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| 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; | |
| } |