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// TODO: move somewhere else | |
// default hparams (LLaMA76B) | |
struct llama_hparams { | |
int32_t n_vocab = 32000; | |
int32_t n_ctx = 512; // this is provided as user input? | |
int32_t n_embd = 4096; | |
int32_t n_mult = 256; | |
int32_t n_head = 32; | |
int32_t n_layer = 32; | |
int32_t n_rot = 64; | |
int32_t f16 = 1; | |
}; | |
// quantize a model | |
bool llama_model_quantize(const std::string & fname_inp, const std::string & fname_out, int itype) { | |
ggml_type type = GGML_TYPE_Q4_1; | |
switch (itype) { | |
case 2: type = GGML_TYPE_Q4_0; break; | |
case 3: type = GGML_TYPE_Q4_1; break; | |
default: fprintf(stderr, "%s: invalid quantization type %d\n", __func__, itype); return 1; | |
}; | |
if (type != GGML_TYPE_Q4_0 && type != GGML_TYPE_Q4_1) { | |
fprintf(stderr, "%s: invalid quantization type %d\n", __func__, type); | |
return false; | |
} | |
gpt_vocab vocab; | |
printf("%s: loading model from '%s'\n", __func__, fname_inp.c_str()); | |
auto finp = std::ifstream(fname_inp, std::ios::binary); | |
if (!finp) { | |
fprintf(stderr, "%s: failed to open '%s' for reading\n", __func__, fname_inp.c_str()); | |
return false; | |
} | |
auto fout = std::ofstream(fname_out, std::ios::binary); | |
if (!fout) { | |
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname_out.c_str()); | |
return false; | |
} | |
// verify magic | |
{ | |
uint32_t magic; | |
finp.read((char *) &magic, sizeof(magic)); | |
if (magic != 0x67676d6c) { | |
fprintf(stderr, "%s: invalid model file '%s' (bad magic)\n", __func__, fname_inp.c_str()); | |
return false; | |
} | |
fout.write((char *) &magic, sizeof(magic)); | |
} | |
llama_hparams hparams; | |
// load hparams | |
{ | |
finp.read((char *) &hparams.n_vocab, sizeof(hparams.n_vocab)); | |
//finp.read((char *) &hparams.n_ctx, sizeof(hparams.n_ctx)); | |
finp.read((char *) &hparams.n_embd, sizeof(hparams.n_embd)); | |
finp.read((char *) &hparams.n_mult, sizeof(hparams.n_mult)); | |
finp.read((char *) &hparams.n_head, sizeof(hparams.n_head)); | |
finp.read((char *) &hparams.n_layer, sizeof(hparams.n_layer)); | |
finp.read((char *) &hparams.n_rot, sizeof(hparams.n_rot)); | |
finp.read((char *) &hparams.f16, sizeof(hparams.f16)); | |
printf("%s: n_vocab = %d\n", __func__, hparams.n_vocab); | |
printf("%s: n_ctx = %d\n", __func__, hparams.n_ctx); | |
printf("%s: n_embd = %d\n", __func__, hparams.n_embd); | |
printf("%s: n_mult = %d\n", __func__, hparams.n_mult); | |
printf("%s: n_head = %d\n", __func__, hparams.n_head); | |
printf("%s: n_layer = %d\n", __func__, hparams.n_layer); | |
printf("%s: f16 = %d\n", __func__, hparams.f16); | |
fout.write((char *) &hparams.n_vocab, sizeof(hparams.n_vocab)); | |
//fout.write((char *) &hparams.n_ctx, sizeof(hparams.n_ctx)); | |
fout.write((char *) &hparams.n_embd, sizeof(hparams.n_embd)); | |
fout.write((char *) &hparams.n_mult, sizeof(hparams.n_mult)); | |
fout.write((char *) &hparams.n_head, sizeof(hparams.n_head)); | |
fout.write((char *) &hparams.n_layer, sizeof(hparams.n_layer)); | |
fout.write((char *) &hparams.n_rot, sizeof(hparams.n_rot)); | |
fout.write((char *) &itype, sizeof(hparams.f16)); | |
} | |
// load vocab | |
{ | |
const int32_t n_vocab = hparams.n_vocab; | |
if (n_vocab != hparams.n_vocab) { | |
fprintf(stderr, "%s: invalid model file '%s' (bad vocab size %d != %d)\n", | |
__func__, fname_inp.c_str(), n_vocab, hparams.n_vocab); | |
return false; | |
} | |
std::string word; | |
for (int i = 0; i < n_vocab; i++) { | |
uint32_t len; | |
finp.read ((char *) &len, sizeof(len)); | |
fout.write((char *) &len, sizeof(len)); | |
word.resize(len); | |
finp.read ((char *) word.data(), len); | |
fout.write((char *) word.data(), len); | |
vocab.token_to_id[word] = i; | |
vocab.id_to_token[i] = word; | |
} | |
} | |
// load weights | |
{ | |
