ikawrakow/ik_llama.cpp
1
0
Fork 0
mirror of https://github.com/ikawrakow/ik_llama.cpp.git synced 2026-02-23 22:54:10 +00:00
Code Issues Packages Projects Releases Wiki Activity

Builds successfully

Browse Source
This commit is contained in:
Iwan Kawrakow
2025-08-13 14:31:48 +03:00
parent 6b6d25bfbf
commit 949b686412
10 changed files with 3148 additions and 1863 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
examples/sweep-bench/sweep-bench.cpp
View File

@@ -61,7 +61,7 @@ int main(int argc, char ** argv) {
const llama_vocab * vocab = llama_get_vocab(ctx);
llama_token bos = llama_token_bos_impl(*vocab);
llama_token bos = vocab->token_bos();
//llama_token eos = llama_token_eos_impl(*vocab);
const unsigned int n_vocab = llama_n_vocab(model);

84
include/llama.h
View File

@@ -70,50 +70,52 @@ extern "C" {
typedef int32_t llama_seq_id;
enum llama_vocab_type {
LLAMA_VOCAB_TYPE_NONE = 0, // For models without vocab
LLAMA_VOCAB_TYPE_SPM = 1, // LLaMA tokenizer based on byte-level BPE with byte fallback
LLAMA_VOCAB_TYPE_BPE = 2, // GPT-2 tokenizer based on byte-level BPE
LLAMA_VOCAB_TYPE_WPM = 3, // BERT tokenizer based on WordPiece
LLAMA_VOCAB_TYPE_UGM = 4, // T5 tokenizer based on Unigram
LLAMA_VOCAB_TYPE_NONE = 0, // For models without vocab
LLAMA_VOCAB_TYPE_SPM = 1, // LLaMA tokenizer based on byte-level BPE with byte fallback
LLAMA_VOCAB_TYPE_BPE = 2, // GPT-2 tokenizer based on byte-level BPE
LLAMA_VOCAB_TYPE_WPM = 3, // BERT tokenizer based on WordPiece
LLAMA_VOCAB_TYPE_UGM = 4, // T5 tokenizer based on Unigram
LLAMA_VOCAB_TYPE_RWKV = 5, // RWKV tokenizer based on greedy tokenization
LLAMA_VOCAB_TYPE_PLAMO2 = 6, // PLaMo-2 tokenizer based on Aho-Corasick with dynamic programming
};
// pre-tokenization types
enum llama_vocab_pre_type {
LLAMA_VOCAB_PRE_TYPE_DEFAULT = 0,
LLAMA_VOCAB_PRE_TYPE_LLAMA3 = 1,
LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM = 2,
LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_CODER = 3,
LLAMA_VOCAB_PRE_TYPE_FALCON = 4,
LLAMA_VOCAB_PRE_TYPE_MPT = 5,
LLAMA_VOCAB_PRE_TYPE_STARCODER = 6,
LLAMA_VOCAB_PRE_TYPE_GPT2 = 7,
LLAMA_VOCAB_PRE_TYPE_REFACT = 8,
LLAMA_VOCAB_PRE_TYPE_COMMAND_R = 9,
LLAMA_VOCAB_PRE_TYPE_STABLELM2 = 10,
LLAMA_VOCAB_PRE_TYPE_QWEN2 = 11,
LLAMA_VOCAB_PRE_TYPE_OLMO = 12,
LLAMA_VOCAB_PRE_TYPE_DBRX = 13,
LLAMA_VOCAB_PRE_TYPE_SMAUG = 14,
LLAMA_VOCAB_PRE_TYPE_PORO = 15,
LLAMA_VOCAB_PRE_TYPE_CHATGLM3 = 16,
LLAMA_VOCAB_PRE_TYPE_CHATGLM4 = 17,
LLAMA_VOCAB_PRE_TYPE_VIKING = 18,
LLAMA_VOCAB_PRE_TYPE_JAIS = 19,
LLAMA_VOCAB_PRE_TYPE_TEKKEN = 20,
LLAMA_VOCAB_PRE_TYPE_SMOLLM = 21,
LLAMA_VOCAB_PRE_TYPE_CODESHELL = 22,
LLAMA_VOCAB_PRE_TYPE_DEEPSEEK3_LLM = 28, //llama.cpp lists this as 28
LLAMA_VOCAB_PRE_TYPE_GPT4O = 29,
LLAMA_VOCAB_PRE_TYPE_SUPERBPE = 30,
LLAMA_VOCAB_PRE_TYPE_TRILLION = 31,
LLAMA_VOCAB_PRE_TYPE_BAILINGMOE = 32,
LLAMA_VOCAB_PRE_TYPE_LLAMA4 = 33,
LLAMA_VOCAB_PRE_TYPE_FALCON_3 = 34,
LLAMA_VOCAB_PRE_TYPE_FALCON_E = 35,
LLAMA_VOCAB_PRE_TYPE_SEED_CODER = 36, //llama.cpp lists this as 35
LLAMA_VOCAB_PRE_TYPE_HUNYUAN = 37, //llama.cpp lists this as 36
LLAMA_VOCAB_PRE_TYPE_KIMI_K2 = 38, //llama.cpp lists this as 37
};
//enum llama_vocab_pre_type {
// LLAMA_VOCAB_PRE_TYPE_DEFAULT = 0,
// LLAMA_VOCAB_PRE_TYPE_LLAMA3 = 1,
// LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM = 2,
// LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_CODER = 3,
// LLAMA_VOCAB_PRE_TYPE_FALCON = 4,
// LLAMA_VOCAB_PRE_TYPE_MPT = 5,
// LLAMA_VOCAB_PRE_TYPE_STARCODER = 6,
// LLAMA_VOCAB_PRE_TYPE_GPT2 = 7,
// LLAMA_VOCAB_PRE_TYPE_REFACT = 8,
// LLAMA_VOCAB_PRE_TYPE_COMMAND_R = 9,
// LLAMA_VOCAB_PRE_TYPE_STABLELM2 = 10,
// LLAMA_VOCAB_PRE_TYPE_QWEN2 = 11,
// LLAMA_VOCAB_PRE_TYPE_OLMO = 12,
// LLAMA_VOCAB_PRE_TYPE_DBRX = 13,
// LLAMA_VOCAB_PRE_TYPE_SMAUG = 14,
// LLAMA_VOCAB_PRE_TYPE_PORO = 15,
// LLAMA_VOCAB_PRE_TYPE_CHATGLM3 = 16,
// LLAMA_VOCAB_PRE_TYPE_CHATGLM4 = 17,
// LLAMA_VOCAB_PRE_TYPE_VIKING = 18,
// LLAMA_VOCAB_PRE_TYPE_JAIS = 19,
// LLAMA_VOCAB_PRE_TYPE_TEKKEN = 20,
// LLAMA_VOCAB_PRE_TYPE_SMOLLM = 21,
// LLAMA_VOCAB_PRE_TYPE_CODESHELL = 22,
// LLAMA_VOCAB_PRE_TYPE_DEEPSEEK3_LLM = 28, //llama.cpp lists this as 28
// LLAMA_VOCAB_PRE_TYPE_GPT4O = 29,
// LLAMA_VOCAB_PRE_TYPE_SUPERBPE = 30,
// LLAMA_VOCAB_PRE_TYPE_TRILLION = 31,
// LLAMA_VOCAB_PRE_TYPE_BAILINGMOE = 32,
// LLAMA_VOCAB_PRE_TYPE_LLAMA4 = 33,
// LLAMA_VOCAB_PRE_TYPE_FALCON_3 = 34,
// LLAMA_VOCAB_PRE_TYPE_FALCON_E = 35,
// LLAMA_VOCAB_PRE_TYPE_SEED_CODER = 36, //llama.cpp lists this as 35
// LLAMA_VOCAB_PRE_TYPE_HUNYUAN = 37, //llama.cpp lists this as 36
// LLAMA_VOCAB_PRE_TYPE_KIMI_K2 = 38, //llama.cpp lists this as 37
//};
// note: these values should be synchronized with ggml_rope
// TODO: maybe move this enum to ggml.h (ggml_rope_type)

1
src/llama-arch.h
View File

@@ -157,6 +157,7 @@ enum llm_kv {
LLM_KV_TOKENIZER_MASK_ID,
LLM_KV_TOKENIZER_ADD_BOS,
LLM_KV_TOKENIZER_ADD_EOS,
LLM_KV_TOKENIZER_ADD_SEP,
LLM_KV_TOKENIZER_ADD_PREFIX,
LLM_KV_TOKENIZER_REMOVE_EXTRA_WS,
LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP,

8
src/llama-grammar.cpp
View File

@@ -486,9 +486,9 @@ void llama_grammar_sample_impl(const struct llama_grammar * grammar, const struc
for (size_t i = 0; i < candidates->size; ++i) {
const llama_token id = candidates->data[i].id;
const std::string & piece = vocab->cache_token_to_piece.at(id);
const std::string & piece = vocab->token_to_piece(id);
if (llama_token_is_eog_impl(*vocab, id)) {
if (vocab->is_eog(id)) {
if (!allow_eog) {
candidates->data[i].logit = -INFINITY;
}
@@ -511,7 +511,7 @@ void llama_grammar_sample_impl(const struct llama_grammar * grammar, const struc
void llama_grammar_accept_token_impl(struct llama_grammar * grammar, const struct llama_vocab * vocab, const struct llama_sampling * smpl, llama_token token) {
const int64_t t_start_sample_us = ggml_time_us();
if (llama_token_is_eog_impl(*vocab, token)) {
if (vocab->is_eog(token)) {
for (const auto & stack : grammar->stacks) {
if (stack.empty()) {
return;
@@ -520,7 +520,7 @@ void llama_grammar_accept_token_impl(struct llama_grammar * grammar, const struc
GGML_ABORT("fatal error");
}
const std::string & piece = vocab->cache_token_to_piece.at(token);
const std::string & piece = vocab->token_to_piece(token);
// Note terminating 0 in decoded string
const auto decoded = decode_utf8(piece, grammar->partial_utf8);

