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- #include "utils.h"
- #include <cassert>
- #include <cstring>
- #include <fstream>
- #include <regex>
- #include <iostream>
- #include <iterator>
- #include <queue>
- #include <string>
- #include <math.h>
- #if defined(_MSC_VER) || defined(__MINGW32__)
- #include <malloc.h> // using malloc.h with MSC/MINGW
- #elif !defined(__FreeBSD__) && !defined(__NetBSD__) && !defined(__OpenBSD__)
- #include <alloca.h>
- #endif
- bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
- // determine sensible default number of threads.
- // std::thread::hardware_concurrency may not be equal to the number of cores, or may return 0.
- #ifdef __linux__
- std::ifstream cpuinfo("/proc/cpuinfo");
- params.n_threads = std::count(std::istream_iterator<std::string>(cpuinfo),
- std::istream_iterator<std::string>(),
- std::string("processor"));
- #endif
- if (params.n_threads == 0) {
- params.n_threads = std::max(1, (int32_t) std::thread::hardware_concurrency());
- }
- 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 == "-f" || arg == "--file") {
- std::ifstream file(argv[++i]);
- std::copy(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), back_inserter(params.prompt));
- if (params.prompt.back() == '\n') {
- params.prompt.pop_back();
- }
- } 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 == "-c" || arg == "--ctx_size") {
- params.n_ctx = std::stoi(argv[++i]);
- } else if (arg == "--memory_f16") {
- params.memory_f16 = true;
- } 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 == "-i" || arg == "--interactive") {
- params.interactive = true;
- } else if (arg == "-ins" || arg == "--instruct") {
- params.instruct = true;
- } else if (arg == "--color") {
- params.use_color = true;
- } else if (arg == "-r" || arg == "--reverse-prompt") {
- params.antiprompt.push_back(argv[++i]);
- } else if (arg == "--ignore-eos") {
- params.ignore_eos = true;
- } else if (arg == "--n_parts") {
- params.n_parts = std::stoi(argv[++i]);
- } else if (arg == "-h" || arg == "--help") {
- gpt_print_usage(argc, argv, params);
- exit(0);
- } else if (arg == "--random-prompt") {
- params.random_prompt = true;
- } 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, " -i, --interactive run in interactive mode\n");
- fprintf(stderr, " -ins, --instruct run in instruction mode (use with Alpaca models)\n");
- fprintf(stderr, " -r PROMPT, --reverse-prompt PROMPT\n");
- fprintf(stderr, " in interactive mode, poll user input upon seeing PROMPT (can be\n");
- fprintf(stderr, " specified more than once for multiple prompts).\n");
- fprintf(stderr, " --color colorise output to distinguish prompt and user input from generations\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: empty)\n");
- fprintf(stderr, " --random-prompt start with a randomized prompt.\n");
- fprintf(stderr, " -f FNAME, --file FNAME\n");
- fprintf(stderr, " prompt file to start generation.\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, " -c N, --ctx_size N size of the prompt context (default: %d)\n", params.n_ctx);
- fprintf(stderr, " --ignore-eos ignore end of stream token and continue generating\n");
- fprintf(stderr, " --memory_f16 use f16 instead of f32 for memory key+value\n");
- fprintf(stderr, " --temp N temperature (default: %.1f)\n", params.temp);
- fprintf(stderr, " --n_parts N number of model parts (default: -1 = determine from dimensions)\n");
- 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;
- }
- static size_t utf8_len(char src) {
- const size_t lookup[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 4 };
- uint8_t highbits = static_cast<uint8_t>(src) >> 4;
- return lookup[highbits];
- }
- struct llama_sp_symbol {
- using index = int;
- index prev;
- index next;
- const char * text;
- size_t n;
- };
- struct llama_sp_bigram {
- struct comparator {
- bool operator()(llama_sp_bigram & l, llama_sp_bigram & r) {
- return (l.score < r.score) || (l.score == r.score && l.left > r.left);
- }
- };
- using queue_storage = std::vector<llama_sp_bigram>;
- using queue = std::priority_queue<llama_sp_bigram, queue_storage, comparator>;
- llama_sp_symbol::index left;
- llama_sp_symbol::index right;
- float score;
- size_t size;
- };
- // original implementation:
- // https://github.com/ggerganov/llama.cpp/commit/074bea2eb1f1349a0118239c4152914aecaa1be4
- struct llama_tokenizer {
- llama_tokenizer(const llama_vocab & vocab): vocab_(vocab) {}
- void tokenize(const std::string & text, std::vector<llama_vocab::id> & output) {
- // split string into utf8 chars
- int index = 0;
- size_t offs = 0;
- while (offs < text.size()) {
- llama_sp_symbol sym;
- size_t char_len = std::min(text.size() - offs, utf8_len(text[offs]));
- sym.text = text.c_str() + offs;
- sym.n = char_len;
- offs += char_len;
- sym.prev = index - 1;
- sym.next = offs == text.size() ? -1 : index + 1;
- index++;
- symbols_.emplace_back(std::move(sym));
- }
- // seed the work queue with all possible 2-character tokens.
