#include "utils.h" #include #include #include #include #include #include #include #include #include #if defined(_MSC_VER) || defined(__MINGW32__) #include // using malloc.h with MSC/MINGW #elif !defined(__FreeBSD__) && !defined(__NetBSD__) && !defined(__OpenBSD__) #include #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(cpuinfo), std::istream_iterator(), 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(file), std::istreambuf_iterator(), 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 == "--perplexity") { params.perplexity = true; } 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, " --perplexity compute perplexity over the prompt\n"); 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::unordered_map json_parse(const std::string & fname) { std::unordered_map 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(ifs)), (std::istreambuf_iterator())); } 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(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; using queue = std::priority_queue; 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 & 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(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; } if (static_cast((*token).second) >= vocab_.id_to_token.size()) { return; } const auto &tok_score = vocab_.id_to_token[(*token).second]; llama_sp_bigram bigram; bigram.left = left; bigram.right = right; bigram.score = tok_score.score; bigram.size = text.size(); work_queue_.push(bigram); } const llama_vocab & vocab_; std::vector 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 tmp(64); vocab.id_to_token.resize(n_vocab); 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; auto &tok_score = vocab.id_to_token[i]; tok_score.tok = word; tok_score.score = score; } return true; } std::vector llama_tokenize(const llama_vocab & vocab, const std::string & text, bool bos) { llama_tokenizer tokenizer(vocab); std::vector 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> & 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 & a, const std::pair & 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 & 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> 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 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(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(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::max(); float max = std::numeric_limits::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; }