wang2vec: move to the right position
diff --git a/word2phrase.c b/word2phrase.c
new file mode 100644
index 0000000..24238bc
--- /dev/null
+++ b/word2phrase.c
@@ -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;
+}