#include "llama.h" #include "common.h" #include "console.h" #include #include #include #include #include #include using llama_tests = std::map>; static llama_tests read_tests(const std::string & fname_inp, const std::string & fname_out) { llama_tests tests; std::ifstream ifs_inp(fname_inp); if (!ifs_inp) { fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_inp.c_str()); return tests; } std::string sraw((std::istreambuf_iterator(ifs_inp)), std::istreambuf_iterator()); std::ifstream ifs_out(fname_out); if (!ifs_out) { fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str()); return tests; } std::vector sout; for (std::string line; std::getline(ifs_out, line);) { sout.push_back(line); } const std::string sep = "\n__ggml_vocab_test__\n"; std::vector sinp; size_t pos = 0; while (pos < sraw.size()) { const size_t next = sraw.find(sep, pos); if (next == std::string::npos) { sinp.push_back(sraw.substr(pos)); break; } sinp.push_back(sraw.substr(pos, next - pos)); pos = next + sep.size(); } if (sinp.size() != sout.size()) { fprintf(stderr, "%s : error: input and output files have different number of tests\n", __func__); return tests; } for (size_t i = 0; i < sinp.size(); ++i) { const std::string & s = sinp[i]; const std::string & o = string_strip(sout[i]); std::vector toks; size_t pos = 0; while (pos < o.size()) { size_t next = o.find(' ', pos); if (next == std::string::npos) { next = o.size(); } const std::string stok = o.substr(pos, next - pos); toks.push_back(std::stoi(stok)); pos = next + 1; } tests[s] = toks; } return tests; } int main(int argc, char const *argv[]) { if (argc < 2) { fprintf(stderr, "Usage: %s vocab-file \n", argv[0]); return 1; } const std::string fname = argv[1]; const std::string fname_inp = fname + ".inp"; const std::string fname_out = fname + ".out"; fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str()); llama_model * model; llama_context * ctx; llama_backend_init(); // load the vocab { auto mparams = llama_model_default_params(); mparams.vocab_only = true; model = llama_load_model_from_file(fname.c_str(), mparams); if (model == NULL) { fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); return 1; } auto cparams = llama_context_default_params(); ctx = llama_new_context_with_model(model, cparams); if (ctx == NULL) { fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); llama_free_model(model); return 1; } } #ifdef _WIN32 // We need this for unicode console support console::init(false, false); atexit([]() { console::cleanup(); }); #endif const int nthread = std::thread::hardware_concurrency(); std::vector threads(nthread); bool success = true; const auto k_tests = [&]() -> llama_tests { const auto res = read_tests(fname_inp, fname_out); if (res.empty()) { fprintf(stderr, "%s : error: no tests found\n", __func__); exit(1); } return res; }(); const bool add_special = false; for (int i = 0; i < nthread; i++) { threads[i] = std::thread([&]() { for (const auto & test_kv : k_tests) { const std::vector res = llama_tokenize(ctx, test_kv.first, add_special, false); bool correct = res.size() == test_kv.second.size(); for (int i = 0; i < (int) res.size() && correct; ++i) { if (test_kv.second[i] != res[i]) { correct = false; } } if (!correct) { success = false; } } }); } for (int i = 0; i < nthread; i++) { threads[i].join(); } llama_free_model(model); llama_free(ctx); llama_backend_free(); printf("\n"); printf("Tests %s\n", success ? "passed" : "failed"); return success ? 0 : 3; }