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struct mpt_hparams { | |
int32_t d_model = 0; | |
int32_t max_seq_len = 0; | |
int32_t n_heads = 0; | |
int32_t n_layers = 0; | |
int32_t n_vocab = 0; | |
float alibi_bias_max = 0; | |
float clip_qkv = 0; | |
int32_t ftype = 0; | |
}; | |
// quantize a model | |
bool mpt_model_quantize(const std::string & fname_inp, | |
const std::string & fname_out, ggml_ftype ftype) { | |
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)); | |
} | |
mpt_hparams hparams; | |
// load hparams | |
{ | |
finp.read((char *) &hparams.d_model, sizeof(hparams.d_model)); | |
finp.read((char *) &hparams.max_seq_len, sizeof(hparams.max_seq_len)); | |
finp.read((char *) &hparams.n_heads, sizeof(hparams.n_heads)); | |
finp.read((char *) &hparams.n_layers, sizeof(hparams.n_layers)); | |
finp.read((char *) &hparams.n_vocab, sizeof(hparams.n_vocab)); | |
finp.read((char *) &hparams.alibi_bias_max, sizeof(hparams.alibi_bias_max)); | |
finp.read((char *) &hparams.clip_qkv, sizeof(hparams.clip_qkv)); | |
finp.read((char *) &hparams.ftype, sizeof(hparams.ftype)); | |
const int32_t qntvr_src = hparams.ftype / GGML_QNT_VERSION_FACTOR; | |
const int32_t ftype_dst = GGML_QNT_VERSION * GGML_QNT_VERSION_FACTOR + ftype; | |
printf("%s: d_model = %d\n", __func__, hparams.d_model); | |
printf("%s: max_seq_len = %d\n", __func__, hparams.max_seq_len); | |
printf("%s: n_heads = %d\n", __func__, hparams.n_heads); | |
printf("%s: n_layers = %d\n", __func__, hparams.n_layers); | |
printf("%s: n_vocab = %d\n", __func__, hparams.n_vocab); | |
printf("%s: alibi_bias_max = %f\n", __func__, hparams.alibi_bias_max); | |
printf("%s: clip_qkv = %f\n", __func__, hparams.clip_qkv); | |
printf("%s: ftype (src) = %d\n", __func__, hparams.ftype); | |
printf("%s: qntvr (src) = %d\n", __func__, qntvr_src); | |
printf("%s: ftype (dst) = %d\n", __func__, ftype_dst); | |
printf("%s: qntvr (dst) = %d\n", __func__, GGML_QNT_VERSION); | |
fout.write((char *) &hparams.d_model, sizeof(hparams.d_model)); | |
fout.write((char *) &hparams.max_seq_len, sizeof(hparams.max_seq_len)); | |
fout.write((char *) &hparams.n_heads, sizeof(hparams.n_heads)); | |
fout.write((char *) &hparams.n_layers, sizeof(hparams.n_layers)); | |
fout.write((char *) &hparams.n_vocab, sizeof(hparams.n_vocab)); | |
fout.write((char *) &hparams.alibi_bias_max, sizeof(hparams.alibi_bias_max)); | |
fout.write((char *) &hparams.clip_qkv, sizeof(hparams.clip_qkv)); | |
fout.write((char *) &ftype_dst, sizeof(ftype_dst)); | |
} | |
// load vocab | |
{ | |
const int32_t n_vocab = hparams.n_vocab; | |
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); | |
} | |
} | |
printf("%s: quantizing tensors\n", __func__); | |
// regexes of tensor names to be quantized | |
const std::vector<std::string> to_quant = { | |
".*weight", | |
}; | |
if (!ggml_common_quantize_0(finp, fout, ftype, to_quant, {})) { | |
fprintf(stderr, "%s: failed to quantize model '%s'\n", __func__, | |
fname_inp.c_str()); | |
return false; | |
} | |
finp.close(); | |
fout.close(); | |
return true; | |
} | |
// usage: | |
// ./mpt-quantize models/mpt/ggml-model.bin | |
// models/mpt/ggml-model-quant.bin type | |
// | |
int main(int argc, char ** argv) { | |
if (argc != 4) { | |
fprintf(stderr, "usage: %s model-f32.bin model-quant.bin type\n", | |
argv[0]); | |
ggml_print_ftypes(stderr); | |
return 1; | |
} | |
// needed to initialize f16 tables | |
{ | |
struct ggml_init_params params = {0, NULL, false}; | |
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 ggml_ftype ftype = ggml_parse_ftype(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 (!mpt_model_quantize(fname_inp, fname_out, ggml_ftype(ftype))) { | |
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; | |
} |