// 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 == "--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;

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");

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";

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<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;

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];

using index = int;

index prev;

index next;

const char * text;

size_t n;

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;

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);

}

}

}

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<size_t>((*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<llama_sp_symbol> symbols_;

llama_sp_bigram::queue work_queue_;

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);

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;

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;

// 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);

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;

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;

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;