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- #include "utils.h"
- #include <cassert>
- #include <cstring>
- #include <fstream>
- #include <regex>
- #if defined(_MSC_VER) || defined(__MINGW32__)
- #include <malloc.h> // using malloc.h with MSC/MINGW
- #elif !defined(__FreeBSD__)
- #include <alloca.h>
- #endif
- bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
- for (int i = 1; i < argc; i++) {
- std::string arg = argv[i];
- if (arg == "-s" || arg == "--seed") {
- params.seed = std::stoi(argv[++i]);
- } else if (arg == "-t" || arg == "--threads") {
- params.n_threads = std::stoi(argv[++i]);
- } else if (arg == "-p" || arg == "--prompt") {
- params.prompt = argv[++i];
- } else if (arg == "-n" || arg == "--n_predict") {
- params.n_predict = std::stoi(argv[++i]);
- } else if (arg == "--top_k") {
- params.top_k = std::stoi(argv[++i]);
- } else if (arg == "--top_p") {
- params.top_p = std::stof(argv[++i]);
- } else if (arg == "--temp") {
- params.temp = std::stof(argv[++i]);
- } else if (arg == "--repeat_last_n") {
- params.repeat_last_n = std::stoi(argv[++i]);
- } else if (arg == "--repeat_penalty") {
- params.repeat_penalty = std::stof(argv[++i]);
- } else if (arg == "-b" || arg == "--batch_size") {
- params.n_batch = std::stoi(argv[++i]);
- } else if (arg == "-m" || arg == "--model") {
- params.model = argv[++i];
- } else if (arg == "-h" || arg == "--help") {
- gpt_print_usage(argc, argv, params);
- exit(0);
- } else {
- fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
- gpt_print_usage(argc, argv, params);
- exit(0);
- }
- }
- return true;
- }
- void gpt_print_usage(int argc, char ** argv, const gpt_params & params) {
- fprintf(stderr, "usage: %s [options]\n", argv[0]);
- fprintf(stderr, "\n");
- fprintf(stderr, "options:\n");
- fprintf(stderr, " -h, --help show this help message and exit\n");
- fprintf(stderr, " -s SEED, --seed SEED RNG seed (default: -1)\n");
- fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
- fprintf(stderr, " -p PROMPT, --prompt PROMPT\n");
- fprintf(stderr, " prompt to start generation with (default: random)\n");
- fprintf(stderr, " -n N, --n_predict N number of tokens to predict (default: %d)\n", params.n_predict);
- fprintf(stderr, " --top_k N top-k sampling (default: %d)\n", params.top_k);
- fprintf(stderr, " --top_p N top-p sampling (default: %.1f)\n", params.top_p);
- fprintf(stderr, " --repeat_last_n N last n tokens to consider for penalize (default: %d)\n", params.repeat_last_n);
- fprintf(stderr, " --repeat_penalty N penalize repeat sequence of tokens (default: %.1f)\n", params.repeat_penalty);
- fprintf(stderr, " --temp N temperature (default: %.1f)\n", params.temp);
- fprintf(stderr, " -b N, --batch_size N batch size for prompt processing (default: %d)\n", params.n_batch);
- fprintf(stderr, " -m FNAME, --model FNAME\n");
- fprintf(stderr, " model path (default: %s)\n", params.model.c_str());
- fprintf(stderr, "\n");
- }
- std::string gpt_random_prompt(std::mt19937 & rng) {
- const int r = rng() % 10;
- switch (r) {
- case 0: return "So";
- case 1: return "Once upon a time";
- case 2: return "When";
- case 3: return "The";
- case 4: return "After";
- case 5: return "If";
- case 6: return "import";
- case 7: return "He";
- case 8: return "She";
- case 9: return "They";
- default: return "To";
- }
- return "The";
- }
- void replace(std::string & str, const std::string & needle, const std::string & replacement) {
- size_t pos = 0;
- while ((pos = str.find(needle, pos)) != std::string::npos) {
- str.replace(pos, needle.length(), replacement);
- pos += replacement.length();
- }
- }
- std::map<std::string, int32_t> json_parse(const std::string & fname) {
- std::map<std::string, int32_t> result;
- // read file into string
- std::string json;
- {
- std::ifstream ifs(fname);
- if (!ifs) {
- fprintf(stderr, "Failed to open %s\n", fname.c_str());
- exit(1);
- }
- json = std::string((std::istreambuf_iterator<char>(ifs)),
- (std::istreambuf_iterator<char>()));
- }
- if (json[0] != '{') {
