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#ifndef CTRANSFORMERS_MODELS_COMMON_H_
#define CTRANSFORMERS_MODELS_COMMON_H_
#include <algorithm>
#include <cmath>
#include <codecvt>
#include <cstdio>
#include <cstring>
#include <fstream>
#include <locale>
#include <map>
#include <queue>
#include <random>
#include <regex>
#include <string>
#include <thread>
#include <unordered_set>
#include <unordered_map>
#include <vector>
#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, id> token_to_id;
std::map<id, token> id_to_token;
std::vector<std::string> 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<std::codecvt_utf8<wchar_t>> converter;
return converter.to_bytes(input);
}
std::wstring convert_to_wstring(const std::string &input) {
std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
return converter.from_bytes(input);
}
void gpt_split_words(std::string str, std::vector<std::string> &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_vocab::id> gpt_tokenize(const gpt_vocab &vocab,
const std::string &text) {
std::vector<std::string> 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<gpt_vocab::id> 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<gpt_vocab::id> &recent_tokens, std::mt19937 &rng) {
int n_logits = vocab.id_to_token.size();
std::vector<std::pair<double, gpt_vocab::id>> 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<double, gpt_vocab::id> &a,
const std::pair<double, gpt_vocab::id> &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<double> 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
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