#include "llama.h" #include #include #include #include static const std::map> & k_tests() { static std::map> _k_tests = { { "Hello World", { 1, 10994, 2787, }, }, { " Hello World", { 1, 15043, 2787, }, }, { " Hello World!", { 1, 15043, 2787, 29991, }, }, { " this is 🦙.cpp", { 1, 445, 338, 29871, 243, 162, 169, 156, 29889, 8223, }, }, { "w048 7tuijk dsdfhu", { 1, 29893, 29900, 29946, 29947, 29871, 29955, 9161, 13535, 18031, 2176, 6905, }, }, { "нещо на Български", { 1, 821, 4851, 665, 1386, 29713, 1305, }, }, { "\xe6\x88\x91\xe4\xbb\xac\xe5\xa4\xa7\xe5\xae\xb6\xe4\xb8\x80\xe8\xb5\xb7", { 1, 30672, 31381, 30257, 30613, 30287, 31558, }, }, { " >>>>ANSWER<<", {1, 5099, 6778, 2190, 23066, 1001, 9314}, }, }; return _k_tests; }; int main(int argc, char **argv) { if (argc < 2) { fprintf(stderr, "Usage: %s \n", argv[0]); return 1; } const std::string fname = argv[1]; fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str()); llama_model * model; llama_context * ctx; // load the vocab { auto lparams = llama_context_default_params(); lparams.vocab_only = true; model = llama_load_model_from_file(fname.c_str(), lparams); if (model == NULL) { fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); return 1; } ctx = llama_new_context_with_model(model, lparams); if (ctx == NULL) { fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); llama_free_model(model); return 1; } } const int n_vocab = llama_n_vocab(ctx); if (n_vocab != 32000) { fprintf(stderr, "%s : expected 32000 tokens, got %d\n", __func__, n_vocab); llama_free_model(model); llama_free(ctx); return 2; } for (const auto & test_kv : k_tests()) { std::vector res(test_kv.first.size()); const int n = llama_tokenize(ctx, test_kv.first.c_str(), res.data(), int(res.size()), true); res.resize(n); bool correct = res.size() == test_kv.second.size(); for (int i = 0; i < (int) res.size() && correct; ++i) { if (res[i] != test_kv.second[i]) { correct = false; } } if (!correct) { fprintf(stderr, "%s : failed test: '%s'\n", __func__, test_kv.first.c_str()); fprintf(stderr, "%s : expected tokens: ", __func__); for (const auto & t : test_kv.second) { fprintf(stderr, "%6d, ", t); } fprintf(stderr, "\n"); for (const auto & t : test_kv.second) { fprintf(stderr, "%7s ", llama_token_to_str(ctx, t)); } fprintf(stderr, "\n"); fprintf(stderr, "%s : got tokens: ", __func__); for (const auto & t : res) { fprintf(stderr, "%6d, ", t); } fprintf(stderr, "\n"); for (const auto & t : res) { fprintf(stderr, "%7s ", llama_token_to_str(ctx, t)); } fprintf(stderr, "\n"); llama_free_model(model); llama_free(ctx); return 3; } } #if 0 // how many tokens would not tokenize to themselves for (llama_token i = 1; i < llama_n_vocab(ctx); i++) { const char* str = llama_token_to_str(ctx, i); std::vector res(100); const int n = llama_tokenize(ctx, str, res.data(), int(res.size()), false); res.resize(n); for (const auto & t : res) { //if (t == 1) continue; if (t != i) { fprintf(stderr, "%s : failed test: '%s'\n", __func__, str); fprintf(stderr, "%s : expected tokens: %d\n", __func__, i); fprintf(stderr, "%s : got tokens: ", __func__); for (const auto & t : res) { fprintf(stderr, "%6d, ", t); } for (const auto & t : res) { fprintf(stderr, "%s|", llama_token_to_str(ctx, t)); } fprintf(stderr, "\n"); } } } #endif llama_free_model(model); llama_free(ctx); return 0; }