5
src/llama-sampling.cpp
View File

@@ -734,7 +734,7 @@ llama_token llama_sample_token_impl(struct llama_sampling * smpl, llama_token_da
// Ported from Koboldcpp, original PR: https://github.com/LostRuins/koboldcpp/pull/982 (Original author: pi6am)
static void get_overlapping_token_sequences(const llama_vocab& vocab, const std::string& str, std::unordered_multimap<llama_token, std::vector<llama_token>>& token_sequences, int max_tail_len = -1) {
for (llama_token token_id = 0; token_id < (llama_token)vocab.n_tokens(); token_id++) {
std::string word = llama_detokenize(vocab, { token_id }, true);
auto word = vocab.detokenize( { token_id }, true);
if (word.find(str) != std::string::npos) {
token_sequences.emplace(token_id, std::vector<llama_token>());
}
@@ -751,7 +751,8 @@ static void get_overlapping_token_sequences(const llama_vocab& vocab, const std:
}
}
if (match) {
std::vector<llama_token> tokenization = llama_tokenize_internal(vocab, str.substr(i), false, false);
auto tokenization = vocab.tokenize(str.substr(i), false, false);
//std::vector<llama_token> tokenization = llama_tokenize_internal(vocab, str.substr(i), false, false);
if (max_tail_len >= 0 && tokenization.size() > (size_t)max_tail_len) {
tokenization.resize(max_tail_len);
}

3122
src/llama-vocab.cpp
View File

File diff suppressed because it is too large Load Diff

279
src/llama-vocab.h
View File

@@ -1,155 +1,178 @@
#pragma once
#include "llama-impl.h"
#include "llama.h"
#include <string>
#include <vector>
#include <unordered_map>
#include <map>
#include <memory>
// pre-tokenization types
enum llama_vocab_pre_type {
LLAMA_VOCAB_PRE_TYPE_DEFAULT = 0,
LLAMA_VOCAB_PRE_TYPE_LLAMA3 = 1,
LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM = 2,
LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_CODER = 3,
LLAMA_VOCAB_PRE_TYPE_FALCON = 4,
LLAMA_VOCAB_PRE_TYPE_MPT = 5,
LLAMA_VOCAB_PRE_TYPE_STARCODER = 6,
LLAMA_VOCAB_PRE_TYPE_GPT2 = 7,
LLAMA_VOCAB_PRE_TYPE_REFACT = 8,
LLAMA_VOCAB_PRE_TYPE_COMMAND_R = 9,
LLAMA_VOCAB_PRE_TYPE_STABLELM2 = 10,
LLAMA_VOCAB_PRE_TYPE_QWEN2 = 11,
LLAMA_VOCAB_PRE_TYPE_OLMO = 12,
LLAMA_VOCAB_PRE_TYPE_DBRX = 13,
LLAMA_VOCAB_PRE_TYPE_SMAUG = 14,
LLAMA_VOCAB_PRE_TYPE_PORO = 15,
LLAMA_VOCAB_PRE_TYPE_CHATGLM3 = 16,
LLAMA_VOCAB_PRE_TYPE_CHATGLM4 = 17,
LLAMA_VOCAB_PRE_TYPE_VIKING = 18,
LLAMA_VOCAB_PRE_TYPE_JAIS = 19,
LLAMA_VOCAB_PRE_TYPE_TEKKEN = 20,
LLAMA_VOCAB_PRE_TYPE_SMOLLM = 21,
LLAMA_VOCAB_PRE_TYPE_CODESHELL = 22,
LLAMA_VOCAB_PRE_TYPE_BLOOM = 23,
LLAMA_VOCAB_PRE_TYPE_GPT3_FINNISH = 24,
LLAMA_VOCAB_PRE_TYPE_EXAONE = 25,
LLAMA_VOCAB_PRE_TYPE_CHAMELEON = 26,
LLAMA_VOCAB_PRE_TYPE_MINERVA = 27,
LLAMA_VOCAB_PRE_TYPE_DEEPSEEK3_LLM = 28,
LLAMA_VOCAB_PRE_TYPE_GPT4O = 29,
LLAMA_VOCAB_PRE_TYPE_SUPERBPE = 30,
LLAMA_VOCAB_PRE_TYPE_TRILLION = 31,
LLAMA_VOCAB_PRE_TYPE_BAILINGMOE = 32,
LLAMA_VOCAB_PRE_TYPE_LLAMA4 = 33,
LLAMA_VOCAB_PRE_TYPE_PIXTRAL = 34,
LLAMA_VOCAB_PRE_TYPE_SEED_CODER = 35,
LLAMA_VOCAB_PRE_TYPE_HUNYUAN = 36,
LLAMA_VOCAB_PRE_TYPE_KIMI_K2 = 37,
LLAMA_VOCAB_PRE_TYPE_HUNYUAN_DENSE = 38,
};
struct LLM_KV;
struct llama_model_loader;
struct llama_vocab {
using id = llama_token;
using token = std::string;
using tattr = llama_token_attr;
struct token_data {
token text;
float score;
tattr attr;
std::string text;
float score;
llama_token_attr attr;
};
enum llama_vocab_type type = LLAMA_VOCAB_TYPE_SPM;
enum llama_vocab_pre_type type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
llama_vocab();
~llama_vocab();
int max_token_len = 0; // used for optimizing longest token search
void load(llama_model_loader & ml, const LLM_KV & kv);
std::string get_tokenizer_model() const;
std::string get_tokenizer_pre() const;
enum llama_vocab_type get_type() const;
enum llama_vocab_pre_type get_pre_type() const;
uint32_t n_tokens() const;
uint32_t n_token_types() const;
std::unordered_map<token, id> token_to_id;
std::vector<token_data> id_to_token;
std::string type_name() const;
std::vector<id> cache_special_tokens;
std::vector<token> cache_token_to_piece; // llama_token_to_piece(special = true);
bool is_normal (llama_token id) const;
bool is_unknown (llama_token id) const;
bool is_control (llama_token id) const;
bool is_byte (llama_token id) const;
bool is_user_defined(llama_token id) const;
bool is_unused (llama_token id) const;
bool is_eog (llama_token id) const;
std::map<std::pair<std::string, std::string>, int> bpe_ranks;
uint8_t token_to_byte(llama_token id) const;
llama_token byte_to_token(uint8_t ch) const;
// default LLaMA special tokens
id special_bos_id = 1;
id special_eos_id = 2;
id special_unk_id = 0;
id special_sep_id = -1;
id special_pad_id = -1;
id special_cls_id = -1;
id special_mask_id = -1;
llama_token text_to_token(const std::string & text) const;
id linefeed_id = 13;
const token_data & get_token_data(llama_token id) const;
// fim tokens
llama_token special_fim_pre_id = -1;
llama_token special_fim_suf_id = -1;
llama_token special_fim_mid_id = -1;
llama_token special_fim_pad_id = -1;
llama_token special_fim_rep_id = -1; // repo
llama_token special_fim_sep_id = -1; // file separator
const char * token_get_text (llama_token id) const;
float token_get_score(llama_token id) const;
llama_token_attr token_get_attr (llama_token id) const;
id special_prefix_id = -1;
id special_suffix_id = -1;
id special_middle_id = -1;
id special_eot_id = -1; // TODO: move above after "eos_id", and here add "file separator" token
id special_eom_id = -1;
llama_token token_bos() const;
llama_token token_eos() const;
llama_token token_eot() const;
llama_token token_eom() const;
llama_token token_unk() const;
llama_token token_sep() const;
llama_token token_nl () const;
llama_token token_pad() const;
llama_token token_mask() const;
// tokenizer flags
bool tokenizer_add_space_prefix = false;
bool tokenizer_add_bos = false;
bool tokenizer_add_eos = false;
bool tokenizer_ignore_merges = false;
bool tokenizer_clean_spaces = false; // clean_up_tokenization_spaces
bool tokenizer_remove_extra_whitespaces = false;
bool tokenizer_escape_whitespaces = true;
bool tokenizer_treat_whitespace_as_suffix = false;
llama_token token_prefix() const;
llama_token token_middle() const;
llama_token token_suffix() const;
std::vector<char> precompiled_charsmap;
llama_token token_fim_pre() const;
llama_token token_fim_suf() const;
llama_token token_fim_mid() const;
llama_token token_fim_pad() const;
llama_token token_fim_rep() const;
llama_token token_fim_sep() const;
bool get_add_space_prefix () const;
bool get_add_bos () const;
bool get_add_eos () const;
bool get_add_sep () const;
bool get_ignore_merges () const;
bool get_clean_spaces () const;
bool get_remove_extra_whitespaces () const;
bool get_escape_whitespaces () const;
bool get_treat_whitespace_as_suffix() const;
int max_token_len() const;
int find_bpe_rank(const std::string & token_left, const std::string & token_right) const;
std::vector<std::string> get_bpe_merges() const;
std::vector<char> get_precompiled_charsmap() const;
int32_t tokenize(
const char * text,
int32_t text_len,
llama_token * tokens,
int32_t n_tokens_max,
bool add_special,
bool parse_special) const;
std::vector<llama_token> tokenize(
const std::string & raw_text,
bool add_special,
bool parse_special = false) const;
// does not write null-terminator to buf
int32_t token_to_piece(
llama_token token,
char * buf,
int32_t length,
int32_t lstrip,
bool special) const;
// use cached data
const std::string & token_to_piece(llama_token token) const;
int32_t detokenize(
const llama_token * tokens,
int32_t n_tokens,
char * text,
int32_t text_len_max,
bool remove_special,
bool unparse_special) const;
std::string detokenize(
const std::vector<llama_token> & tokens,
bool special) const;
void print_info() const;
private:
struct impl;
std::unique_ptr<impl> pimpl;
};
const struct llama_vocab * llama_get_vocab(const struct llama_context * ctx);
//
// internal API
//
// TODO: rename to llama_tokenize_impl
// TODO: This should probably be in llama.h
std::vector<llama_vocab::id> llama_tokenize_internal(
const llama_vocab & vocab,
std::string raw_text,
bool add_special,
bool parse_special = false);
llama_token llama_byte_to_token_impl(const llama_vocab & vocab, uint8_t ch);
const char * llama_token_get_text_impl(const struct llama_vocab & vocab, llama_token token);
float llama_token_get_score_impl(const struct llama_vocab & vocab, llama_token token);
llama_token_attr llama_token_get_attr_impl(const struct llama_vocab & vocab, llama_token token);
bool llama_token_is_eog_impl(const struct llama_vocab & vocab, llama_token token);
bool llama_token_is_control_impl(const struct llama_vocab & vocab, llama_token token);
llama_token llama_token_bos_impl(const struct llama_vocab & vocab);
llama_token llama_token_eos_impl(const struct llama_vocab & vocab);
llama_token llama_token_cls_impl(const struct llama_vocab & vocab);
llama_token llama_token_sep_impl(const struct llama_vocab & vocab);
llama_token llama_token_nl_impl (const struct llama_vocab & vocab);
llama_token llama_token_pad_impl(const struct llama_vocab & vocab);
int32_t llama_add_bos_token_impl(const struct llama_vocab & vocab);
int32_t llama_add_eos_token_impl(const struct llama_vocab & vocab);
llama_token llama_token_fim_pre_impl(const struct llama_vocab & vocab);
llama_token llama_token_fim_suf_impl(const struct llama_vocab & vocab);
llama_token llama_token_fim_mid_impl(const struct llama_vocab & vocab);
llama_token llama_token_fim_pad_impl(const struct llama_vocab & vocab);
llama_token llama_token_fim_rep_impl(const struct llama_vocab & vocab);
llama_token llama_token_fim_sep_impl(const struct llama_vocab & vocab);
llama_token llama_token_prefix_impl(const struct llama_vocab & vocab);
llama_token llama_token_middle_impl(const struct llama_vocab & vocab);
llama_token llama_token_suffix_impl(const struct llama_vocab & vocab);
llama_token llama_token_eot_impl (const struct llama_vocab & vocab);
llama_token llama_token_eom_impl (const struct llama_vocab & vocab);
int32_t llama_tokenize_impl(
const struct llama_vocab & vocab,
const char * text,
int32_t text_len,
llama_token * tokens,
int32_t n_tokens_max,
bool add_special,
bool parse_special);
// does not write null-terminator to buf
int32_t llama_token_to_piece_impl(
const struct llama_vocab & vocab,
llama_token token,
char * buf,
int32_t length,
int32_t lstrip,
bool special);
int32_t llama_detokenize_impl(
const struct llama_vocab & vocab,
const llama_token * tokens,
int32_t n_tokens,
char * text,
int32_t text_len_max,
bool remove_special,
bool unparse_special);
std::string llama_detokenize(
const struct llama_vocab& vocab,
const std::vector<llama_token>& tokens,
bool special);

