llama.cpp/tests/test-tokenizer-0.cpp

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#include "llama.h"
#include "common.h"
#include <cstdio>
#include <string>
#include <map>
#include <vector>
static std::string unescape_whitespace(llama_context* ctx, const std::vector<llama_token>& tokens) {
std::string result;
for (size_t i = 0; i < tokens.size(); ++i) {
result += llama_token_to_str(ctx, tokens[i]);
}
return result;
}
static const std::map<std::string, std::vector<llama_token>> & k_tests() {
static std::map<std::string, std::vector<llama_token>> _k_tests = {
{ " ", {1, 259, }, },
{ "\t", { 1, 29871, 12, }, },
{ "\n", { 1, 29871, 13, }, },
{ "\t\n", { 1, 29871, 12, 13, }, },
{ "Hello world", { 1, 15043, 3186, }, },
{ " Hello world", { 1, 29871, 15043, 3186, }, },
{ "Hello World", { 1, 15043, 2787, }, },
{ " Hello World", { 1, 29871, 15043, 2787, }, },
{ " Hello World!", { 1, 29871, 15043, 2787, 29991, }, },
{ " this is 🦙.cpp", { 1, 29871, 445, 338, 29871, 243, 162, 169, 156, 29889, 8223, }, },
{ "w048 7tuijk dsdfhu", { 1, 281, 29900, 29946, 29947, 29871, 29955, 9161, 13535, 18031, 2176, 6905, }, },
{ "нещо на Български", { 1, 1538, 4851, 665, 1386, 29713, 1305, }, },
{ "កាន់តែពិសេសអាចខលចេញ", { 1, 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, }, },
{ "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)",
{ 1, 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, }, },
};
return _k_tests;
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}
int main(int argc, char **argv) {
if (argc < 2) {
fprintf(stderr, "Usage: %s <vocab-file>\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;
llama_backend_init(false);
// 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;
}
bool success = true;
for (const auto & test_kv : k_tests()) {
std::vector<llama_token> res = llama_tokenize(ctx, test_kv.first, true);
fprintf(stderr, "%s : '%s' tokenized to '%s'\n",
__func__, test_kv.first.c_str(), unescape_whitespace(ctx, res).c_str());
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 : detokenized to: '%s'\n", __func__, unescape_whitespace(ctx, test_kv.second).c_str());
fprintf(stderr, "%s : expected tokens: ", __func__);
for (const auto & t : test_kv.second) {
fprintf(stderr, "%6d, ", t);
}
fprintf(stderr, "\n");
fprintf(stderr, "%s : got tokens: ", __func__);
for (const auto & t : res) {
fprintf(stderr, "%6d, ", t);
}
fprintf(stderr, "\n");
success = false;
}
}
llama_free_model(model);
llama_free(ctx);
llama_backend_free();
return success ? 0 : 3;
}