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#include "build-info.h"
#include "llama.h"
#include <cstdio>
#include <cstring>
#include <map>
#include <string>
static const std::map<std::string, llama_ftype> LLAMA_FTYPE_MAP = {
{"q4_0", LLAMA_FTYPE_MOSTLY_Q4_0},
{"q4_1", LLAMA_FTYPE_MOSTLY_Q4_1},
{"q5_0", LLAMA_FTYPE_MOSTLY_Q5_0},
{"q5_1", LLAMA_FTYPE_MOSTLY_Q5_1},
{"q8_0", LLAMA_FTYPE_MOSTLY_Q8_0},
{"q2_K", LLAMA_FTYPE_MOSTLY_Q2_K},
{"q3_K", LLAMA_FTYPE_MOSTLY_Q3_K_M},
{"q3_K_S", LLAMA_FTYPE_MOSTLY_Q3_K_S},
{"q3_K_M", LLAMA_FTYPE_MOSTLY_Q3_K_M},
{"q3_K_L", LLAMA_FTYPE_MOSTLY_Q3_K_L},
{"q4_K", LLAMA_FTYPE_MOSTLY_Q4_K_M},
{"q4_K_S", LLAMA_FTYPE_MOSTLY_Q4_K_S},
{"q4_K_M", LLAMA_FTYPE_MOSTLY_Q4_K_M},
{"q5_K", LLAMA_FTYPE_MOSTLY_Q5_K_M},
{"q5_K_S", LLAMA_FTYPE_MOSTLY_Q5_K_S},
{"q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M},
{"q6_K", LLAMA_FTYPE_MOSTLY_Q6_K},
};
bool try_parse_ftype(const std::string & ftype_str, llama_ftype & ftype, std::string & ftype_str_out) {
auto it = LLAMA_FTYPE_MAP.find(ftype_str);
if (it != LLAMA_FTYPE_MAP.end()) {
ftype = it->second;
ftype_str_out = it->first;
return true;
}
// try to parse as an integer
try {
int ftype_int = std::stoi(ftype_str);
for (auto it = LLAMA_FTYPE_MAP.begin(); it != LLAMA_FTYPE_MAP.end(); it++) {
if (it->second == ftype_int) {
ftype = it->second;
ftype_str_out = it->first;
return true;
}
}
}
catch (...) {
// stoi failed
}
return false;
}
// usage:
// ./quantize models/llama/ggml-model.bin [models/llama/ggml-model-quant.bin] type [nthreads]
//
void usage(const char * executable) {
fprintf(stderr, "usage: %s [--help] [--allow-requantize] [--leave-output-tensor] model-f32.bin [model-quant.bin] type [nthreads]\n", executable);
fprintf(stderr, " --allow-requantize: Allows requantizing tensors that have already been quantized. Warning: This can severely reduce quality compared to quantizing from 16bit or 32bit\n");
fprintf(stderr, " --leave-output-tensor: Will leave output.weight un(re)quantized. Increases model size but may also increase quality, especially when requantizing\n");
fprintf(stderr, "Allowed quantization types:\n");
for (auto it = LLAMA_FTYPE_MAP.begin(); it != LLAMA_FTYPE_MAP.end(); it++) {
fprintf(stderr, " type = \"%s\" or %d\n", it->first.c_str(), it->second);
}
exit(1);
}
int main(int argc, char ** argv) {
if (argc < 3) {
usage(argv[0]);
}
llama_model_quantize_params params = llama_model_quantize_default_params();
int arg_idx = 1;
for (; arg_idx < argc && strncmp(argv[arg_idx], "--", 2) == 0; arg_idx++) {
if (strcmp(argv[arg_idx], "--leave-output-tensor") == 0) {
params.quantize_output_tensor = false;
} else if (strcmp(argv[arg_idx], "--allow-requantize") == 0) {
params.allow_requantize = true;
} else {
usage(argv[0]);
}
}
if (argc - arg_idx < 3) {
usage(argv[0]);
}
llama_init_backend();
// parse command line arguments
const std::string fname_inp = argv[arg_idx];
arg_idx++;
std::string fname_out;
std::string ftype_str;
if (try_parse_ftype(argv[arg_idx], params.ftype, ftype_str)) {
std::string fpath;
const size_t pos = fname_inp.find_last_of('/');
if (pos != std::string::npos) {
fpath = fname_inp.substr(0, pos + 1);
}
// export as [inp path]/ggml-model-[ftype].bin
fname_out = fpath + "ggml-model-" + ftype_str + ".bin";
arg_idx++;
}
else {
fname_out = argv[arg_idx];
arg_idx++;
if (argc <= arg_idx) {
fprintf(stderr, "%s: missing ftype\n", __func__);
return 1;
}
if (!try_parse_ftype(argv[arg_idx], params.ftype, ftype_str)) {
fprintf(stderr, "%s: invalid ftype '%s'\n", __func__, argv[3]);
return 1;
}
arg_idx++;
}
// parse nthreads
if (argc > arg_idx) {
try {
params.nthread = std::stoi(argv[arg_idx]);
}
catch (const std::exception & e) {
fprintf(stderr, "%s: invalid nthread '%s' (%s)\n", __func__, argv[arg_idx], e.what());
return 1;
}
}
fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
fprintf(stderr, "%s: quantizing '%s' to '%s' as %s", __func__, fname_inp.c_str(), fname_out.c_str(), ftype_str.c_str());
if (params.nthread > 0) {
fprintf(stderr, " using %d threads", params.nthread);
}
fprintf(stderr, "\n");
const int64_t t_main_start_us = llama_time_us();
int64_t t_quantize_us = 0;
// load the model
{
const int64_t t_start_us = llama_time_us();
if (llama_model_quantize(fname_inp.c_str(), fname_out.c_str(), ¶ms)) {
fprintf(stderr, "%s: failed to quantize model from '%s'\n", __func__, fname_inp.c_str());
return 1;
}
t_quantize_us = llama_time_us() - t_start_us;
}
// report timing
{
const int64_t t_main_end_us = llama_time_us();
printf("\n");
printf("%s: quantize time = %8.2f ms\n", __func__, t_quantize_us/1000.0);
printf("%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0);
}
return 0;
}
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