800
src/llama.cpp
View File

@@ -4307,702 +4307,6 @@ static void llm_load_hparams(
hparams.rope_type = llama_rope_type(&model);
}
static void llm_load_vocab(
llama_model_loader & ml,
llama_model & model) {
auto & vocab = model.vocab;
struct gguf_context * ctx = ml.meta;
const auto kv = LLM_KV(model.arch);
// determine vocab type
{
std::string tokenizer_model;
std::string tokenizer_pre;
ml.get_key(LLM_KV_TOKENIZER_MODEL, tokenizer_model);
ml.get_key(LLM_KV_TOKENIZER_PRE, tokenizer_pre, false);
if (tokenizer_model == "no_vocab") {
vocab.type = LLAMA_VOCAB_TYPE_NONE;
// default special tokens
vocab.special_bos_id = -1;
vocab.special_eos_id = -1;
vocab.special_unk_id = -1;
vocab.special_sep_id = -1;
vocab.special_pad_id = -1;
vocab.special_cls_id = -1;
vocab.special_mask_id = -1;
vocab.linefeed_id = -1;
return;
} else if (tokenizer_model == "llama") {
vocab.type = LLAMA_VOCAB_TYPE_SPM;
// default special tokens
vocab.special_bos_id = 1;
vocab.special_eos_id = 2;
vocab.special_unk_id = 0;
vocab.special_sep_id = -1;
vocab.special_pad_id = -1;
vocab.special_cls_id = -1;
vocab.special_mask_id = -1;
} else if (tokenizer_model == "bert") {
vocab.type = LLAMA_VOCAB_TYPE_WPM;
// default special tokens
vocab.special_bos_id = -1;
vocab.special_eos_id = -1;
vocab.special_unk_id = 100;
vocab.special_sep_id = 102;
vocab.special_pad_id = 0;
vocab.special_cls_id = 101;
vocab.special_mask_id = 103;
} else if (tokenizer_model == "gpt2") {
vocab.type = LLAMA_VOCAB_TYPE_BPE;
// read bpe merges and populate bpe ranks
const int merges_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_MERGES).c_str());
if (merges_keyidx == -1) {
throw std::runtime_error("cannot find tokenizer merges in model file\n");
}
const int n_merges = gguf_get_arr_n(ctx, merges_keyidx);
for (int i = 0; i < n_merges; i++) {
const std::string word = gguf_get_arr_str(ctx, merges_keyidx, i);
GGML_ASSERT(unicode_cpts_from_utf8(word).size() > 0);
std::string first;
std::string second;
const size_t pos = word.find(' ', 1);
if (pos != std::string::npos) {
first = word.substr(0, pos);
second = word.substr(pos + 1);
}
vocab.bpe_ranks.emplace(std::make_pair(first, second), i);
}
// default special tokens
if(model.arch == LLM_ARCH_DOTS1) {
vocab.special_bos_id = -1;
}
else {
vocab.special_bos_id = 11;
}
vocab.special_eos_id = 11;
vocab.special_unk_id = -1;
vocab.special_sep_id = -1;
vocab.special_pad_id = -1;
vocab.special_cls_id = -1;
vocab.special_mask_id = -1;
} else if (tokenizer_model == "t5") {
vocab.type = LLAMA_VOCAB_TYPE_UGM;
// default special tokens
vocab.special_bos_id = -1;
vocab.special_eos_id = 1;
vocab.special_unk_id = 2;
vocab.special_sep_id = -1;
vocab.special_pad_id = 0;
vocab.special_cls_id = -1;
vocab.special_mask_id = -1;
const int precompiled_charsmap_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP).c_str());
if (precompiled_charsmap_keyidx != -1) {
size_t n_precompiled_charsmap = gguf_get_arr_n(ctx, precompiled_charsmap_keyidx);
const char * precompiled_charsmap = (const char *) gguf_get_arr_data(ctx, precompiled_charsmap_keyidx);
vocab.precompiled_charsmap.assign(precompiled_charsmap, precompiled_charsmap + n_precompiled_charsmap);
#ifdef IS_BIG_ENDIAN
// correct endiannes of data in precompiled_charsmap binary blob
uint32_t * xcda_blob_size = (uint32_t *) &vocab.precompiled_charsmap[0];
*xcda_blob_size = __builtin_bswap32(*xcda_blob_size);
assert(*xcda_blob_size + sizeof(uint32_t) < n_precompiled_charsmap);
size_t xcda_array_size = *xcda_blob_size / sizeof(uint32_t);
uint32_t * xcda_array = (uint32_t *) &vocab.precompiled_charsmap[sizeof(uint32_t)];
for (size_t i = 0; i < xcda_array_size; ++i) {
xcda_array[i] = __builtin_bswap32(xcda_array[i]);
}
#endif
}
} else {
throw std::runtime_error(format("unknown tokenizer: '%s'", tokenizer_model.c_str()));
}
// for now, only BPE models have pre-tokenizers
if (vocab.type == LLAMA_VOCAB_TYPE_BPE) {
vocab.tokenizer_add_space_prefix = false;
vocab.tokenizer_clean_spaces = true;
if (tokenizer_pre.empty()) {
//!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
// OK - I don't feel like recreati8ng the LLaMA-v3 models. Considering that, at least for now,
// LLaMA-v3 is the only model wehere we end up here, let's just force the pre-tokanizer to be
// llama3.
tokenizer_pre = "llama3";
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_LLAMA3;
LLAMA_LOG_WARN("%s: missing pre-tokenizer type, using: 'llama3'\n", __func__);
LLAMA_LOG_WARN("%s: \n", __func__);
LLAMA_LOG_WARN("%s: ************************************ \n", __func__);
LLAMA_LOG_WARN("%s: GENERATION QUALITY MAY BE DEGRADED! \n", __func__);
LLAMA_LOG_WARN("%s: CONSIDER REGENERATING THE MODEL \n", __func__);
LLAMA_LOG_WARN("%s: ************************************ \n", __func__);
LLAMA_LOG_WARN("%s: \n", __func__);
//vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
//!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
} else if (tokenizer_pre == "default") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
} else if (
tokenizer_pre == "llama3" ||
tokenizer_pre == "llama-v3" ||
tokenizer_pre == "llama-bpe") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_LLAMA3;
vocab.tokenizer_ignore_merges = true;
vocab.tokenizer_add_bos = true;
} else if (
tokenizer_pre == "deepseek-llm") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "deepseek-coder") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_CODER;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "deepseek-v3") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEEPSEEK3_LLM;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "falcon") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_FALCON;
} else if (tokenizer_pre == "falcon3") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_FALCON_3;
} else if (tokenizer_pre == "falcon_e") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_FALCON_E;
} else if (
tokenizer_pre == "mpt") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_MPT;
} else if (
tokenizer_pre == "starcoder") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_STARCODER;
} else if (
tokenizer_pre == "gpt-2" ||
tokenizer_pre == "phi-2" ||
tokenizer_pre == "jina-es" ||
tokenizer_pre == "jina-de" ||
tokenizer_pre == "jina-v2-es" ||
tokenizer_pre == "jina-v2-de" ||
tokenizer_pre == "jina-v2-code") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_GPT2;
} else if (
tokenizer_pre == "refact") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_REFACT;
} else if (
tokenizer_pre == "command-r") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_COMMAND_R;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "qwen2" || tokenizer_pre == "deepseek-r1-qwen") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_QWEN2;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "stablelm2") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_STABLELM2;
} else if (
tokenizer_pre == "olmo") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_OLMO;
} else if (
tokenizer_pre == "dbrx") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DBRX;
} else if (
tokenizer_pre == "smaug-bpe") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_SMAUG;
} else if (
