mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2025-10-31 08:51:55 +00:00
7494c78428
* llama : sync gguf-llama with llama * tests : fix build + warnings (test-tokenizer-1 still fails) * tests : fix wstring_convert * convert : fix layer names * llama : sync gguf-llama.cpp * convert : update HF converter to new tokenizer voodoo magics
129 lines
3.8 KiB
C++
129 lines
3.8 KiB
C++
#define LLAMA_API_CPP // TODO: eliminate me
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#include "llama.h"
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#include <cassert>
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#include <cstdio>
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#include <cstring>
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#include <string>
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#include <codecvt>
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#include <map>
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#include <vector>
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#include <locale>
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static std::string vocab_type(llama_context * ctx) {
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return llama_n_vocab(ctx) == 32000 ? "spm": "bpe";
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}
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static std::string escape_whitespace(const std::string& text) {
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std::string result;
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bool escaping = false;
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result += "\xe2\x96\x81";
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for (size_t offs = 0; offs < text.length(); ++offs) {
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if (text[offs] == ' ') {
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if (!escaping) {
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result += "\xe2\x96\x81";
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escaping = true;
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}
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}
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else {
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escaping = false;
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result += text[offs];
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}
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}
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return result;
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}
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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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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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for (int i = 0; i < n_vocab; ++i) {
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std::string forward = llama_token_to_str_bpe(ctx, i);
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std::vector<llama_token> tokens = llama_tokenize_bpe(ctx, forward, false);
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if (tokens.size() == 1) {
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if (i != tokens[0]) {
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std::string backward = llama_token_to_str(ctx, tokens[0]);
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fprintf(stderr, "%s : error: token %d is string %s but bpe returns token %d %s\n",
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__func__, i, llama_token_to_str(ctx, i).c_str(), tokens[0], backward.c_str());
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return 2;
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}
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} else {
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if ((vocab_type(ctx) == "spm" && i <= 258) ||
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(vocab_type(ctx) == "bpe" && (i == 0 || i >= 100000))) {
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fprintf(stderr, "%s : info: token %d is string %s and bpe returns tokens %s\n",
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__func__, i, llama_token_to_str(ctx, i).c_str(), unescape_whitespace(ctx, tokens).c_str());
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} else {
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fprintf(stderr, "%s : error: token %d is string %s but bpe returns tokens %s\n",
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__func__, i, llama_token_to_str(ctx, i).c_str(), unescape_whitespace(ctx, tokens).c_str());
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return 2;
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}
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}
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}
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std::wstring_convert<typename std::codecvt_utf8<wchar_t>, wchar_t> converter;
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for (wchar_t ch = 0x0000; ch < 0xffff; ++ch) {
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std::wstring wstr(1, ch);
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std::string str;
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try {
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str = converter.to_bytes(wstr);
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} catch (std::exception & e) {
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continue;
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}
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std::vector<llama_token> tokens = llama_tokenize(ctx, escape_whitespace(str), false);
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if (tokens.size() == 1) {
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fprintf(stderr, "%s : info: %s tokenized to %d \n",
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__func__, str.c_str(), tokens[0]);
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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 0;
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}
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