mirror of
https://github.com/ggerganov/llama.cpp.git
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f486f6e1e5
* Added numa options to allow finer grained control as well as plumbing for a new mirror mode that will require numa.h * Reverted Makefile * Fixed include * Removed sched.h from ggml.h, moved ggml_get_numa_affinity into ggml.c, removed trailing whitespace and fixed up a few inconsistent variables * removed trailing whitespace * Added numa options to allow finer grained control as well as plumbing for a new mirror mode that will require numa.h * Reverting Makefile * Fixed a number of issues with the move from BOOL to ggml_numa_strategies. Added a note about mirror mode note being implemented yet * Removing MIRROR_MODE code for this PR * Removing last bit of MIRROR_MODE code for this PR * Removing unneeded branch in server.cpp example and moving get_numa_affinity and making it static * Fixed lingering init_llama_backend() bool calls in tests and examples * Remote enum llama_numa_strategies * Revert bad merge with dynatemp flags * add missing enum ggml_numa_strategies declaration and revert sync problem with master * add missing enum ggml_numa_strategies declaration * fixed ggml_init_numa variable * Update ggml.h Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * Update READMEs with info about numa flags, change INTERLEAVE strategy name to DISTRIBUTE everywhere, implement the improved distribution strategy from @rankaiyx, fix a spelling mistake and un-merge some bad merges * split numa init out from llama_backend_init and created llama_numa_init. Updated all code paths and samples * Fix up some boolean vs enum comparisons * Added #ifdefs for non-Linux OS that don't have cpu_set_t datatype * Update ggml.h Align enum values Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml.c Remove whitespace Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml.c align paremeters Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update examples/server/server.cpp remove whitespace and align brace Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update common/common.cpp Remove whitespace and align brace Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * unified ggml_numa_strategy enum and fixed text alignment in server.cpp example * Update ggml.c simplified return for platforms without NUMA support Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * removed redundant else from cli argument processing of --numa * whitespace --------- Co-authored-by: root <root@nenya.lothlorien.ca> Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Jared Van Bortel <jared@nomic.ai>
124 lines
3.8 KiB
C++
124 lines
3.8 KiB
C++
#include "llama.h"
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#include "common.h"
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#include "unicode.h"
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#include "console.h"
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#include <cassert>
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#include <codecvt>
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#include <cstdio>
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#include <cstring>
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#include <locale>
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#include <string>
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#include <thread>
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#include <vector>
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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>\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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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();
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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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GGML_ASSERT(llama_vocab_type(model) == LLAMA_VOCAB_TYPE_BPE);
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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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const int n_vocab = llama_n_vocab(model);
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for (int i = 0; i < n_vocab; ++i) {
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std::string str = llama_detokenize_bpe(ctx, std::vector<int>(1, i));
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try {
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auto cps = codepoints_from_utf8(str);
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std::vector<llama_token> tokens = llama_tokenize(ctx, str, false);
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std::string check = llama_detokenize_bpe(ctx, tokens);
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if (check != str) {
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fprintf(stderr, "%s : error: token %d detokenizes to '%s'(%zu) but tokenization of this detokenizes to '%s'(%zu)\n",
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__func__, i, str.c_str(), str.length(), check.c_str(), check.length());
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return 2;
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}
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}
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catch (const std::invalid_argument &) {
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//fprintf(stderr, "%s : info: utf8 conversion %d '%s'\n", __func__, i, str.c_str());
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}
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}
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// unicode
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{
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const int nthread = std::thread::hardware_concurrency();
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std::vector<std::thread> threads(nthread);
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for (int i = 0; i < nthread; ++i) {
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threads[i] = std::thread([i, nthread, ctx]() {
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for (uint32_t cp = i; cp < 0x0010ffff; cp += nthread) {
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if (!( // NOLINT
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(cp < 0x03 || cp > 0x05) && cp != 0x0b && cp != 0x11 &&
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(cp < 0x13 || cp > 0x17) && cp != 0x19 &&
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(cp < 0x1c || cp > 0x1e) &&
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(cp < 0xd800 || cp > 0xdfff) &&
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(cp < 0x00040000 || cp >= 0x000e0000)
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)) {
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continue;
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}
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std::string str = codepoint_to_utf8(cp);
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std::vector<llama_token> tokens = llama_tokenize(ctx, str, false);
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std::string check = llama_detokenize_bpe(ctx, tokens);
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if (cp != 9601 && str != check) {
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fprintf(stderr, "error: codepoint %x detokenizes to '%s'(%zu) instead of '%s'(%zu)\n",
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cp, check.c_str(), check.length(), str.c_str(), str.length());
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std::exit(3);
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}
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}
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});
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}
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for (auto & t : threads) {
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t.join();
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}
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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 0;
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}
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