tokenizer_pre == "poro-chat") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_PORO;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "glm4" ||
tokenizer_pre == "chatglm-bpe") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_CHATGLM4;
vocab.special_bos_id = -1;
} else if (
tokenizer_pre == "viking") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_VIKING;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "jais") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_JAIS;
} else if (
tokenizer_pre == "tekken") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_TEKKEN;
vocab.tokenizer_clean_spaces = false;
vocab.tokenizer_ignore_merges = true;
vocab.tokenizer_add_bos = true;
} else if (
tokenizer_pre == "smollm") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_SMOLLM;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "codeshell") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_CODESHELL;
} else if (
tokenizer_pre == "gpt-4o" ||
tokenizer_pre == "llama4") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_GPT4O;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "superbpe") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_SUPERBPE;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "trillion") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_TRILLION;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "bailingmoe") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_BAILINGMOE;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "seed-coder") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_SEED_CODER;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "hunyuan") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_HUNYUAN;
vocab.tokenizer_clean_spaces = false;
} else if (
tokenizer_pre == "kimi-k2") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_KIMI_K2;
vocab.tokenizer_clean_spaces = false;
} else {
throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
}
} else if (vocab.type == LLAMA_VOCAB_TYPE_SPM) {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
vocab.tokenizer_add_space_prefix = true;
vocab.tokenizer_clean_spaces = false;
vocab.tokenizer_add_bos = true;
vocab.tokenizer_add_eos = false;
} else if (vocab.type == LLAMA_VOCAB_TYPE_WPM) {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
vocab.tokenizer_add_space_prefix = false;
vocab.tokenizer_clean_spaces = true;
vocab.tokenizer_add_bos = true;
vocab.tokenizer_add_eos = false;
} else if (vocab.type == LLAMA_VOCAB_TYPE_UGM) {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
vocab.tokenizer_add_bos = false;
vocab.tokenizer_add_eos = true;
} else {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
}
ml.get_key(LLM_KV_TOKENIZER_ADD_PREFIX, vocab.tokenizer_add_space_prefix, false);
ml.get_key(LLM_KV_TOKENIZER_REMOVE_EXTRA_WS, vocab.tokenizer_remove_extra_whitespaces, false);
}
const int token_idx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_LIST).c_str());
if (token_idx == -1) {
throw std::runtime_error("cannot find tokenizer vocab in model file\n");
}
const float * scores = nullptr;
const int score_idx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_SCORES).c_str());
if (score_idx != -1) {
scores = (const float * ) gguf_get_arr_data(ctx, score_idx);
}
const int * toktypes = nullptr;
const int toktype_idx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_TOKEN_TYPE).c_str());
if (toktype_idx != -1) {
toktypes = (const int * ) gguf_get_arr_data(ctx, toktype_idx);
}
const uint32_t n_vocab = gguf_get_arr_n(ctx, token_idx);
vocab.id_to_token.resize(n_vocab);
for (uint32_t i = 0; i < n_vocab; i++) {
std::string word = gguf_get_arr_str(ctx, token_idx, i);
GGML_ASSERT(unicode_cpts_from_utf8(word).size() > 0);
vocab.token_to_id[word] = i;
vocab.max_token_len = std::max(vocab.max_token_len, (int) word.size());
auto & token_data = vocab.id_to_token[i];
token_data.text = std::move(word);
token_data.score = scores ? scores[i] : 0.0f;
token_data.attr = LLAMA_TOKEN_ATTR_NORMAL;
if (toktypes) { //TODO: remove, required until per token attributes are available from GGUF file
switch(toktypes[i]) {
case LLAMA_TOKEN_TYPE_UNKNOWN: token_data.attr = LLAMA_TOKEN_ATTR_UNKNOWN; break;
case LLAMA_TOKEN_TYPE_UNUSED: token_data.attr = LLAMA_TOKEN_ATTR_UNUSED; break;
case LLAMA_TOKEN_TYPE_NORMAL: token_data.attr = LLAMA_TOKEN_ATTR_NORMAL; break;
case LLAMA_TOKEN_TYPE_CONTROL: token_data.attr = LLAMA_TOKEN_ATTR_CONTROL; break;
case LLAMA_TOKEN_TYPE_USER_DEFINED: token_data.attr = LLAMA_TOKEN_ATTR_USER_DEFINED; break;
case LLAMA_TOKEN_TYPE_BYTE: token_data.attr = LLAMA_TOKEN_ATTR_BYTE; break;
case LLAMA_TOKEN_TYPE_UNDEFINED: token_data.attr = LLAMA_TOKEN_ATTR_UNDEFINED; break;
default: token_data.attr = LLAMA_TOKEN_ATTR_UNDEFINED; break;
}
}
}
GGML_ASSERT(vocab.id_to_token.size() == vocab.token_to_id.size());
// determine the newline token: LLaMA "<0x0A>" == 10 == '\n', Falcon 193 == '\n'
if (vocab.type == LLAMA_VOCAB_TYPE_SPM) {
// For Fill-In-the-Middle (FIM)/infill models which where converted
// prior to support of FIM special tokens in GGUF, the following
// will allow those models to continue to work. The general names
// of the known models are currently CodeLlama (LLM_ARCH_LLAMA) and
// CodeGemma (LLM_ARCH_GEMMA). This can potentially be removed once
// new versions of these models have been published.
std::string gen_name;
ml.get_key(LLM_KV_GENERAL_NAME, gen_name, false);
std::transform(gen_name.begin(), gen_name.end(), gen_name.begin(),
[](unsigned char c){ return std::tolower(c); });
if (gen_name.find("code") != std::string::npos) {
if (model.arch == LLM_ARCH_LLAMA
&& 32010 < vocab.id_to_token.size()
&& vocab.id_to_token[32007].text.find("<PRE>") != std::string::npos
&& vocab.id_to_token[32008].text.find("<SUF>") != std::string::npos
&& vocab.id_to_token[32009].text.find("<MID>") != std::string::npos
&& vocab.id_to_token[32010].text.find("<EOT>") != std::string::npos) {
vocab.special_prefix_id = 32007;
vocab.special_suffix_id = 32008;
vocab.special_middle_id = 32009;
vocab.special_eot_id = 32010;
} else if (model.arch == LLM_ARCH_GEMMA
&& 107 < vocab.id_to_token.size()
&& vocab.id_to_token[67].text == "<|fim_prefix|>"
&& vocab.id_to_token[69].text == "<|fim_suffix|>"
&& vocab.id_to_token[68].text == "<|fim_middle|>"
&& vocab.id_to_token[107].text == "<end_of_turn>") {
vocab.special_prefix_id = 67;
vocab.special_suffix_id = 69;
vocab.special_middle_id = 68;
// TODO: this is not EOT, it is "file separator" token, needs fix
// https://huggingface.co/google/codegemma-7b-it/blob/9b1d9231388358c04d90bd003458f5070d97db44/tokenizer_config.json#L565-L572
//vocab.special_eot_id = 70;
vocab.special_eot_id = 107;
}
}
try {
vocab.linefeed_id = llama_byte_to_token_impl(vocab, '\n');
} catch (const std::exception & e) {
LLAMA_LOG_WARN("%s: SPM vocabulary, but newline token not found: %s! Using special_pad_id instead.", __func__, e.what());
vocab.linefeed_id = vocab.special_pad_id;
}
} else if (vocab.type == LLAMA_VOCAB_TYPE_WPM) {
vocab.linefeed_id = vocab.special_pad_id;
} else {
const std::vector<int> ids = llama_tokenize_internal(vocab, "\xC4\x8A", false); // U+010A
GGML_ASSERT(!ids.empty() && "model vocab missing newline token");
