mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-25 13:58:46 +01:00
331 lines
11 KiB
C++
331 lines
11 KiB
C++
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#include "ggml.h"
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#include "utils.h"
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#include <cassert>
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#include <cmath>
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#include <cstdio>
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#include <cstring>
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#include <fstream>
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#include <map>
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#include <string>
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#include <vector>
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#include <regex>
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// TODO: move somewhere else
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#define QK 32
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// default hparams (LLaMA76B)
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struct llama_hparams {
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int32_t n_vocab = 32000;
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int32_t n_ctx = 512; // this is provided as user input?
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int32_t n_embd = 4096;
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int32_t n_mult = 256;
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int32_t n_head = 32;
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int32_t n_layer = 32;
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int32_t n_rot = 64;
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int32_t f16 = 1;
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};
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// quantize a model
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bool llama_model_quantize(const std::string & fname_inp, const std::string & fname_out, int itype) {
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ggml_type type = GGML_TYPE_Q4_1;
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switch (itype) {
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case 2: type = GGML_TYPE_Q4_0; break;
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case 3: type = GGML_TYPE_Q4_1; break;
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default: fprintf(stderr, "%s: invalid quantization type %d\n", __func__, itype); return 1;
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};
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if (type != GGML_TYPE_Q4_0 && type != GGML_TYPE_Q4_1) {
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fprintf(stderr, "%s: invalid quantization type %d\n", __func__, type);
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return false;
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}
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gpt_vocab vocab;
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printf("%s: loading model from '%s'\n", __func__, fname_inp.c_str());
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auto finp = std::ifstream(fname_inp, std::ios::binary);
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if (!finp) {
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fprintf(stderr, "%s: failed to open '%s' for reading\n", __func__, fname_inp.c_str());
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return false;
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}
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auto fout = std::ofstream(fname_out, std::ios::binary);
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if (!fout) {
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fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname_out.c_str());
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return false;
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}
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// verify magic
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{
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uint32_t magic;
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finp.read((char *) &magic, sizeof(magic));
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if (magic != 0x67676d6c) {
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fprintf(stderr, "%s: invalid model file '%s' (bad magic)\n", __func__, fname_inp.c_str());
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return false;
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}
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fout.write((char *) &magic, sizeof(magic));
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}
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llama_hparams hparams;
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// load hparams
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{
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finp.read((char *) &hparams.n_vocab, sizeof(hparams.n_vocab));
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//finp.read((char *) &hparams.n_ctx, sizeof(hparams.n_ctx));
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finp.read((char *) &hparams.n_embd, sizeof(hparams.n_embd));
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finp.read((char *) &hparams.n_mult, sizeof(hparams.n_mult));
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finp.read((char *) &hparams.n_head, sizeof(hparams.n_head));
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finp.read((char *) &hparams.n_layer, sizeof(hparams.n_layer));
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finp.read((char *) &hparams.n_rot, sizeof(hparams.n_rot));
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finp.read((char *) &hparams.f16, sizeof(hparams.f16));
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printf("%s: n_vocab = %d\n", __func__, hparams.n_vocab);
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printf("%s: n_ctx = %d\n", __func__, hparams.n_ctx);
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printf("%s: n_embd = %d\n", __func__, hparams.n_embd);
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printf("%s: n_mult = %d\n", __func__, hparams.n_mult);
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printf("%s: n_head = %d\n", __func__, hparams.n_head);
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printf("%s: n_layer = %d\n", __func__, hparams.n_layer);
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printf("%s: f16 = %d\n", __func__, hparams.f16);
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fout.write((char *) &hparams.n_vocab, sizeof(hparams.n_vocab));
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//fout.write((char *) &hparams.n_ctx, sizeof(hparams.n_ctx));
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fout.write((char *) &hparams.n_embd, sizeof(hparams.n_embd));
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fout.write((char *) &hparams.n_mult, sizeof(hparams.n_mult));
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fout.write((char *) &hparams.n_head, sizeof(hparams.n_head));
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fout.write((char *) &hparams.n_layer, sizeof(hparams.n_layer));
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fout.write((char *) &hparams.n_rot, sizeof(hparams.n_rot));
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fout.write((char *) &itype, sizeof(hparams.f16));
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}
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// load vocab
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{
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const int32_t n_vocab = hparams.n_vocab;
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if (n_vocab != hparams.n_vocab) {
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fprintf(stderr, "%s: invalid model file '%s' (bad vocab size %d != %d)\n",
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__func__, fname_inp.c_str(), n_vocab, hparams.n_vocab);
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return false;
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}
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std::string word;
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for (int i = 0; i < n_vocab; i++) {
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uint32_t len;
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finp.read ((char *) &len, sizeof(len));
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fout.write((char *) &len, sizeof(len));
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word.resize(len);
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finp.read ((char *) word.data(), len);
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fout.write((char *) word.data(), len);
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vocab.token_to_id[word] = i;
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vocab.id_to_token[i] = word;
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}
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}
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// load weights
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{
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size_t total_size_org = 0;
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size_t total_size_new = 0;
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std::vector<float> work;
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std::vector<uint8_t> data_u8;
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std::vector<ggml_fp16_t> data_f16;
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std::vector<float> data_f32;
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std::vector<int64_t> hist_all(1 << 4, 0);
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while (true) {
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int32_t n_dims;
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int32_t length;
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int32_t ftype;
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finp.read(reinterpret_cast<char *>(&n_dims), sizeof(n_dims));
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finp.read(reinterpret_cast<char *>(&length), sizeof(length));
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finp.read(reinterpret_cast<char *>(&ftype), sizeof(ftype));
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if (finp.eof()) {
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break;
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}
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int32_t nelements = 1;
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int32_t ne[2] = { 1, 1 };
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for (int i = 0; i < n_dims; ++i) {
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finp.read (reinterpret_cast<char *>(&ne[i]), sizeof(ne[i]));
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nelements *= ne[i];
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}
