mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-11-14 06:49:54 +00:00
ff5a3f0c09
* Work on the BPE tokenizer Tokenizer tests work for Falcon-7B * Try to fix build problem * Fix debug assertion failure * Fix MSVC Unicode BOM problem * Cleanup and an improvement * Fix compiler warning * Cleanup * Test doesn't work over the full range of Unicodes * Update .gitignore and Makefile * Another Makefile rule * Testing Aquila * Moving byte decoding back to `token_to_piece` ... ... because everyone is using it. * Guarding some unusable code pathes * Streamlining code and adding some more assertions Important change: I'm classifying added tokens as control tokens now for BPE. * Adding a comment * Adding another assertion * Fixed vocabulary guarding assertions * Fix PR for recent change * Fix PR for recent change * Fix for compiler warning * Fix PR for recent change * Fix PR for recent change * Fix PR for recent change * Fix for compiler warning * Fixes for more compiler warnings * Remove unused code * Fix initialization of static maps * Add scores and token types back, adapt gptneox * Update llama.cpp Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update unicode.h Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update unicode.h Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Ported Starcoder and added some assertions * Fix coding style * Apply @jploski 's fix for missing tokens --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
188 lines
6.9 KiB
C++
188 lines
6.9 KiB
C++
#include "llama.h"
|
|
#include "common.h"
|
|
#include "console.h"
|
|
|
|
#include <cstdio>
|
|
#include <string>
|
|
#include <map>
|
|
#include <vector>
|
|
#include <fstream>
|
|
|
|
// generate using test-tokenizer-0-falcon.py
|
|
static const std::map<std::string, std::vector<llama_token>> & k_tests() {
|
|
static std::map<std::string, std::vector<llama_token>> _k_tests = {
|
|
{ "" , { }, },
|
|
{ " " , { 204, }, },
|
|
{ " " , { 258, }, },
|
|
{ " " , { 466, }, },
|
|
{ "\t" , { 192, }, },
|
|
{ "\n" , { 193, }, },
|
|
{ "\t\n" , { 19125, }, },
|
|
{ "Hello world" , { 9856, 1079, }, },
|
|
{ " Hello world" , { 23090, 1079, }, },
|
|
{ "Hello World" , { 9856, 2889, }, },
|
|
{ " Hello World" , { 23090, 2889, }, },
|
|
{ " Hello World!" , { 23090, 2889, 12, }, },
|
|
{ "Hello, world!" , { 9856, 23, 1079, 12, }, },
|
|
{ " Hello, world!" , { 23090, 23, 1079, 12, }, },
|
|
{ " this is 🦙.cpp" , { 414, 304, 3346, 111, 231, 25, 29247, }, },
|
|
{ "w048 7tuijk dsdfhu" , { 98, 55866, 204, 34, 16682, 7149, 36190, 6869, 11481, }, },
|
|
{ "нещо на Български" , { 150, 133, 6207, 151, 215, 150, 134, 5052, 133, 6279, 5052, 223, 151, 216, 49679, 123, 53110, 47043, 7795, }, },
|
|
{ "កាន់តែពិសេសអាចខលចេញ" , { 38154, 206, 38154, 126, 38154, 225, 167, 237, 217, 38154, 221, 167, 237, 208, 38154, 228, 38154, 127, 38154, 237, 167, 237, 207, 38154, 237, 38154, 107, 38154, 126, 38154, 211, 38154, 207, 38154, 233, 38154, 211, 167, 237, 207, 38154, 215, }, },
|
|
{ "🚀 (normal) 😶🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", { 2571, 232, 206, 204, 19, 11003, 20, 8196, 126, 283, 219, 48778, 116, 13392, 204, 19, 51831, 732, 63209, 1741, 7955, 522, 20, 22438, 211, 204, 19, 7927, 53360, 325, 504, 701, 946, 10930, 20, }, },
|
|
{ "Hello" , { 9856, }, },
|
|
{ " Hello" , { 23090, }, },
|
|
{ " Hello" , { 204, 23090, }, },
|
|
{ " Hello" , { 258, 23090, }, },
|
|
{ " Hello" , { 466, 23090, }, },
|
|
{ " Hello\n Hello" , { 466, 23090, 742, 23090, }, },
|
|
};
|
|
|
|
return _k_tests;
|
|
}
|
|
|
|
int main(int argc, char **argv) {
|
|
if (argc < 2) {
|
|
fprintf(stderr, "Usage: %s vocab-file [text-file]\n", argv[0]);
|
|
return 1;
|
|
}
|
|
|
|
const std::string fname = argv[1];
|
|
|
|
std::string fname_text;
|
|
if (argc > 2) {
|
|
fname_text = argv[2];
|
|
}
|
|
|
|
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 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;
|
|
}
|
|
}
|
|
|
|
if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_BPE) {
|
|
fprintf(stderr, "%s : error: vocab type is not BPE\n", __func__);
|
|
llama_free_model(model);
|
|
llama_free(ctx);
|
|
return 2;
|
|
}
|
|
|
|
#ifdef _WIN32
|
|
// We need this for unicode console support
|
|
console::init(false, false);
|
|
atexit([]() { console::cleanup(); });
|
|
#endif
|
|
|
|
bool success = true;
|
|
|
|
for (const auto & test_kv : k_tests()) {
|
|
const std::vector<llama_token> res = llama_tokenize(ctx, test_kv.first, false);
|
|
|
|
printf("\n");
|
|
printf("src: '%s'\n", test_kv.first.c_str());
|
|
printf("res: '%s'\n", llama_detokenize_bpe(ctx, res).c_str());
|
|
printf("tok: ");
|
|
for (const auto & tok : res) {
|
|
printf("%d ", tok);
|
|
}
|
|
printf("\n");
|
|
|
|
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) {
|
|
fprintf(stderr, "%s : failed test: '%s'\n", __func__, test_kv.first.c_str());
|
|
fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__,
|
|
llama_detokenize_bpe(ctx, res).c_str(),
|
|
llama_detokenize_bpe(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;
|
|
}
|
|
}
|
|
|
|
if (!fname_text.empty()) {
|
|
fprintf(stderr, "%s : tokenizing: '%s'\n", __func__, fname_text.c_str());
|
|
|
|
std::string text;
|
|
{
|
|
std::ifstream ifs(fname_text);
|
|
if (!ifs) {
|
|
fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_text.c_str());
|
|
return 1;
|
|
}
|
|
text = std::string(std::istreambuf_iterator<char>(ifs), std::istreambuf_iterator<char>());
|
|
}
|
|
|
|
fprintf(stderr, "%s : text size: %zu\n", __func__, text.size());
|
|
|
|
const std::vector<llama_token> res = llama_tokenize(ctx, text, true);
|
|
|
|
fprintf(stderr, "%s : tokens: %zu\n", __func__, res.size());
|
|
|
|
{
|
|
const std::string fname_out = fname_text + ".tokcpp";
|
|
|
|
std::ofstream ofs(fname_out);
|
|
if (!ofs) {
|
|
fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str());
|
|
return 1;
|
|
}
|
|
|
|
for (const auto & tok : res) {
|
|
ofs << tok << " ";
|
|
}
|
|
|
|
ofs << "\n";
|
|
}
|
|
|
|
fprintf(stderr, "%s : tokens written to '%s'\n", __func__, (fname_text + ".tokcpp").c_str());
|
|
}
|
|
|
|
llama_free_model(model);
|
|
llama_free(ctx);
|
|
|
|
llama_backend_free();
|
|
|
|
return success ? 0 : 3;
|
|
}
|