vocab.linefeed_id = ids[0];
}
// special tokens
{
const std::vector<std::pair<enum llm_kv, int32_t &>> special_token_types = {
{ LLM_KV_TOKENIZER_BOS_ID, vocab.special_bos_id },
{ LLM_KV_TOKENIZER_EOS_ID, vocab.special_eos_id },
{ LLM_KV_TOKENIZER_EOT_ID, vocab.special_eot_id },
{ LLM_KV_TOKENIZER_EOM_ID, vocab.special_eom_id },
{ LLM_KV_TOKENIZER_UNK_ID, vocab.special_unk_id },
{ LLM_KV_TOKENIZER_SEP_ID, vocab.special_sep_id },
{ LLM_KV_TOKENIZER_PAD_ID, vocab.special_pad_id },
{ LLM_KV_TOKENIZER_CLS_ID, vocab.special_cls_id },
{ LLM_KV_TOKENIZER_MASK_ID, vocab.special_mask_id },
{ LLM_KV_TOKENIZER_FIM_PRE_ID, vocab.special_fim_pre_id },
{ LLM_KV_TOKENIZER_FIM_SUF_ID, vocab.special_fim_suf_id },
{ LLM_KV_TOKENIZER_FIM_MID_ID, vocab.special_fim_mid_id },
{ LLM_KV_TOKENIZER_FIM_PAD_ID, vocab.special_fim_pad_id },
{ LLM_KV_TOKENIZER_FIM_REP_ID, vocab.special_fim_rep_id },
{ LLM_KV_TOKENIZER_FIM_SEP_ID, vocab.special_fim_sep_id },
{ LLM_KV_TOKENIZER_PREFIX_ID, vocab.special_prefix_id },
{ LLM_KV_TOKENIZER_SUFFIX_ID, vocab.special_suffix_id },
{ LLM_KV_TOKENIZER_MIDDLE_ID, vocab.special_middle_id },
};
for (const auto & it : special_token_types) {
const std::string & key = kv(std::get<0>(it));
int32_t & id = std::get<1>(it);
uint32_t new_id;
if (!ml.get_key(std::get<0>(it), new_id, false)) {
continue;
}
if (new_id >= vocab.id_to_token.size()) {
LLAMA_LOG_WARN("%s: bad special token: '%s' = %ud, using default id %d\n",
__func__, key.c_str(), new_id, id);
} else {
id = new_id;
}
}
// Handle add_bos_token and add_eos_token
{
bool temp = true;
if (ml.get_key(LLM_KV_TOKENIZER_ADD_BOS, temp, false)) {
vocab.tokenizer_add_bos = temp;
}
if (ml.get_key(LLM_KV_TOKENIZER_ADD_EOS, temp, false)) {
vocab.tokenizer_add_eos = temp;
}
}
// find EOT token: "<|eot_id|>", "<|im_end|>", "<end_of_turn>", etc.
//
// TODO: convert scripts should provide this token through the KV metadata LLAMA_KV_TOKENIZER_EOT_ID
// for now, we apply this workaround to find the EOT token based on its text
if (vocab.special_eot_id == -1) {
for (const auto & t : vocab.token_to_id) {
if (
// TODO: gemma "<end_of_turn>" is exported as a normal token, so the following check does not work
// need to fix convert script
//vocab.id_to_token[t.second].type == LLAMA_TOKEN_TYPE_CONTROL &&
(t.first == "<|eot_id|>" ||
t.first == "<|im_end|>" ||
t.first == "<|end|>" ||
t.first == "<end_of_turn>" ||
t.first == "<|endoftext|>"
)
) {
vocab.special_eot_id = t.second;
break;
}
}
}
// @ngxson : quick hack for gpt-oss, always render these tokens
for (const auto & t : vocab.token_to_id) {
if (t.first == "<|channel|>" || t.first == "<|message|>" || t.first == "<|start|>") {
vocab.id_to_token[t.second].attr = LLAMA_TOKEN_ATTR_USER_DEFINED;
}
}
// find EOM token: "<|eom_id|>"
//
// TODO: convert scripts should provide this token through the KV metadata LLAMA_KV_TOKENIZER_EOM_ID
// for now, we apply this workaround to find the EOM token based on its text
if (vocab.special_eom_id == -1) {
const auto & t = vocab.token_to_id.find("<|eom_id|>");
if (t != vocab.token_to_id.end()) {
vocab.special_eom_id = t->second;
}
}
for (const auto & t : vocab.token_to_id) {
// find FIM_PRE token: "<|fim_prefix|>", "<fim-prefix>", "<PRE>", etc.
if (vocab.special_fim_pre_id == -1) {
if (false
|| t.first == "<|fim_prefix|>" // Qwen
|| t.first == "<fim-prefix>"
|| t.first == "<fim_prefix>" // Granite
|| t.first == "<｜fim▁begin｜>" // DeepSeek
|| t.first == "<PRE>"
|| t.first == "▁<PRE>" // CodeLlama
|| t.first == "<|code_prefix|>" // GLM-4.5
) {
vocab.special_fim_pre_id = t.second;
if ((vocab.id_to_token[t.second].attr & LLAMA_TOKEN_ATTR_CONTROL) == 0) {
LLAMA_LOG_WARN("%s: control-looking token: %6d '%s' was not control-type; this is probably a bug in the model. its type will be overridden\n",
__func__, t.second, t.first.c_str());
vocab.id_to_token[t.second].attr = LLAMA_TOKEN_ATTR_CONTROL;
}
}
}
// find FIM_SUF token: "<|fim_suffix|>", "<fim-suffix>", "<SUF>", etc.
if (vocab.special_fim_suf_id == -1) {
if (false
|| t.first == "<|fim_suffix|>" // Qwen
|| t.first == "<fim-suffix>"
|| t.first == "<fim_suffix>" // Granite
|| t.first == "<｜fim▁hole｜>" // DeepSeek
|| t.first == "<SUF>"
|| t.first == "▁<SUF>" // CodeLlama
|| t.first == "<|code_suffix|>" // GLM-4.5
) {
vocab.special_fim_suf_id = t.second;
if ((vocab.id_to_token[t.second].attr & LLAMA_TOKEN_ATTR_CONTROL) == 0) {
LLAMA_LOG_WARN("%s: control-looking token: %6d '%s' was not control-type; this is probably a bug in the model. its type will be overridden\n",
__func__, t.second, t.first.c_str());
vocab.id_to_token[t.second].attr = LLAMA_TOKEN_ATTR_CONTROL;
}
}
}
// find FIM_MID token: "<|fim_middle|>", "<fim-middle>", "<MID>", etc.
// TODO OAI_MOE: o200k_harmony
if (vocab.special_fim_mid_id == -1) {
if (false
|| t.first == "<|fim_middle|>" // Qwen
|| t.first == "<fim-middle>"
|| t.first == "<fim_middle>" // Granite
|| t.first == "<｜fim▁end｜>" // DeepSeek
|| t.first == "<MID>"
|| t.first == "▁<MID>" // CodeLlama
|| t.first == "<|code_middle|>" // GLM-4.5
) {
vocab.special_fim_mid_id = t.second;
if ((vocab.id_to_token[t.second].attr & LLAMA_TOKEN_ATTR_CONTROL) == 0) {
LLAMA_LOG_WARN("%s: control-looking token: %6d '%s' was not control-type; this is probably a bug in the model. its type will be overridden\n",
__func__, t.second, t.first.c_str());
vocab.id_to_token[t.second].attr = LLAMA_TOKEN_ATTR_CONTROL;
}
}
}
// find FIM_PAD token: "<|fim_pad|>", "<fim-pad>", "<PAD>", etc.
if (vocab.special_fim_pad_id == -1) {
if (false
|| t.first == "<|fim_pad|>" // Qwen
|| t.first == "<fim-pad>"
|| t.first == "<fim_pad>" // Granite
|| t.first == "<PAD>"
) {
vocab.special_fim_pad_id = t.second;
if ((vocab.id_to_token[t.second].attr & LLAMA_TOKEN_ATTR_CONTROL) == 0) {
LLAMA_LOG_WARN("%s: control-looking token: %6d '%s' was not control-type; this is probably a bug in the model. its type will be overridden\n",
__func__, t.second, t.first.c_str());
vocab.id_to_token[t.second].attr = LLAMA_TOKEN_ATTR_CONTROL;
}
}
}
// find FIM_REP token: "<|fim_repo|>", "<fim-repo>", "<REP>", etc.
if (vocab.special_fim_rep_id == -1) {
if (false
|| t.first == "<|fim_repo|>" // Qwen
|| t.first == "<|repo_name|>"
|| t.first == "<fim-repo>"
|| t.first == "<REPO>"
|| t.first == "<reponame>" // Granite
) {
vocab.special_fim_rep_id = t.second;
if ((vocab.id_to_token[t.second].attr & LLAMA_TOKEN_ATTR_CONTROL) == 0) {
LLAMA_LOG_WARN("%s: control-looking token: %6d '%s' was not control-type; this is probably a bug in the model. its type will be overridden\n",
__func__, t.second, t.first.c_str());
vocab.id_to_token[t.second].attr = LLAMA_TOKEN_ATTR_CONTROL;
}
}
}
// find FIM_SEP token: "<|file_sep|>"
if (vocab.special_fim_sep_id == -1) {
if (false
|| t.first == "<|file_sep|>" // Qwen
) {
vocab.special_fim_sep_id = t.second;
if ((vocab.id_to_token[t.second].attr & LLAMA_TOKEN_ATTR_CONTROL) == 0) {
LLAMA_LOG_WARN("%s: control-looking token: %6d '%s' was not control-type; this is probably a bug in the model. its type will be overridden\n",
__func__, t.second, t.first.c_str());
vocab.id_to_token[t.second].attr = LLAMA_TOKEN_ATTR_CONTROL;
}
}
}
}
}
// build special tokens cache
{