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std::string name(length, 0);
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finp.read (&name[0], length);
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{
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static const char * ftype_str[] = { "f32", "f16", "q4_0", "q4_1", };
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printf("%48s - [%5d, %5d], type = %6s ", name.data(), ne[0], ne[1], ftype_str[ftype]);
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}
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// regexes of tensor names to be quantized
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const std::vector<std::string> k_names = {
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".*weight",
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};
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bool quantize = false;
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for (const auto & s : k_names) {
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if (std::regex_match(name, std::regex(s))) {
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quantize = true;
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break;
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}
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}
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// quantize only 2D tensors
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quantize &= (n_dims == 2);
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if (quantize) {
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if (ftype != 0 && ftype != 1) {
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fprintf(stderr, "%s: unsupported ftype %d for integer quantization\n", __func__, ftype);
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return false;
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}
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if (ftype == 1) {
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data_f16.resize(nelements);
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finp.read(reinterpret_cast<char *>(data_f16.data()), nelements * sizeof(ggml_fp16_t));
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data_f32.resize(nelements);
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for (int i = 0; i < nelements; ++i) {
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data_f32[i] = ggml_fp16_to_fp32(data_f16[i]);
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}
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} else {
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data_f32.resize(nelements);
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finp.read(reinterpret_cast<char *>(data_f32.data()), nelements * sizeof(float));
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}
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ftype = itype;
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} else {
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const int bpe = (ftype == 0) ? sizeof(float) : sizeof(uint16_t);
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data_u8.resize(nelements*bpe);
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finp.read(reinterpret_cast<char *>(data_u8.data()), nelements * bpe);
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}
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fout.write(reinterpret_cast<char *>(&n_dims), sizeof(n_dims));
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fout.write(reinterpret_cast<char *>(&length), sizeof(length));
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fout.write(reinterpret_cast<char *>(&ftype), sizeof(ftype));
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for (int i = 0; i < n_dims; ++i) {
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fout.write(reinterpret_cast<char *>(&ne[i]), sizeof(ne[i]));
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}
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fout.write(&name[0], length);
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if (quantize) {
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printf("quantizing .. ");
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work.resize(nelements); // for quantization
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size_t cur_size = 0;
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std::vector<int64_t> hist_cur(1 << 4, 0);
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switch (type) {
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case GGML_TYPE_Q4_0:
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{
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cur_size = ggml_quantize_q4_0(data_f32.data(), work.data(), nelements, ne[0], QK, hist_cur.data());
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} break;
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case GGML_TYPE_Q4_1:
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{
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cur_size = ggml_quantize_q4_1(data_f32.data(), work.data(), nelements, ne[0], QK, hist_cur.data());
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} break;
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default:
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{
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fprintf(stderr, "%s: unsupported quantization type %d\n", __func__, type);
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return false;
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}
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}
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fout.write(reinterpret_cast<char *>(work.data()), cur_size);
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total_size_new += cur_size;
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printf("size = %8.2f MB -> %8.2f MB | hist: ", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0);
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for (int i = 0; i < hist_cur.size(); ++i) {
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hist_all[i] += hist_cur[i];
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}
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for (int i = 0; i < hist_cur.size(); ++i) {
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printf("%5.3f ", hist_cur[i] / (float)nelements);
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}
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printf("\n");
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} else {
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printf("size = %8.3f MB\n", data_u8.size()/1024.0/1024.0);
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fout.write(reinterpret_cast<char *>(data_u8.data()), data_u8.size());
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total_size_new += data_u8.size();
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}
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total_size_org += nelements * sizeof(float);
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}
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printf("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
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printf("%s: quant size = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0);
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{
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int64_t sum_all = 0;
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for (int i = 0; i < hist_all.size(); ++i) {
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sum_all += hist_all[i];
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}
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printf("%s: hist: ", __func__);
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for (int i = 0; i < hist_all.size(); ++i) {
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printf("%5.3f ", hist_all[i] / (float)sum_all);
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}
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printf("\n");
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}
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}
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finp.close();
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fout.close();
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return true;
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}
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// usage:
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// ./llama-quantize models/llama/ggml-model.bin models/llama/ggml-model-quant.bin type
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//
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int main(int argc, char ** argv) {
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if (argc != 4) {
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fprintf(stderr, "usage: %s model-f32.bin model-quant.bin type\n", argv[0]);
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fprintf(stderr, " type = 2 - q4_0\n");
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fprintf(stderr, " type = 3 - q4_1\n");
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return 1;
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}
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const std::string fname_inp = argv[1];
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const std::string fname_out = argv[2];
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const int itype = atoi(argv[3]);
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const int64_t t_main_start_us = ggml_time_us();
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int64_t t_quantize_us = 0;
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// load the model
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{
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const int64_t t_start_us = ggml_time_us();
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if (!llama_model_quantize(fname_inp, fname_out, itype)) {
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fprintf(stderr, "%s: failed to quantize model from '%s'\n", __func__, fname_inp.c_str());
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return 1;
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}
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t_quantize_us = ggml_time_us() - t_start_us;
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}
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// report timing
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{
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const int64_t t_main_end_us = ggml_time_us();
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printf("\n");
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printf("%s: quantize time = %8.2f ms\n", __func__, t_quantize_us/1000.0f);
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printf("%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0f);
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}
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return 0;
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}
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