#include "utils.h" #include #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__) #include #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 == "-f" || arg == "--file") { std::ifstream file(argv[++i]); std::copy(std::istreambuf_iterator(file), std::istreambuf_iterator(), back_inserter(params.prompt)); } 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 == "-i" || arg == "--interactive") { params.interactive = true; } else if (arg == "--interactive-start") { params.interactive = true; params.interactive_start = true; } else if (arg == "--color") { params.use_color = true; } else if (arg == "-r" || arg == "--reverse-prompt") { params.antiprompt = 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, " -i, --interactive run in interactive mode\n"); fprintf(stderr, " --interactive-start run in interactive mode and poll user input at startup\n"); fprintf(stderr, " -r PROMPT, --reverse-prompt PROMPT\n"); fprintf(stderr, " in interactive mode, poll user input upon seeing PROMPT\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: random)\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, " --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 json_parse(const std::string & fname) { std::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; } 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; 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 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 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 res; // if (bos) { // res.push_back(1); // TODO: replace with vocab.bos // } sentencepiece::SentencePieceProcessor sp; sp.Load("./models/tokenizer.model"); std::vector pieces; return sp.EncodeAsIds(text); /* for (const auto & piece : pieces) { printf("piece: %s\n", piece.c_str()); if (vocab.token_to_id.count(piece) > 0) { res.push_back(vocab.token_to_id.at(piece)); } else { // handle unknown token } } for (const auto& id : res) { printf("%d\n", id); } 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> & 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); } gpt_vocab::id llama_sample_top_p_top_k( const gpt_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 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(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::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; 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; } void untokenize(sentencepiece::SentencePieceProcessor &sp, std::vector &buffids, std::vector &embd) { for (auto id : embd) { std::string s = sp.IdToPiece(id); // vocab.id_to_token[id]; if (s.find("<0x") == 0 && s[s.length() - 1] == '>') { buffids.push_back(id); std::string txt = sp.DecodeIds(buffids); // printf("bufferring %s, total buffer: %s\n", s.c_str(), txt.c_str()); } else if (s.find("▁") == 0) { if (!buffids.empty()) { std::string txt = sp.DecodeIds(buffids); printf("%s", txt.c_str()); buffids.clear(); } s = std::regex_replace(s, std::regex("▁"), " "); printf("%s", s.c_str()); } else { if (!buffids.empty()) { std::string txt = sp.DecodeIds(buffids); printf("%s", txt.c_str()); buffids.clear(); } printf("%s", s.c_str()); } } }