for (llama_vocab::id id = 0; id < (llama_vocab::id)n_vocab; ++id) {
if (vocab.id_to_token[id].attr & (LLAMA_TOKEN_ATTR_CONTROL | LLAMA_TOKEN_ATTR_USER_DEFINED | LLAMA_TOKEN_ATTR_UNKNOWN)) {
vocab.cache_special_tokens.push_back(id);
}
}
std::sort(vocab.cache_special_tokens.begin(), vocab.cache_special_tokens.end(),
[&] (const llama_vocab::id a, const llama_vocab::id b) {
return vocab.id_to_token[a].text.size() > vocab.id_to_token[b].text.size();
}
);
LLAMA_LOG_INFO("%s: special tokens cache size = %u\n", __func__, (uint32_t)vocab.cache_special_tokens.size());
}
// build token to piece cache
{
size_t size_cache = 0;
std::vector<llama_vocab::token> cache_token_to_piece(n_vocab);
for (uint32_t id = 0; id < n_vocab; ++id) {
cache_token_to_piece[id] = llama_token_to_piece(&model, id, true);
size_cache += cache_token_to_piece[id].size();
}
std::swap(vocab.cache_token_to_piece, cache_token_to_piece);
LLAMA_LOG_INFO("%s: token to piece cache size = %.4f MB\n", __func__, size_cache / 1024.0 / 1024.0);
}
// Handle per token attributes
//NOTE: Each model customizes per token attributes.
//NOTE: Per token attributes are missing from the GGUF file.
//TODO: Extract attributes from GGUF file.
{
auto _contains_any = [] (const std::string &str, const std::vector<std::string> &substrs) -> bool {
for (auto substr : substrs) {
if (str.find(substr) < std::string::npos) {
return true;
}
}
return false;
};
auto _set_tokenid_attr = [&] (const llama_vocab::id id, llama_token_attr attr, bool value) {
uint32_t current = vocab.id_to_token.at(id).attr;
current = value ? (current | attr) : (current & ~attr);
vocab.id_to_token[id].attr = (llama_token_attr) current;
};
auto _set_token_attr = [&] (const std::string & token, llama_token_attr attr, bool value) {
_set_tokenid_attr(vocab.token_to_id.at(token), attr, value);
};
std::string model_name;
std::string tokenizer_pre;
ml.get_key(LLM_KV_GENERAL_NAME, model_name, false);
ml.get_key(LLM_KV_TOKENIZER_PRE, tokenizer_pre, false);
// model name to lowercase
std::transform(model_name.begin(), model_name.end(), model_name.begin(),
[] (const std::string::value_type x) {
return std::tolower(x);
}
);
// set attributes by model/tokenizer name
if (_contains_any(tokenizer_pre, {"jina-v2-de", "jina-v2-es", "jina-v2-code"})) {
_set_token_attr("<mask>", LLAMA_TOKEN_ATTR_LSTRIP, true);
} else if (_contains_any(model_name, {"phi-3", "phi3"})) {
for (auto id : vocab.cache_special_tokens) {
_set_tokenid_attr(id, LLAMA_TOKEN_ATTR_RSTRIP, true);
}
for (auto token : {"</s>"}) {
_set_token_attr(token, LLAMA_TOKEN_ATTR_RSTRIP, true);
}
for (auto token : {"<unk>", "<s>", "<|endoftext|>"}) {
_set_token_attr(token, LLAMA_TOKEN_ATTR_RSTRIP, false);
}
}
}
}
static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
const auto & hparams = model.hparams;
const auto & vocab = model.vocab;
@@ -5041,10 +4345,6 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
// hparams
LLAMA_LOG_INFO("%s: format = %s\n", __func__, llama_file_version_name(ml.fver));
LLAMA_LOG_INFO("%s: arch = %s\n", __func__, LLM_ARCH_NAMES.at(model.arch));
LLAMA_LOG_INFO("%s: vocab type = %s\n", __func__, llama_model_vocab_type_name(vocab.type));
LLAMA_LOG_INFO("%s: n_vocab = %u\n", __func__, hparams.n_vocab);
LLAMA_LOG_INFO("%s: n_merges = %u\n", __func__, (int) vocab.bpe_ranks.size());
LLAMA_LOG_INFO("%s: vocab_only = %d\n", __func__, hparams.vocab_only);
if (!hparams.vocab_only) {
LLAMA_LOG_INFO("%s: n_ctx_train = %u\n", __func__, hparams.n_ctx_train);
@@ -5124,31 +4424,6 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
// general kv
LLAMA_LOG_INFO("%s: general.name = %s\n", __func__, model.name.c_str());
// special tokens
if (vocab.special_bos_id != -1) { LLAMA_LOG_INFO( "%s: BOS token = %d '%s'\n", __func__, vocab.special_bos_id, vocab.id_to_token[vocab.special_bos_id].text.c_str() ); }
if (vocab.special_eos_id != -1) { LLAMA_LOG_INFO( "%s: EOS token = %d '%s'\n", __func__, vocab.special_eos_id, vocab.id_to_token[vocab.special_eos_id].text.c_str() ); }
if (vocab.special_unk_id != -1) { LLAMA_LOG_INFO( "%s: UNK token = %d '%s'\n", __func__, vocab.special_unk_id, vocab.id_to_token[vocab.special_unk_id].text.c_str() ); }
if (vocab.special_sep_id != -1) { LLAMA_LOG_INFO( "%s: SEP token = %d '%s'\n", __func__, vocab.special_sep_id, vocab.id_to_token[vocab.special_sep_id].text.c_str() ); }
if (vocab.special_pad_id != -1) { LLAMA_LOG_INFO( "%s: PAD token = %d '%s'\n", __func__, vocab.special_pad_id, vocab.id_to_token[vocab.special_pad_id].text.c_str() ); }
if (vocab.special_cls_id != -1) { LLAMA_LOG_INFO( "%s: CLS token = %d '%s'\n", __func__, vocab.special_cls_id, vocab.id_to_token[vocab.special_cls_id].text.c_str() ); }
if (vocab.special_mask_id != -1) { LLAMA_LOG_INFO( "%s: MASK token = %d '%s'\n", __func__, vocab.special_mask_id, vocab.id_to_token[vocab.special_mask_id].text.c_str() ); }
if (vocab.linefeed_id != -1) { LLAMA_LOG_INFO( "%s: LF token = %d '%s'\n", __func__, vocab.linefeed_id, vocab.id_to_token[vocab.linefeed_id].text.c_str() ); }
if (vocab.special_fim_pre_id != -1) { LLAMA_LOG_INFO( "%s: FIM PRE token = %d '%s'\n", __func__, vocab.special_fim_pre_id, vocab.id_to_token.at(vocab.special_fim_pre_id).text.c_str() ); }
if (vocab.special_fim_suf_id != -1) { LLAMA_LOG_INFO( "%s: FIM SUF token = %d '%s'\n", __func__, vocab.special_fim_suf_id, vocab.id_to_token.at(vocab.special_fim_suf_id).text.c_str() ); }
if (vocab.special_fim_mid_id != -1) { LLAMA_LOG_INFO( "%s: FIM MID token = %d '%s'\n", __func__, vocab.special_fim_mid_id, vocab.id_to_token.at(vocab.special_fim_mid_id).text.c_str() ); }
if (vocab.special_fim_pad_id != -1) { LLAMA_LOG_INFO( "%s: FIM PAD token = %d '%s'\n", __func__, vocab.special_fim_pad_id, vocab.id_to_token.at(vocab.special_fim_pad_id).text.c_str() ); }
if (vocab.special_fim_rep_id != -1) { LLAMA_LOG_INFO( "%s: FIM REP token = %d '%s'\n", __func__, vocab.special_fim_rep_id, vocab.id_to_token.at(vocab.special_fim_rep_id).text.c_str() ); }
if (vocab.special_fim_sep_id != -1) { LLAMA_LOG_INFO( "%s: FIM SEP token = %d '%s'\n", __func__, vocab.special_fim_sep_id, vocab.id_to_token.at(vocab.special_fim_sep_id).text.c_str() ); }
if (vocab.special_prefix_id != -1) { LLAMA_LOG_INFO( "%s: PRE token = %d '%s'\n", __func__, vocab.special_prefix_id, vocab.id_to_token[vocab.special_prefix_id].text.c_str() ); }
if (vocab.special_suffix_id != -1) { LLAMA_LOG_INFO( "%s: SUF token = %d '%s'\n", __func__, vocab.special_suffix_id, vocab.id_to_token[vocab.special_suffix_id].text.c_str() ); }
if (vocab.special_middle_id != -1) { LLAMA_LOG_INFO( "%s: MID token = %d '%s'\n", __func__, vocab.special_middle_id, vocab.id_to_token[vocab.special_middle_id].text.c_str() ); }
if (vocab.special_eot_id != -1) { LLAMA_LOG_INFO( "%s: EOT token = %d '%s'\n", __func__, vocab.special_eot_id, vocab.id_to_token[vocab.special_eot_id].text.c_str() ); }
LLAMA_LOG_INFO("%s: max token length = %d\n", __func__, vocab.max_token_len);
if (model.arch == LLM_ARCH_DEEPSEEK2) {
LLAMA_LOG_INFO("%s: n_layer_dense_lead = %d\n", __func__, hparams.n_layer_dense_lead);
LLAMA_LOG_INFO("%s: n_lora_q = %d\n", __func__, hparams.n_lora_q);
@@ -5176,6 +4451,8 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
