mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-26 11:24:35 +00:00
132 lines
5.0 KiB
C++
132 lines
5.0 KiB
C++
#include "llama.h"
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#include "common.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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static std::string unescape_whitespace(llama_context* ctx, const std::vector<llama_token>& tokens) {
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std::string result;
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for (size_t i = 0; i < tokens.size(); ++i) {
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result += llama_token_to_str(ctx, tokens[i]);
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}
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return result;
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}
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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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{ " ", {1, 259, }, },
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{ "\t", { 1, 29871, 12, }, },
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{ "\n", { 1, 29871, 13, }, },
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{ "\t\n", { 1, 29871, 12, 13, }, },
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{ "Hello world", { 1, 15043, 3186, }, },
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{ " Hello world", { 1, 29871, 15043, 3186, }, },
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{ "Hello World", { 1, 15043, 2787, }, },
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{ " Hello World", { 1, 29871, 15043, 2787, }, },
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{ " Hello World!", { 1, 29871, 15043, 2787, 29991, }, },
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{ " this is 🦙.cpp", { 1, 29871, 445, 338, 29871, 243, 162, 169, 156, 29889, 8223, }, },
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{ "w048 7tuijk dsdfhu", { 1, 281, 29900, 29946, 29947, 29871, 29955, 9161, 13535, 18031, 2176, 6905, }, },
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{ "нещо на Български", { 1, 1538, 4851, 665, 1386, 29713, 1305, }, },
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{ "កាន់តែពិសេសអាចខលចេញ", { 1, 29871, 31849, 31324, 31934, 228, 162, 142, 228, 161,
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146, 228, 162, 133, 228, 161, 153, 228, 161, 186,
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31708, 228, 162, 132, 31708, 228, 161, 165, 31324, 228,
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161, 136, 228, 161, 132, 228, 161, 158, 228, 161,
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136, 228, 162, 132, 228, 161, 140, }, },
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{ "🚀 (normal) 😶🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)",
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{ 1, 29871, 243, 162, 157, 131, 313, 8945, 29897, 29871,
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243, 162, 155, 185, 30722, 243, 162, 143, 174, 30598,
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313, 20787, 953, 3848, 275, 16125, 630, 29897, 29871, 31681,
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313, 6194, 953, 29877, 2397, 393, 756, 967, 1914, 5993, 29897, }, },
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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>\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(false);
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// load the vocab
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{
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auto lparams = llama_context_default_params();
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lparams.vocab_only = true;
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model = llama_load_model_from_file(fname.c_str(), lparams);
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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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ctx = llama_new_context_with_model(model, lparams);
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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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const int n_vocab = llama_n_vocab(ctx);
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if (n_vocab != 32000) {
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fprintf(stderr, "%s : expected 32000 tokens, got %d\n", __func__, n_vocab);
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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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bool success = true;
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for (const auto & test_kv : k_tests()) {
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std::vector<llama_token> res = llama_tokenize(ctx, test_kv.first, true);
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fprintf(stderr, "%s : '%s' tokenized to '%s'\n",
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__func__, test_kv.first.c_str(), unescape_whitespace(ctx, res).c_str());
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bool correct = res.size() == test_kv.second.size();
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for (int i = 0; i < (int) res.size() && correct; ++i) {
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if (res[i] != test_kv.second[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'\n", __func__, unescape_whitespace(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) {
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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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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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