aa
This commit is contained in:
tmikolov
parent
06dca5f0db
commit
35a3c66ba3
292
word2phrase.c
Normal file
292
word2phrase.c
Normal file
@ -0,0 +1,292 @@
|
||||
// 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;
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user