LLAMA_LOG_INFO("%s: f_attention_scale = %f\n", __func__, hparams.f_attention_scale);
}
vocab.print_info();
}
static void llm_prepare_mla(llama_model & model, int mla) {
@@ -8049,15 +7326,15 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam
throw std::runtime_error("error loading model hyperparameters: " + std::string(e.what()));
}
try {
llm_load_vocab(ml, model);
model.vocab.load(ml, LLM_KV(model.arch));
} catch(const std::exception & e) {
throw std::runtime_error("error loading model vocabulary: " + std::string(e.what()));
}
llm_load_print_meta(ml, model);
if (model.vocab.type != LLAMA_VOCAB_TYPE_NONE &&
model.hparams.n_vocab != model.vocab.id_to_token.size()) {
if (model.vocab.get_type() != LLAMA_VOCAB_TYPE_NONE &&
model.hparams.n_vocab != model.vocab.n_tokens()) {
throw std::runtime_error("vocab size mismatch");
}
@@ -16318,9 +15595,9 @@ static struct ggml_cgraph * llama_build_graph(
struct ggml_cgraph * result = NULL;
const llama_vocab * vocab = llama_get_vocab(&lctx);
llama_token bos = llama_token_bos_impl(*vocab);
llama_token eos = llama_token_eos_impl(*vocab);
const llama_vocab * vocab = &lctx.model.vocab; //llama_get_vocab(&lctx);
llama_token bos = vocab->token_bos();
llama_token eos = vocab->token_eos();
bool is_warming_up = lctx.n_eval == 0 && (batch.n_tokens == 1 && (batch.token[0] == ((bos != -1) ? bos : eos)));
struct llm_build_context llm(lctx, batch, cb, worst_case, is_warming_up);
@@ -20254,7 +19531,7 @@ uint32_t llama_n_seq_max(const struct llama_context * ctx) {
}
enum llama_vocab_type llama_vocab_type(const struct llama_model * model) {
return model->vocab.type;
return model->vocab.get_type();
}
const struct llama_vocab* llama_get_model_vocab(const struct llama_model* model) {
@@ -20426,7 +19703,7 @@ const char* llama_model_chat_template(const struct llama_model* model, const cha
// one-off fix for very popular models (so we are not flooded with issues)
// do not extend this list unless absolutely necessary
// Mistral-Small-2503 does not have built-in chat template
llama_vocab_pre_type pre_type = model->vocab.type_pre;
llama_vocab_pre_type pre_type = model->vocab.get_pre_type();
if (!name && pre_type == LLAMA_VOCAB_PRE_TYPE_TEKKEN && model->layers.size() == 40) {
return "mistral-v7-tekken";
}
@@ -21947,101 +21224,102 @@ float * llama_get_embeddings_seq(struct llama_context * ctx, llama_seq_id seq_id
//
const char * llama_token_get_text(const struct llama_model * model, llama_token token) {
return llama_token_get_text_impl(model->vocab, token);
return model->vocab.token_get_text(token);
}
float llama_token_get_score(const struct llama_model * model, llama_token token) {
return llama_token_get_score_impl(model->vocab, token);
return model->vocab.token_get_score(token);
}
enum llama_token_attr llama_token_get_attr(const struct llama_model * model, llama_token token) {
return llama_token_get_attr_impl(model->vocab, token);
return model->vocab.token_get_attr(token);
}
bool llama_token_is_eog(const struct llama_model * model, llama_token token) {
return llama_token_is_eog_impl(model->vocab, token);
return model->vocab.is_eog(token);
}
bool llama_token_is_control(const struct llama_model * model, llama_token token) {
return llama_token_is_control_impl(model->vocab, token);
return model->vocab.is_control(token);
}
llama_token llama_token_bos(const struct llama_model * model) {
return llama_token_bos_impl(model->vocab);
return model->vocab.token_bos();
}
llama_token llama_token_eos(const struct llama_model * model) {
return llama_token_eos_impl(model->vocab);
return model->vocab.token_eos();
}
llama_token llama_token_cls(const struct llama_model * model) {
return llama_token_cls_impl(model->vocab);
}
// What is cls?
//llama_token llama_token_cls(const struct llama_model * model) {
// return llama_token_cls_impl(model->vocab);
//}
llama_token llama_token_sep(const struct llama_model * model) {
return llama_token_sep_impl(model->vocab);
return model->vocab.token_sep();
}
llama_token llama_token_nl (const struct llama_model * model) {
return llama_token_nl_impl(model->vocab);
return model->vocab.token_nl();
}
llama_token llama_token_pad(const struct llama_model * model) {
return llama_token_pad_impl(model->vocab);
return model->vocab.token_pad();
}
int32_t llama_add_bos_token(const struct llama_model * model) {
return llama_add_bos_token_impl(model->vocab);
return model->vocab.get_add_bos();
}
int32_t llama_add_eos_token(const struct llama_model * model) {
return llama_add_eos_token_impl(model->vocab);
return model->vocab.get_add_eos();
}
llama_token llama_token_prefix(const struct llama_model * model) {
return llama_token_prefix_impl(model->vocab);
return model->vocab.token_prefix();
}
llama_token llama_token_middle(const struct llama_model * model) {
return llama_token_middle_impl(model->vocab);
return model->vocab.token_middle();
}
llama_token llama_token_suffix(const struct llama_model * model) {
return llama_token_suffix_impl(model->vocab);
return model->vocab.token_suffix();
}
llama_token llama_token_eot(const struct llama_model * model) {
return llama_token_eot_impl(model->vocab);
return model->vocab.token_eot();
}
// deprecated
llama_token llama_token_fim_pre(const struct llama_model * model) {
return llama_token_fim_pre_impl(model->vocab);
return model->vocab.token_fim_pre();
}
// deprecated
llama_token llama_token_fim_suf(const struct llama_model * model) {
return llama_token_fim_suf_impl(model->vocab);
return model->vocab.token_fim_suf();
}
// deprecated
llama_token llama_token_fim_mid(const struct llama_model * model) {
return llama_token_fim_mid_impl(model->vocab);
return model->vocab.token_fim_mid();
}
// deprecated
llama_token llama_token_fim_pad(const struct llama_model * model) {
return llama_token_fim_pad_impl(model->vocab);
return model->vocab.token_fim_pad();
}
// deprecated
llama_token llama_token_fim_rep(const struct llama_model * model) {
return llama_token_fim_rep_impl(model->vocab);
return model->vocab.token_fim_rep();
}
// deprecated
llama_token llama_token_fim_sep(const struct llama_model * model) {
return llama_token_fim_sep_impl(model->vocab);
return model->vocab.token_fim_sep();
}
//
@@ -22056,7 +21334,7 @@ int32_t llama_tokenize(
int32_t n_tokens_max,
bool add_special,
bool parse_special) {
return llama_tokenize_impl(model->vocab, text, text_len, tokens, n_tokens_max, add_special, parse_special);
return model->vocab.tokenize(text, text_len, tokens, n_tokens_max, add_special, parse_special);
}
int32_t llama_token_to_piece(
@@ -22066,7 +21344,7 @@ int32_t llama_token_to_piece(
int32_t length,
int32_t lstrip,
bool special) {
return llama_token_to_piece_impl(model->vocab, token, buf, length, lstrip, special);
return model->vocab.token_to_piece(token, buf, length, lstrip, special);
}
int32_t llama_detokenize(
@@ -22077,7 +21355,7 @@ int32_t llama_detokenize(
int32_t text_len_max,
bool remove_special,
bool unparse_special) {
return llama_detokenize_impl(model->vocab, tokens, n_tokens, text, text_len_max, remove_special, unparse_special);
return model->vocab.detokenize(tokens, n_tokens, text, text_len_max, remove_special, unparse_special);
}
//

