mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-26 11:24:35 +00:00
16bc66d947
* llama.cpp : split llama_context_params into model and context params ggml-ci * fix metal build * fix freq_base/scale default to model value * llama-bench : keep the same model between tests when possible * move n_threads to llama_context_params, add n_threads_batch * fix mpi build * remove kv_size(), cuda scratch fixes * remove low-vram option * add n_threads_batch to system info, refactor to get_system_info() * add documentation about --threads-batch to the READMEs * llama-bench fix * main : fix rope freq/scale warning * llama.cpp : add llama_get_model common : add llama_tokenize from model * remove duplicated ctx/model functions ggml-ci * cuda : print total VRAM used
193 lines
7.3 KiB
C++
193 lines
7.3 KiB
C++
#include "llama.h"
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#include "common.h"
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#include "console.h"
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#include <cstdio>
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#include <string>
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#include <map>
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#include <vector>
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#include <fstream>
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// generate using test-tokenizer-0-llama.py
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static const std::map<std::string, std::vector<llama_token>> & k_tests() {
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static std::map<std::string, std::vector<llama_token>> _k_tests = {
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{ "" , { }, },
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{ " " , { 259, }, },
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{ " " , { 1678, }, },
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{ " " , { 268, }, },
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{ "\t" , { 29871, 12, }, },
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{ "\n" , { 29871, 13, }, },
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{ "\t\n" , { 29871, 12, 13, }, },
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{ "Hello world" , { 15043, 3186, }, },
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{ " Hello world" , { 29871, 15043, 3186, }, },
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{ "Hello World" , { 15043, 2787, }, },
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{ " Hello World" , { 29871, 15043, 2787, }, },
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{ " Hello World!" , { 29871, 15043, 2787, 29991, }, },
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{ "Hello, world!" , { 15043, 29892, 3186, 29991, }, },
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{ " Hello, world!" , { 29871, 15043, 29892, 3186, 29991, }, },
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{ " this is 🦙.cpp" , { 29871, 445, 338, 29871, 243, 162, 169, 156, 29889, 8223, }, },
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{ "w048 7tuijk dsdfhu" , { 281, 29900, 29946, 29947, 29871, 29955, 9161, 13535, 18031, 2176, 6905, }, },
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{ "нещо на Български" , { 1538, 4851, 665, 1386, 29713, 1305, }, },
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{ "កាន់តែពិសេសអាចខលចេញ" , { 29871, 31849, 31324, 31934, 228, 162, 142, 228, 161, 146, 228, 162, 133, 228, 161, 153, 228, 161, 186, 31708, 228, 162, 132, 31708, 228, 161, 165, 31324, 228, 161, 136, 228, 161, 132, 228, 161, 158, 228, 161, 136, 228, 162, 132, 228, 161, 140, }, },
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{ "🚀 (normal) 😶🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", { 29871, 243, 162, 157, 131, 313, 8945, 29897, 29871, 243, 162, 155, 185, 30722, 243, 162, 143, 174, 30598, 313, 20787, 953, 3848, 275, 16125, 630, 29897, 29871, 31681, 313, 6194, 953, 29877, 2397, 393, 756, 967, 1914, 5993, 29897, }, },
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{ "Hello" , { 15043, }, },
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{ " Hello" , { 29871, 15043, }, },
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{ " Hello" , { 259, 15043, }, },
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{ " Hello" , { 1678, 15043, }, },
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{ " Hello" , { 268, 15043, }, },
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{ " Hello\n Hello" , { 268, 15043, 13, 1678, 15043, }, },
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{ " (" , { 29871, 313, }, },
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};
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return _k_tests;
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}
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int main(int argc, char **argv) {
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if (argc < 2) {
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fprintf(stderr, "Usage: %s vocab-file [text-file]\n", argv[0]);
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return 1;
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}
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const std::string fname = argv[1];
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std::string fname_text;
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if (argc > 2) {
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fname_text = argv[2];
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}
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fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str());
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llama_model * model;
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llama_context * ctx;
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llama_backend_init(false);
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// load the vocab
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{
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auto mparams = llama_model_default_params();
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mparams.vocab_only = true;
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model = llama_load_model_from_file(fname.c_str(), mparams);
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if (model == NULL) {
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fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
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return 1;
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}
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auto cparams = llama_context_default_params();
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ctx = llama_new_context_with_model(model, cparams);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
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llama_free_model(model);
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return 1;
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}
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}
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if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_SPM) {
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fprintf(stderr, "%s : error: vocab type is not SPM\n", __func__);
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llama_free_model(model);
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llama_free(ctx);
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return 2;
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}
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#ifdef _WIN32
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// We need this for unicode console support
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console::init(false, false);
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atexit([]() { console::cleanup(); });
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#endif
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bool success = true;
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for (const auto & test_kv : k_tests()) {
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const std::vector<llama_token> res_bos = llama_tokenize(ctx, test_kv.first, true);
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const std::vector<llama_token> res_nobos = llama_tokenize(ctx, test_kv.first, false);
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printf("\n");
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printf("src: '%s'\n", test_kv.first.c_str());
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printf("res: '%s'\n", llama_detokenize_spm(ctx, res_bos).c_str());
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printf("tok: ");
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for (const auto & tok : res_bos) {
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printf("%d ", tok);
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}
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printf("\n");
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bool correct = res_nobos.size() == test_kv.second.size() && res_bos.size() == res_nobos.size() + 1 && res_bos[0] == 1;
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for (int i = 0; i < (int) res_nobos.size() && correct; ++i) {
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if (test_kv.second[i] != res_bos[i + 1]) {
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correct = false;
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}
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if (test_kv.second[i] != res_nobos[i]) {
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correct = false;
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}
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}
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if (!correct) {
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fprintf(stderr, "%s : failed test: '%s'\n", __func__, test_kv.first.c_str());
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fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__,
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llama_detokenize_spm(ctx, res_nobos).c_str(),
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llama_detokenize_spm(ctx, test_kv.second).c_str());
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fprintf(stderr, "%s : expected tokens: ", __func__);
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for (const auto & t : test_kv.second) {
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fprintf(stderr, "%6d, ", t);
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}
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fprintf(stderr, "\n");
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fprintf(stderr, "%s : got tokens: ", __func__);
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for (const auto & t : res_nobos) {
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fprintf(stderr, "%6d, ", t);
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}
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fprintf(stderr, "\n");
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success = false;
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}
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}
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if (!fname_text.empty()) {
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fprintf(stderr, "%s : tokenizing: '%s'\n", __func__, fname_text.c_str());
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std::string text;
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{
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std::ifstream ifs(fname_text);
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if (!ifs) {
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fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_text.c_str());
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return 1;
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}
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text = std::string(std::istreambuf_iterator<char>(ifs), std::istreambuf_iterator<char>());
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}
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fprintf(stderr, "%s : text size: %zu\n", __func__, text.size());
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const std::vector<llama_token> res = llama_tokenize(ctx, text, true);
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fprintf(stderr, "%s : tokens: %zu\n", __func__, res.size());
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{
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const std::string fname_out = fname_text + ".tokcpp";
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std::ofstream ofs(fname_out);
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if (!ofs) {
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fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str());
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return 1;
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}
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for (const auto & tok : res) {
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ofs << tok << " ";
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}
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ofs << "\n";
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}
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fprintf(stderr, "%s : tokens written to '%s'\n", __func__, (fname_text + ".tokcpp").c_str());
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}
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llama_free_model(model);
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llama_free(ctx);
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llama_backend_free();
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return success ? 0 : 3;
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}
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