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common.cpp
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618 lines (523 loc) · 20.1 KB
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#include "common.h"
// third-party utilities
// use your favorite implementations
#include <cmath>
#include <fstream>
#include <regex>
#ifndef M_PI
#define M_PI 3.14159265358979323846
#endif
// taken from common-ggml.cpp
#include "ggml.h"
#include <map>
static const std::map<std::string, enum ggml_ftype> GGML_FTYPE_MAP = {
{"q4_0", GGML_FTYPE_MOSTLY_Q4_0},
{"q4_1", GGML_FTYPE_MOSTLY_Q4_1},
{"q5_0", GGML_FTYPE_MOSTLY_Q5_0},
{"q5_1", GGML_FTYPE_MOSTLY_Q5_1},
{"q8_0", GGML_FTYPE_MOSTLY_Q8_0},
};
void ggml_print_ftypes(FILE * fp) {
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 ggml_parse_ftype(const char * str) {
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;
}
bool ggml_common_quantize_0(
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;
}
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 == "-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;
}
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, " -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");
}
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";
}
std::string trim(const std::string & s) {
std::regex e("^\\s+|\\s+$");
return std::regex_replace(s, e, "");
}
std::string replace(const std::string & s, const std::string & from, const std::string & to) {
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> 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;
}
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;
}
void gpt_vocab::add_special_token(const std::string & token) {
special_tokens.push_back(token);
}
std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text) {
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;
}
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;
}
gpt_vocab::id gpt_sample_top_k_top_p(
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;
}
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