struct llm_bigram_bpe {
struct comparator {
- bool operator()(llm_bigram_bpe & l, llm_bigram_bpe & r) {
+ bool operator()(const llm_bigram_bpe & l, const llm_bigram_bpe & r) const {
return l.rank > r.rank || (l.rank == r.rank && l.left > r.left);
}
};
}
// probably not 100% correct
- // TODO: this is quite slow - how to make it more efficient?
- static std::vector<std::string> bpe_gpt2_preprocess(std::string text) {
+ static std::vector<std::string> bpe_gpt2_preprocess(const std::string & text) {
std::vector<std::string> words;
// ref: https://github.com/openai/gpt-2/blob/a74da5d99abaaba920de8131d64da2862a8f213b/src/encoder.py#L53
const std::string pattern = R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
const std::regex re(pattern);
- std::smatch m;
- while (std::regex_search(text, m, re)) {
- for (auto x : m) {
- words.push_back(x);
- }
- text = m.suffix();
+ auto words_begin = std::sregex_iterator(text.begin(), text.end(), re);
+ auto words_end = std::sregex_iterator();
+ auto n_words = std::distance(words_begin, words_end);
+ words.reserve(n_words);
+ for (auto it = words_begin; it != words_end; ++it) {
+ words.push_back(it->str());
}
-
return words;
+
}
const llama_vocab & vocab;