- return result;
- }
- // parse json
- {
- bool has_key = false;
- bool in_token = false;
- std::string str_key = "";
- std::string str_val = "";
- int n = json.size();
- for (int i = 1; i < n; ++i) {
- if (!in_token) {
- if (json[i] == ' ') continue;
- if (json[i] == '"') {
- in_token = true;
- continue;
- }
- } else {
- if (json[i] == '\\' && i+1 < n) {
- if (has_key == false) {
- str_key += json[i];
- } else {
- str_val += json[i];
- }
- ++i;
- } else if (json[i] == '"') {
- if (has_key == false) {
- has_key = true;
- ++i;
- while (json[i] == ' ') ++i;
- ++i; // :
- while (json[i] == ' ') ++i;
- if (json[i] != '\"') {
- while (json[i] != ',' && json[i] != '}') {
- str_val += json[i++];
- }
- has_key = false;
- } else {
- in_token = true;
- continue;
- }
- } else {
- has_key = false;
- }
- ::replace(str_key, "\\u0120", " " ); // \u0120 -> space
- ::replace(str_key, "\\u010a", "\n"); // \u010a -> new line
- ::replace(str_key, "\\\"", "\""); // \\\" -> "
- try {
- result[str_key] = std::stoi(str_val);
- } catch (...) {
- //fprintf(stderr, "%s: ignoring key '%s' with value '%s'\n", fname.c_str(), str_key.c_str(), str_val.c_str());
- }
- str_key = "";
- str_val = "";
- in_token = false;
- continue;
- }
- if (has_key == false) {
- str_key += json[i];
- } else {
- str_val += json[i];
- }
- }
- }
- }
- return result;
- }
- 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;
- std::string pat = R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
- std::regex re(pat);
- std::smatch m;
- while (std::regex_search(str, m, re)) {
- for (auto x : m) {
- words.push_back(x);
- }
- str = m.suffix();
- }
- }
- // find the longest tokens that form the words:
- std::vector<gpt_vocab::id> tokens;
- for (const auto & word : words) {
- if (word.size() == 0) continue;
- int i = 0;
- int n = word.size();
- while (i < n) {
- int j = n;
- while (j > i) {
- auto it = vocab.token_to_id.find(word.substr(i, j-i));
- if (it != vocab.token_to_id.end()) {
- tokens.push_back(it->second);
- i = j;
- break;
- }
- --j;
- }
- if (i == n) {
- break;
- }
- if (j == i) {
- auto sub = word.substr(i, 1);
- if (vocab.token_to_id.find(sub) != vocab.token_to_id.end()) {
- tokens.push_back(vocab.token_to_id.at(sub));
- } else {
- fprintf(stderr, "%s: unknown token '%s'\n", __func__, sub.data());
- }
- ++i;
- }
- }
- }
- return tokens;
- }
- std::vector<gpt_vocab::id> llama_tokenize(const gpt_vocab & vocab, const std::string & text, bool bos) {
- //auto res = gpt_tokenize(vocab, text);
- //if (bos) {
- // res.insert(res.begin(), 1); // TODO: replace with vocab.bos
- //}
- std::vector<gpt_vocab::id> res;
- if (bos) {
- res.push_back(1); // TODO: replace with vocab.bos
- }
- //find the longest token that matches the text
- int pos = 0;
- while (true) {
- int l = 0;
- int t = 0;
- for (const auto & kv : vocab.id_to_token) {
- if (kv.second.size() < l) continue;
- if (kv.second.size() > text.size() - pos) continue;
- if (text.substr(pos, kv.second.size()) == kv.second) {
- l = kv.second.size();
- t = kv.first;
- }
- }
- if (l == 0) {
- break;
- }
- res.push_back(t);
- pos += l;
- }
- return res;
- }
- bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab) {
- printf("%s: loading vocab from '%s'\n", __func__, fname.c_str());
- vocab.token_to_id = ::json_parse(fname);
- for (const auto & kv : vocab.token_to_id) {
- vocab.id_to_token[kv.second] = kv.first;
- }
- printf("%s: vocab size = %d\n", __func__, (int) vocab.token_to_id.size());
- // print the vocabulary
- //for (auto kv : vocab.token_to_id) {
- // printf("'%s' -> %d\n", kv.first.data(), kv.second);
- //}
- return true;
- }
- void sample_top_k(std::vector<std::pair<double, gpt_vocab::id>> & logits_id, int top_k) {
- // 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);
- }
- gpt_vocab::id llama_sample_top_p_top_k(
- const gpt_vocab & vocab,
- const float * logits,
- std::vector<gpt_vocab::id> & last_n_tokens,
- double repeat_penalty,
- int top_k,
- double top_p,
- double temp,
- 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) {
