);

printf("Words in train file: %lld\n", train_words);

}

fclose(fin);

}

void TrainModel() {

long long pa = 0, pb = 0, pab = 0, oov, i, li = -1, cn = 0;

char word[MAX_STRING], last_word[MAX_STRING], bigram_word[MAX_STRING * 2];

real score;

FILE *fo, *fin;

printf("Starting training using file %s\n", train_file);

LearnVocabFromTrainFile();

fin = fopen(train_file, "rb");

fo = fopen(output_file, "wb");

word[0] = 0;

while (1) {

strcpy(last_word, word);

ReadWord(word, fin);

if (feof(fin)) break;

if (!strcmp(word, "</s>")) {

fprintf(fo, "\n");

continue;

}

cn++;

if ((debug_mode > 1) && (cn % 100000 == 0)) {

printf("Words written: %lldK%c", cn / 1000, 13);

fflush(stdout);

}

oov = 0;

i = SearchVocab(word);

if (i == -1) oov = 1; else pb = vocab[i].cn;

if (li == -1) oov = 1;

li = i;

sprintf(bigram_word, "%s_%s", last_word, word);

bigram_word[MAX_STRING - 1] = 0;

i = SearchVocab(bigram_word);

if (i == -1) oov = 1; else pab = vocab[i].cn;

if (pa < min_count) oov = 1;

if (pb < min_count) oov = 1;

if (oov) score = 0; else score = (pab - min_count) / (real)pa / (real)pb * (real)train_words;

if (score > threshold) {

fprintf(fo, "_%s", word);

pb = 0;

} else fprintf(fo, " %s", word);

pa = pb;

}

fclose(fo);

fclose(fin);

}

int ArgPos(char *str, int argc, char **argv) {

int a;

for (a = 1; a < argc; a++) if (!strcmp(str, argv[a])) {

if (a == argc - 1) {

printf("Argument missing for %s\n", str);

exit(1);

}

return a;

}

return -1;

}

int main(int argc, char **argv) {

int i;

if (argc == 1) {

printf("WORD2PHRASE tool v0.1a\n\n");

printf("Options:\n");

printf("Parameters for training:\n");

printf("\t-train <file>\n");

printf("\t\tUse text data from <file> to train the model\n");

printf("\t-output <file>\n");

printf("\t\tUse <file> to save the resulting word vectors / word clusters / phrases\n");

printf("\t-min-count <int>\n");

printf("\t\tThis will discard words that appear less than <int> times; default is 5\n");

printf("\t-threshold <float>\n");

printf("\t\t The <float> value represents threshold for forming the phrases (higher means less phrases); default 100\n");

printf("\t-debug <int>\n");

printf("\t\tSet the debug mode (default = 2 = more info during training)\n");

printf("\nExamples:\n");

printf("./word2phrase -train text.txt -output phrases.txt -threshold 100 -debug 2\n\n");

return 0;

}

if ((i = ArgPos((char *)"-train", argc, argv)) > 0) strcpy(train_file, argv[i + 1]);

if ((i = ArgPos((char *)"-debug", argc, argv)) > 0) debug_mode = atoi(argv[i + 1]);

if ((i = ArgPos((char *)"-output", argc, argv)) > 0) strcpy(output_file, argv[i + 1]);

if ((i = ArgPos((char *)"-min-count", argc, argv)) > 0) min_count = atoi(argv[i + 1]);

if ((i = ArgPos((char *)"-threshold", argc, argv)) > 0) threshold = atof(argv[i + 1]);

vocab = (struct vocab_word *)calloc(vocab_max_size, sizeof(struct vocab_word));

vocab_hash = (int *)calloc(vocab_hash_size, sizeof(int));

TrainModel();

return 0;

}