#ifndef CTRANSFORMERS_MODELS_COMMON_H_ #define CTRANSFORMERS_MODELS_COMMON_H_ #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include "ggml/ggml.h" // https://github.com/ggerganov/ggml/blob/master/examples/common.cpp struct gpt_vocab { using id = int32_t; using token = std::string; std::map token_to_id; std::map id_to_token; std::vector special_tokens; void add_special_token(const std::string &token) { special_tokens.push_back(token); } }; std::string convert_to_utf8(const std::wstring &input) { std::wstring_convert> converter; return converter.to_bytes(input); } std::wstring convert_to_wstring(const std::string &input) { std::wstring_convert> converter; return converter.from_bytes(input); } void gpt_split_words(std::string str, std::vector &words) { 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(str, m, re)) { for (auto x : m) { words.push_back(x); } str = m.suffix(); } } std::vector gpt_tokenize(const gpt_vocab &vocab, const std::string &text) { std::vector words; // first split the text into words { std::string str = text; // Generate the subpattern from the special_tokens vector if it's not empty if (!vocab.special_tokens.empty()) { const std::regex escape(R"([\[\\\^\$\.\|\?\*\+\(\)\{\}])"); std::string special_tokens_subpattern; for (const auto &token : vocab.special_tokens) { if (!special_tokens_subpattern.empty()) { special_tokens_subpattern += "|"; } special_tokens_subpattern += std::regex_replace(token, escape, R"(\$&)"); } std::regex re(special_tokens_subpattern); std::smatch m; // Split the text by special tokens. while (std::regex_search(str, m, re)) { // Split the substrings in-between special tokens into words. gpt_split_words(m.prefix(), words); // Add matched special tokens as words. for (auto x : m) { words.push_back(x); } str = m.suffix(); } // Remaining text without special tokens will be handled below. } gpt_split_words(str, words); } // find the longest token that forms each word in words: std::vector tokens; for (const auto &word : words) { for (int i = 0; i < (int)word.size();) { for (int j = word.size() - 1; j >= i; j--) { auto cand = word.substr(i, j - i + 1); auto it = vocab.token_to_id.find(cand); if (it != vocab.token_to_id.end()) { // word.substr(i, j-i+1) in vocab tokens.push_back(it->second); i = j + 1; break; } else if (j == i) { // word.substr(i, 1) has no matching fprintf(stderr, "%s: unknown token '%s'\n", __func__, word.substr(i, 1).data()); i++; } } } } return tokens; } gpt_vocab::id gpt_sample_top_k_top_p( const gpt_vocab &vocab, const float *logits, int top_k, double top_p, double temp, const float repetition_penalty, const std::unordered_set &recent_tokens, std::mt19937 &rng) { int n_logits = vocab.id_to_token.size(); std::vector> logits_id; logits_id.reserve(n_logits); { const double scale = 1.0 / temp; for (int i = 0; i < n_logits; ++i) { logits_id.push_back(std::make_pair(logits[i] * scale, i)); } } for (const gpt_vocab::id token : recent_tokens) { // https://github.com/ggerganov/llama.cpp/blob/3e5aa8a1c44051153d6d7b3eeca2f4b4e5fb310c/llama.cpp#L1690-L1717 // https://github.com/ggerganov/llama.cpp/blob/3e5aa8a1c44051153d6d7b3eeca2f4b4e5fb310c/examples/main/main.cpp#L432-L434 double &logit = logits_id[token].first; if (logit <= 0) { logit *= repetition_penalty; } else { logit /= repetition_penalty; } } // find the top K tokens std::partial_sort(logits_id.begin(), logits_id.begin() + top_k, logits_id.end(), [](const std::pair &a, const std::pair &b) { return a.first > b.first; }); logits_id.resize(top_k); double maxl = -INFINITY; for (const auto &kv : logits_id) { maxl = std::max(maxl, kv.first); } // compute probs for the top K tokens std::vector probs; probs.reserve(logits_id.size()); double sum = 0.0; for (const auto &kv : logits_id) { double p = exp(kv.first - maxl); probs.push_back(p); sum += p; } // normalize the probs for (auto &p : probs) { p /= sum; } if (top_p < 1.0f) { double cumsum = 0.0f; for (int i = 0; i < top_k; i++) { cumsum += probs[i]; if (cumsum >= top_p) { top_k = i + 1; probs.resize(top_k); logits_id.resize(top_k); break; } } cumsum = 1.0 / cumsum; for (int i = 0; i < (int)probs.size(); i++) { probs[i] *= cumsum; } } std::discrete_distribution<> dist(probs.begin(), probs.end()); int idx = dist(rng); return logits_id[idx].second; } #endif