- for (size_t i = 1; i < symbols_.size(); ++i) {
- try_add_bigram(i - 1, i);
- }
- // keep substituting the highest frequency pairs for as long as we can.
- while (!work_queue_.empty()) {
- auto bigram = work_queue_.top();
- work_queue_.pop();
- auto & left_sym = symbols_[bigram.left];
- auto & right_sym = symbols_[bigram.right];
- // if one of the symbols already got merged, skip it.
- if (left_sym.n == 0 || right_sym.n == 0 ||
- left_sym.n + right_sym.n != bigram.size) {
- continue;
- }
- // merge the right sym into the left one
- left_sym.n += right_sym.n;
- right_sym.n = 0;
- //printf("left = '%*s' size = %zu\n", (int) left_sym.n, left_sym.text, bigram.size);
- // remove the right sym from the chain
- left_sym.next = right_sym.next;
- if (right_sym.next >= 0) {
- symbols_[right_sym.next].prev = bigram.left;
- }
- // find more substitutions
- try_add_bigram(left_sym.prev, bigram.left);
- try_add_bigram(bigram.left, left_sym.next);
- }
- for (int i = 0; i != -1; i = symbols_[i].next) {
- auto & symbol = symbols_[i];
- auto token = vocab_.token_to_id.find(std::string(symbol.text, symbol.n));
- if (token == vocab_.token_to_id.end()) {
- // output any symbols that did not form tokens as bytes.
- for (int j = 0; j < (int) symbol.n; ++j) {
- llama_vocab::id token_id = static_cast<uint8_t>(symbol.text[j]) + 3;
- output.push_back(token_id);
- }
- } else {
- output.push_back((*token).second);
- }
- }
- }
- private:
- void try_add_bigram(int left, int right) {
- if (left == -1 || right == -1) {
- return;
- }
- const std::string text = std::string(symbols_[left].text, symbols_[left].n + symbols_[right].n);
- auto token = vocab_.token_to_id.find(text);
- if (token == vocab_.token_to_id.end()) {
- return;
- }
- auto score = vocab_.score.find((*token).second);
- if (score == vocab_.score.end()) {
- return;
- }
- llama_sp_bigram bigram;
- bigram.left = left;
- bigram.right = right;
- bigram.score = (*score).second;
- bigram.size = text.size();
- work_queue_.push(bigram);
- }
- const llama_vocab & vocab_;
- std::vector<llama_sp_symbol> symbols_;
- llama_sp_bigram::queue work_queue_;
- };
- // TODO: temporary code duplication with llama.cpp
- // will resolve after #77 is merged
- bool llama_vocab_load(const std::string & fname, llama_vocab & vocab) {
- std::ifstream fin(fname, std::ios::binary);
- if (!fin.is_open()) {
- return false;
- }
- int n_vocab = 0;
- fin.read((char *) &n_vocab, sizeof(n_vocab));
- std::string word;
- std::vector<char> tmp(64);
- for (int i = 0; i < n_vocab; i++) {
- uint32_t len;
- fin.read((char *) &len, sizeof(len));
- word.resize(len);
- if (len > 0) {
- tmp.resize(len);
- fin.read(tmp.data(), len);
- word.assign(tmp.data(), len);
- } else {
- word.clear();
- }
- float score;
- fin.read((char *) &score, sizeof(score));
- vocab.token_to_id[word] = i;
- vocab.id_to_token[i] = word;
- vocab.score[i] = score;
- }
- return true;
- }
- std::vector<llama_vocab::id> llama_tokenize(const llama_vocab & vocab, const std::string & text, bool bos) {
- llama_tokenizer tokenizer(vocab);
- std::vector<llama_vocab::id> output;
- if (text.size() == 0) {
- return output;
- }
- if (bos) {
- output.push_back(1);
- }
- tokenizer.tokenize(text, output);
- return output;
- }
- void sample_top_k(std::vector<std::pair<double, llama_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, llama_vocab::id> & a, const std::pair<double, llama_vocab::id> & b) {
- return a.first > b.first;
- });
- logits_id.resize(top_k);
- }
- llama_vocab::id llama_sample_top_p_top_k(
- const llama_vocab & vocab,
- const float * logits,
- std::vector<llama_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, llama_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 bs = (2*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 * pm = (uint8_t *) (pdst + (j/k)*row_size + 0*bs + sizeof(float));
- uint8_t * pb = (uint8_t *) (pdst + (j/k)*row_size + 0*bs + 2*sizeof(float));
- //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;
- *(float *) pd = d;
- *(float *) pm = min;
- pd += bs;
- pm += bs;
- 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, pp, pp_size);
- pb += bs;
- }
- }
- }
- return (n/k)*row_size;
- }
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