for (auto it = GGML_FTYPE_MAP.begin(); it != GGML_FTYPE_MAP.end(); it++) {

fprintf(fp, " type = \"%s\" or %d\n", it->first.c_str(), it->second);

}

enum ggml_ftype ftype;

if (str[0] == 'q') {

const auto it = GGML_FTYPE_MAP.find(str);

if (it == GGML_FTYPE_MAP.end()) {

fprintf(stderr, "%s: unknown ftype '%s'\n", __func__, str);

return GGML_FTYPE_UNKNOWN;

}

ftype = it->second;

} else {

ftype = (enum ggml_ftype) atoi(str);

}

return ftype;

std::ifstream & finp,

std::ofstream & fout,

const ggml_ftype ftype,

const std::vector<std::string> & to_quant,

const std::vector<std::string> & to_skip) {

ggml_type qtype = GGML_TYPE_F32;

switch (ftype) {

case GGML_FTYPE_MOSTLY_Q4_0: qtype = GGML_TYPE_Q4_0; break;

case GGML_FTYPE_MOSTLY_Q4_1: qtype = GGML_TYPE_Q4_1; break;

case GGML_FTYPE_MOSTLY_Q5_0: qtype = GGML_TYPE_Q5_0; break;

case GGML_FTYPE_MOSTLY_Q5_1: qtype = GGML_TYPE_Q5_1; break;

case GGML_FTYPE_MOSTLY_Q8_0: qtype = GGML_TYPE_Q8_0; break;

case GGML_FTYPE_UNKNOWN:

case GGML_FTYPE_ALL_F32:

case GGML_FTYPE_MOSTLY_F16:

case GGML_FTYPE_MOSTLY_Q4_1_SOME_F16:

{

fprintf(stderr, "%s: invalid model type %d\n", __func__, ftype);

return false;

}

};

if (!ggml_is_quantized(qtype)) {

fprintf(stderr, "%s: invalid quantization type %d (%s)\n", __func__, qtype, ggml_type_name(qtype));

return false;

}

size_t total_size_org = 0;

size_t total_size_new = 0;

std::vector<float> work;

std::vector<uint8_t> data_u8;

std::vector<ggml_fp16_t> data_f16;

std::vector<float> data_f32;

std::vector<int64_t> hist_all(1 << 4, 0);

while (true) {

int32_t n_dims;

int32_t length;

int32_t ttype;

finp.read(reinterpret_cast<char *>(&n_dims), sizeof(n_dims));

finp.read(reinterpret_cast<char *>(&length), sizeof(length));

finp.read(reinterpret_cast<char *>(&ttype), sizeof(ttype));

if (finp.eof()) {

break;

}

int32_t nelements = 1;

int32_t ne[4] = { 1, 1, 1, 1 };

for (int i = 0; i < n_dims; ++i) {

finp.read (reinterpret_cast<char *>(&ne[i]), sizeof(ne[i]));

nelements *= ne[i];

}

std::string name(length, 0);

finp.read (&name[0], length);

printf("%64s - [%5d, %5d, %5d], type = %6s ", name.data(), ne[0], ne[1], ne[2], ggml_type_name((ggml_type) ttype));

bool quantize = false;

// check if we should quantize this tensor

for (const auto & s : to_quant) {

if (std::regex_match(name, std::regex(s))) {

quantize = true;

break;

}

}

// check if we should skip this tensor

for (const auto & s : to_skip) {

if (std::regex_match(name, std::regex(s))) {

quantize = false;

break;

}

}

// quantize only 2D tensors

quantize &= (n_dims == 2);

if (quantize) {

if (ttype != GGML_TYPE_F32 && ttype != GGML_TYPE_F16) {

fprintf(stderr, "%s: unsupported ttype %d (%s) for integer quantization\n", __func__, ttype, ggml_type_name((ggml_type) ttype));

return false;

}

if (ttype == GGML_TYPE_F16) {

data_f16.resize(nelements);

finp.read(reinterpret_cast<char *>(data_f16.data()), nelements * sizeof(ggml_fp16_t));

data_f32.resize(nelements);

for (int i = 0; i < nelements; ++i) {

data_f32[i] = ggml_fp16_to_fp32(data_f16[i]);

}

} else {

data_f32.resize(nelements);

finp.read(reinterpret_cast<char *>(data_f32.data()), nelements * sizeof(float));

}

ttype = qtype;

} else {

const int bpe = (ttype == 0) ? sizeof(float) : sizeof(uint16_t);

data_u8.resize(nelements*bpe);

finp.read(reinterpret_cast<char *>(data_u8.data()), nelements * bpe);