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 ftype; | |
finp.read(reinterpret_cast<char *>(&n_dims), sizeof(n_dims)); | |
finp.read(reinterpret_cast<char *>(&length), sizeof(length)); | |
finp.read(reinterpret_cast<char *>(&ftype), sizeof(ftype)); | |
if (finp.eof()) { | |
break; | |
} | |
int32_t nelements = 1; | |
int32_t ne[2] = { 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); | |
{ | |
static const char * ftype_str[] = { "f32", "f16", "q4_0", "q4_1", }; | |
printf("%48s - [%5d, %5d], type = %6s ", name.data(), ne[0], ne[1], ftype_str[ftype]); | |
} | |
// regexes of tensor names to be quantized | |
const std::vector<std::string> k_names = { | |
".*weight", | |
}; | |
bool quantize = false; | |
for (const auto & s : k_names) { | |
if (std::regex_match(name, std::regex(s))) { | |
quantize = true; | |
break; | |
} | |
} | |
// quantize only 2D tensors | |
quantize &= (n_dims == 2); | |
if (quantize) { | |
if (ftype != 0 && ftype != 1) { | |
fprintf(stderr, "%s: unsupported ftype %d for integer quantization\n", __func__, ftype); | |
return false; | |
} | |
if (ftype == 1) { | |
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)); | |
} | |
ftype = itype; | |
} else { | |
const int bpe = (ftype == 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 *>(&ftype), sizeof(ftype)); | |
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) { | |
printf("quantizing .. "); | |
work.resize(nelements); // for quantization | |
size_t cur_size = 0; | |
std::vector<int64_t> hist_cur(1 << 4, 0); | |
switch (type) { | |
case GGML_TYPE_Q4_0: | |
{ | |
cur_size = ggml_quantize_q4_0(data_f32.data(), work.data(), nelements, ne[0], QK, hist_cur.data()); | |
} break; | |
case GGML_TYPE_Q4_1: | |
{ | |
cur_size = ggml_quantize_q4_1(data_f32.data(), work.data(), nelements, ne[0], QK, hist_cur.data()); | |
} break; | |
default: | |
{ | |
fprintf(stderr, "%s: unsupported quantization type %d\n", __func__, type); | |
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 < hist_cur.size(); ++i) { | |
hist_all[i] += hist_cur[i]; | |
} | |
for (int i = 0; i < 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\n", __func__, total_size_new/1024.0/1024.0); | |
{ | |
int64_t sum_all = 0; | |
for (int i = 0; i < hist_all.size(); ++i) { | |
sum_all += hist_all[i]; | |
} | |
printf("%s: hist: ", __func__); | |
for (int i = 0; i < hist_all.size(); ++i) { | |
printf("%5.3f ", hist_all[i] / (float)sum_all); | |
} | |
printf("\n"); | |
} | |
} | |
finp.close(); | |
fout.close(); | |
return true; | |
} | |
// usage: | |
// ./llama-quantize models/llama/ggml-model.bin models/llama/ggml-model-quant.bin type | |
// | |
int main(int argc, char ** argv) { | |
ggml_time_init(); | |
if (argc != 4) { | |
fprintf(stderr, "usage: %s model-f32.bin model-quant.bin type\n", argv[0]); | |
fprintf(stderr, " type = 2 - q4_0\n"); | |
fprintf(stderr, " type = 3 - q4_1\n"); | |
return 1; | |
} | |
// needed to initialize f16 tables | |
{ | |
struct ggml_init_params params = { 0, NULL }; | |
struct ggml_context * ctx = ggml_init(params); | |
ggml_free(ctx); | |
} | |
const std::string fname_inp = argv[1]; | |
const std::string fname_out = argv[2]; | |
const int itype = atoi(argv[3]); | |
const int64_t t_main_start_us = ggml_time_us(); | |
int64_t t_quantize_us = 0; | |
// load the model | |
{ | |
const int64_t t_start_us = ggml_time_us(); | |
if (!llama_model_quantize(fname_inp, fname_out, itype)) { | |
fprintf(stderr, "%s: failed to quantize model from '%s'\n", __func__, fname_inp.c_str()); | |
return 1; | |
} | |
t_quantize_us = ggml_time_us() - t_start_us; | |
} | |
// report timing | |
{ | |
const int64_t t_main_end_us = ggml_time_us(); | |
printf("\n"); | |
printf("%s: quantize time = %8.2f ms\n", __func__, t_quantize_us/1000.0f); | |
printf("%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0f); | |
} | |
return 0; | |
} | |