- // repetition penalty from CTRL paper (https://arxiv.org/abs/1909.05858)
- // credit https://github.com/facebookresearch/llama/compare/main...shawwn:llama:main
- if (std::find(last_n_tokens.begin(), last_n_tokens.end(), i) != last_n_tokens.end()) {
- // if score < 0 then repetition penalty has to multiplied to reduce the previous token probability
- if (logits[i] < 0.0) {
- logits_id.push_back(std::make_pair(logits[i]*scale*repeat_penalty, i));
- } else {
- logits_id.push_back(std::make_pair(logits[i]*scale/repeat_penalty, i));
- }
- } else {
- logits_id.push_back(std::make_pair(logits[i]*scale, i));
- }
- }
- }
- sample_top_k(logits_id, 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 < (int) probs.size(); i++) {
- cumsum += probs[i];
- if (cumsum >= top_p) {
- probs.resize(i + 1);
- logits_id.resize(i + 1);
- break;
- }
- }
- cumsum = 1.0/cumsum;
- for (int i = 0; i < (int) probs.size(); i++) {
- probs[i] *= cumsum;
- }
- }
- //printf("\n");
- //for (int i = 0; i < (int) 10; i++) {
- // printf("%d: '%s' %f\n", i, vocab.id_to_token.at(logits_id[i].second).c_str(), probs[i]);
- //}
- //printf("\n\n");
- //exit(0);
- std::discrete_distribution<> dist(probs.begin(), probs.end());
- int idx = dist(rng);
- return logits_id[idx].second;
- }
- size_t ggml_quantize_q4_0(float * src, void * dst, int n, int k, int qk, int64_t * hist) {
- const int nb = k / qk;
- const size_t bs = (sizeof(float) + sizeof(uint8_t)*qk/2);
- const size_t row_size = nb*bs;
- assert(k % qk == 0);
- const size_t pp_size = qk / 2;
- uint8_t *pp = static_cast<uint8_t*>(alloca(pp_size));
- char * pdst = (char *) dst;
- for (int j = 0; j < n; j += k) {
- uint8_t * pd = (uint8_t *) (pdst + (j/k)*row_size + 0*bs);
- uint8_t * pb = (uint8_t *) (pdst + (j/k)*row_size + 0*bs + sizeof(float));
- for (int i = 0; i < nb; i++) {
- float amax = 0.0f; // absolute max
- {
- for (int l = 0; l < qk; l++) {
- const float v = src[j + i*qk + l];
- amax = std::max(amax, fabsf(v));
- }
- const float d = amax / ((1 << 3) - 1);
- const float id = d ? 1.0f/d : 0.0f;
- *(float *) pd = d;
- pd += bs;
- for (int l = 0; l < qk; l += 2) {
- const float v0 = (src[j + i*qk + l + 0])*id;
- const float v1 = (src[j + i*qk + l + 1])*id;
- const uint8_t vi0 = ((int8_t) (round(v0))) + 8;
- const uint8_t vi1 = ((int8_t) (round(v1))) + 8;
- assert(vi0 >= 0 && vi0 < 16);
- assert(vi1 >= 0 && vi1 < 16);
- hist[vi0]++;
- hist[vi1]++;
- pp[l/2] = vi0 | (vi1 << 4);
- }
- memcpy(pb, pp, pp_size);
- pb += bs;
- }
- }
- }
- return (n/k)*row_size;
- }
- size_t ggml_quantize_q4_1(float * src, void * dst, int n, int k, int qk, int64_t * hist) {
- const int nb = k / qk;
- const size_t row_size = nb*(2*sizeof(float) + sizeof(uint8_t)*qk/2);
- assert(k % qk == 0);
- const size_t pp_size = qk / 2;
- uint8_t *pp = static_cast<uint8_t*>(alloca(pp_size));
- char * pdst = (char *) dst;
- for (int j = 0; j < n; j += k) {
- float * pm = (float *) (pdst + (j/k)*row_size);
- float * pd = (float *) (pm + nb);
- uint8_t * pb = (uint8_t *) (pd + nb);
- //printf("n = %d, k = %d, nb = %d, row_size = %d, j = %d, pm = %p, pd = %p, pb = %p\n", n, k, nb, row_size, j, pm, pd, pb);
- for (int i = 0; i < nb; i++) {
- float min = std::numeric_limits<float>::max();
- float max = std::numeric_limits<float>::min();
- {
- for (int l = 0; l < qk; l++) {
- const float v = src[j + i*qk + l];
- if (v < min) min = v;
- if (v > max) max = v;
- }
- const float d = (max - min) / ((1 << 4) - 1);
- const float id = d ? 1.0f/d : 0.0f;
- pm[i] = min;
- pd[i] = d;
- for (int l = 0; l < qk; l += 2) {
- const float v0 = (src[j + i*qk + l + 0] - min)*id;
- const float v1 = (src[j + i*qk + l + 1] - min)*id;
- const uint8_t vi0 = round(v0);
- const uint8_t vi1 = round(v1);
- assert(vi0 >= 0 && vi0 < 16);
- assert(vi1 >= 0 && vi1 < 16);
- hist[vi0]++;
- hist[vi1]++;
- pp[l/2] = vi0 | (vi1 << 4);
- }
- memcpy(pb + i*qk/2, pp, pp_size);
- }
- }
- }
- return (n/k)*row_size;
- }
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