}

fout.write(reinterpret_cast<char *>(&n_dims), sizeof(n_dims));

fout.write(reinterpret_cast<char *>(&length), sizeof(length));

fout.write(reinterpret_cast<char *>(&ttype), sizeof(ttype));

for (int i = 0; i < n_dims; ++i) {

fout.write(reinterpret_cast<char *>(&ne[i]), sizeof(ne[i]));

}

fout.write(&name[0], length);

if (quantize) {

work.resize(nelements); // for quantization

size_t cur_size = 0;

std::vector<int64_t> hist_cur(1 << 4, 0);

switch ((ggml_type) ttype) {

case GGML_TYPE_Q4_0:

{

cur_size = ggml_quantize_q4_0(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());

} break;

case GGML_TYPE_Q4_1:

{

cur_size = ggml_quantize_q4_1(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());

} break;

case GGML_TYPE_Q5_0:

{

cur_size = ggml_quantize_q5_0(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());

} break;

case GGML_TYPE_Q5_1:

{

cur_size = ggml_quantize_q5_1(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());

} break;

case GGML_TYPE_Q8_0:

{

cur_size = ggml_quantize_q8_0(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());

} break;

case GGML_TYPE_F32:

case GGML_TYPE_F16:

case GGML_TYPE_I8:

case GGML_TYPE_I16:

case GGML_TYPE_I32:

case GGML_TYPE_Q8_1:

case GGML_TYPE_COUNT:

{

fprintf(stderr, "%s: unsupported quantization type %d (%s)\n", __func__, ttype, ggml_type_name((ggml_type) ttype));

return false;

}

}

fout.write(reinterpret_cast<char *>(work.data()), cur_size);

total_size_new += cur_size;

printf("size = %8.2f MB -> %8.2f MB | hist: ", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0);

for (int i = 0; i < (int) hist_cur.size(); ++i) {

hist_all[i] += hist_cur[i];

}

for (int i = 0; i < (int) hist_cur.size(); ++i) {

printf("%5.3f ", hist_cur[i] / (float)nelements);

}

printf("\n");

} else {

printf("size = %8.3f MB\n", data_u8.size()/1024.0/1024.0);

fout.write(reinterpret_cast<char *>(data_u8.data()), data_u8.size());

total_size_new += data_u8.size();

}

total_size_org += nelements * sizeof(float);

}

printf("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);

printf("%s: quant size = %8.2f MB | ftype = %d (%s)\n", __func__, total_size_new/1024.0/1024.0, ftype, ggml_type_name(qtype));

{

int64_t sum_all = 0;

for (int i = 0; i < (int) hist_all.size(); ++i) {

sum_all += hist_all[i];

}

printf("%s: hist: ", __func__);

for (int i = 0; i < (int) hist_all.size(); ++i) {

printf("%5.3f ", hist_all[i] / (float)sum_all);

}

printf("\n");

}

return true;

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 == "-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 if (arg == "-f" || arg == "--file") {

if (++i > argc) {

fprintf(stderr, "Invalid file param");

break;

}

std::ifstream file(argv[i]);

if (!file) {

fprintf(stderr, "error: failed to open file '%s'\n", argv[i]);

break;

}

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 {

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, " -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, " load prompt from a file\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, " --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");

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";

std::string result = s;

size_t pos = 0;

while ((pos = result.find(from, pos)) != std::string::npos) {

result.replace(pos, from.length(), to);

pos += to.length();

}

return result;

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;

}

str_key = ::replace(str_key, "\\u0120", " " ); // \u0120 -> space

str_key = ::replace(str_key, "\\u010a", "\n"); // \u010a -> new line

str_key = ::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<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+)";

// Generate the subpattern from the special_tokens vector if it's not empty

if (!vocab.special_tokens.empty()) {

std::string special_tokens_subpattern;

for (const auto & token : vocab.special_tokens) {

if (!special_tokens_subpattern.empty()) {

special_tokens_subpattern += "|";

}

special_tokens_subpattern += token;

}

// Modify the regex pattern with the generated special tokens subpattern

pat = special_tokens_subpattern + "|" + pat;

}

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;

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;

const gpt_vocab & vocab,

const float * logits,

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) {

logits_id.push_back(std::make_pair(logits[i]*scale, i));

}

}

// 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);

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 < top_k; i++) {

cumsum += probs[i];

if (cumsum >= top_p) {

top_k = i + 1;

probs.resize(top_k);

logits_id.resize(top_k);

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) probs.size(); i++) {

// printf("%d: '%s' %f\n", i, vocab.id_to_token.at(logits_id[i].second).c_str(), probs[i]);

//}

//exit(0);

std::discrete_distribution<> dist(probs.begin(), probs.end());

int idx = dist(rng);

return logits_id[idx].second;