691
src/unicode.cpp
View File

@@ -5,20 +5,19 @@
#include "unicode.h"
#include "unicode-data.h"
#include <algorithm>
#include <cassert>
#include <codecvt>
#include <cstddef>
#include <cstdint>
#include <locale>
#include <map>
#include <regex>
#include <stdexcept>
#include <string>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include <vector>
#include <locale>
#include <codecvt>
#include <iostream>
size_t unicode_len_utf8(char src) {
const size_t lookup[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 4 };
@@ -26,7 +25,7 @@ size_t unicode_len_utf8(char src) {
return lookup[highbits];
}
static std::string unicode_cpts_to_utf8(const std::vector<uint32_t>& cps) {
static std::string unicode_cpts_to_utf8(const std::vector<uint32_t> & cps) {
std::string result;
for (size_t i = 0; i < cps.size(); ++i) {
result.append(unicode_cpt_to_utf8(cps[i]));
@@ -34,7 +33,7 @@ static std::string unicode_cpts_to_utf8(const std::vector<uint32_t>& cps) {
return result;
}
uint32_t unicode_cpt_from_utf8(const std::string& utf8, size_t& offset) {
uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset) {
assert(offset < utf8.size());
if (!(utf8[offset + 0] & 0x80)) {
auto result = utf8[offset + 0];
@@ -45,7 +44,7 @@ uint32_t unicode_cpt_from_utf8(const std::string& utf8, size_t& offset) {
throw std::invalid_argument("invalid character");
}
if (!(utf8[offset + 0] & 0x20)) {
if (offset + 1 >= utf8.size() || !((utf8[offset + 1] & 0xc0) == 0x80)) {
if (offset + 1 >= utf8.size() || ! ((utf8[offset + 1] & 0xc0) == 0x80)) {
throw std::invalid_argument("invalid character");
}
auto result = ((utf8[offset + 0] & 0x1f) << 6) | (utf8[offset + 1] & 0x3f);
@@ -53,7 +52,7 @@ uint32_t unicode_cpt_from_utf8(const std::string& utf8, size_t& offset) {
return result;
}
if (!(utf8[offset + 0] & 0x10)) {
if (offset + 2 >= utf8.size() || !((utf8[offset + 1] & 0xc0) == 0x80) || !((utf8[offset + 2] & 0xc0) == 0x80)) {
if (offset + 2 >= utf8.size() || ! ((utf8[offset + 1] & 0xc0) == 0x80) || ! ((utf8[offset + 2] & 0xc0) == 0x80)) {
throw std::invalid_argument("invalid character");
}
auto result = ((utf8[offset + 0] & 0x0f) << 12) | ((utf8[offset + 1] & 0x3f) << 6) | (utf8[offset + 2] & 0x3f);
@@ -61,7 +60,7 @@ uint32_t unicode_cpt_from_utf8(const std::string& utf8, size_t& offset) {
return result;
}
if (!(utf8[offset + 0] & 0x08)) {
if (offset + 3 >= utf8.size() || !((utf8[offset + 1] & 0xc0) == 0x80) || !((utf8[offset + 2] & 0xc0) == 0x80) || !((utf8[offset + 3] & 0xc0) == 0x80)) {
if (offset + 3 >= utf8.size() || ! ((utf8[offset + 1] & 0xc0) == 0x80) || ! ((utf8[offset + 2] & 0xc0) == 0x80) || !((utf8[offset + 3] & 0xc0) == 0x80)) {
throw std::invalid_argument("invalid character");
}
auto result = ((utf8[offset + 0] & 0x07) << 18) | ((utf8[offset + 1] & 0x3f) << 12) | ((utf8[offset + 2] & 0x3f) << 6) | (utf8[offset + 3] & 0x3f);
@@ -71,15 +70,15 @@ uint32_t unicode_cpt_from_utf8(const std::string& utf8, size_t& offset) {
throw std::invalid_argument("failed to convert utf8 to codepoint");
}
//static std::vector<uint16_t> unicode_cpt_to_utf16(uint32_t cp) {
//static std::vector<uint16_t> unicode_cpt_to_utf16(uint32_t cpt) {
// std::vector<uint16_t> result;
// if (/* 0x0000 <= cp && */ cp <= 0xffff) {
// result.emplace_back(cp);
// if (/* 0x0000 <= cpt && */ cpt <= 0xffff) {
// result.emplace_back(cpt);
// return result;
// }
// if (0x10000 <= cp && cp <= 0x10ffff) {
// result.emplace_back(0xd800 | ((cp - 0x10000) >> 10));
// result.emplace_back(0xdc00 | ((cp - 0x10000) & 0x03ff));
// if (0x10000 <= cpt && cpt <= 0x10ffff) {
// result.emplace_back(0xd800 | ((cpt - 0x10000) >> 10));
// result.emplace_back(0xdc00 | ((cpt - 0x10000) & 0x03ff));
// return result;
// }
// throw std::invalid_argument("failed to convert codepoint to utf16");
@@ -120,14 +119,14 @@ uint32_t unicode_cpt_from_utf8(const std::string& utf8, size_t& offset) {
// return result;
//}
static std::vector<codepoint_flags> unicode_cpt_flags_array() {
std::vector<codepoint_flags> cpt_flags(MAX_CODEPOINTS, codepoint_flags::UNDEFINED);
static std::vector<unicode_cpt_flags> unicode_cpt_flags_array() {
std::vector<unicode_cpt_flags> cpt_flags(MAX_CODEPOINTS, unicode_cpt_flags::UNDEFINED);
assert(unicode_ranges_flags.front().first == 0);
assert(unicode_ranges_flags.back().first == MAX_CODEPOINTS);
assert (unicode_ranges_flags.begin()[0].first == 0);
assert (unicode_ranges_flags.begin()[unicode_ranges_flags.size()-1].first == MAX_CODEPOINTS);
for (size_t i = 1; i < unicode_ranges_flags.size(); ++i) {
const auto range_ini = unicode_ranges_flags[i - 1]; // codepoint_ini, flags
const auto range_end = unicode_ranges_flags[i]; // codepoint_end, flags
const auto range_ini = unicode_ranges_flags.begin()[i-1]; // codepoint_ini, flags
const auto range_end = unicode_ranges_flags.begin()[i]; // codepoint_end, flags
for (uint32_t cpt = range_ini.first; cpt < range_end.first; ++cpt) {
cpt_flags[cpt] = range_ini.second;
}
@@ -145,7 +144,7 @@ static std::vector<codepoint_flags> unicode_cpt_flags_array() {
cpt_flags[p.second].is_uppercase = true;
}
for (auto& range : unicode_ranges_nfd) { // start, last, nfd
for (auto &range : unicode_ranges_nfd) { // start, last, nfd
cpt_flags[range.nfd].is_nfd = true;
}
@@ -200,55 +199,38 @@ static std::unordered_map<std::string, uint8_t> unicode_utf8_to_byte_map() {
return map;
}
static inline bool is_valid_utf8(const std::string& str) {
int remaining_bytes = 0; // 当前多字节字符剩余的字节数
for (unsigned char c : str) {
if (remaining_bytes == 0) {
if ((c & 0x80) == 0x00) continue; // 1字节字符
else if ((c & 0xE0) == 0xC0) remaining_bytes = 1; // 2字节
else if ((c & 0xF0) == 0xE0) remaining_bytes = 2; // 3字节
else if ((c & 0xF8) == 0xF0) remaining_bytes = 3; // 4字节
else return false; // 非法起始字节
}
else {
// 检查后续字节是否为10xxxxxx
if ((c & 0xC0) != 0x80)
{
return false;
}
remaining_bytes--;
}
}
return (remaining_bytes == 0); // 确保多字节字符完整
}
static inline std::wstring unicode_wstring_from_utf8(const std::string& s) {
static inline std::wstring unicode_wstring_from_utf8(const std::string & s) {
#if defined(__clang__)
// disable C++17 deprecation warning for std::codecvt_utf8
# pragma clang diagnostic push
# pragma clang diagnostic ignored "-Wdeprecated-declarations"
#elif defined(__GNUC__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#endif
bool isvalid = is_valid_utf8(s);
std::wstring_convert<std::codecvt_utf8<wchar_t>> conv;
#if defined(__clang__)
# pragma clang diagnostic pop
#elif defined(__GNUC__)
# pragma GCC diagnostic pop
#endif
return conv.from_bytes(s);
}
static std::vector<std::string> unicode_byte_encoding_process(const std::vector<std::string>& bpe_words) {
static std::vector<std::string> unicode_byte_encoding_process(const std::vector<std::string> & bpe_words) {
std::vector<std::string> bpe_encoded_words;
for (const auto& word : bpe_words) {
for (const auto & word : bpe_words) {
std::string text_utf;
auto utf_word = unicode_cpts_from_utf8(word);
auto utf_word = unicode_cpts_from_utf8(word);
for (size_t i = 0; i < utf_word.size(); ++i) {
text_utf += unicode_cpt_to_utf8(utf_word[i]);
}
std::string encoded_token;
for (char& c : text_utf) {
for (char & c : text_utf) {
encoded_token += unicode_byte_to_utf8(c);
}
bpe_encoded_words.emplace_back(encoded_token);
@@ -257,7 +239,7 @@ static std::vector<std::string> unicode_byte_encoding_process(const std::vector<
}
// GPT2 system regex: 's|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+
static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string& text, const std::vector<size_t>& offsets) {
static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string & text, const std::vector<size_t> & offsets) {
std::vector<size_t> bpe_offsets; // store the offset of each word
bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
@@ -271,16 +253,16 @@ static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string& te
start = offset_end;
static const uint32_t OUT_OF_RANGE = 0xFFFFFFFF;
auto _get_cpt = [&](const size_t pos) -> uint32_t {
auto _get_cpt = [&] (const size_t pos) -> uint32_t {
return (offset_ini <= pos && pos < offset_end) ? cpts[pos] : OUT_OF_RANGE;
};
auto _get_flags = [&](const size_t pos) -> codepoint_flags {
return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : codepoint_flags{};
auto _get_flags = [&] (const size_t pos) -> unicode_cpt_flags {
return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags_from_cpt(cpts[pos]) : unicode_cpt_flags{};
};
size_t _prev_end = offset_ini;
auto _add_token = [&](const size_t end) -> size_t {
auto _add_token = [&] (const size_t end) -> size_t {
assert(_prev_end <= end && end <= offset_end);
size_t len = end - _prev_end;
if (len > 0) {
@@ -296,29 +278,29 @@ static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string& te
return len;
};
for (size_t pos = offset_ini; pos < offset_end; /*pos++*/) {
for (size_t pos = offset_ini; pos < offset_end; /*pos++*/ ) {
const uint32_t cpt = _get_cpt(pos);
const auto flags = _get_flags(pos);
// regex: 's|'t|'re|'ve|'m|'ll|'d
if (cpt == '\'' && pos + 1 < offset_end) {
uint32_t cpt_next = _get_cpt(pos + 1);
if (cpt == '\'' && pos+1 < offset_end) {
uint32_t cpt_next = _get_cpt(pos+1);
if (cpt_next == 's' || cpt_next == 't' || cpt_next == 'm' || cpt_next == 'd') {
pos += _add_token(pos + 2);
pos += _add_token(pos+2);
continue;
}
if (pos + 2 < offset_end) {
uint32_t cpt_next_next = _get_cpt(pos + 2);
if (pos+2 < offset_end) {
uint32_t cpt_next_next = _get_cpt(pos+2);
if ((cpt_next == 'r' && cpt_next_next == 'e') ||
(cpt_next == 'v' && cpt_next_next == 'e') ||
(cpt_next == 'l' && cpt_next_next == 'l')) {
pos += _add_token(pos + 3);
pos += _add_token(pos+3);
continue;
}
}
}
auto flags2 = (cpt == ' ' ? _get_flags(pos + 1) : flags);
auto flags2 = (cpt == ' ' ? _get_flags(pos+1) : flags);
// regex: <space>?\p{L}+
if (flags2.is_letter) {
pos += (cpt == ' ');
@@ -348,12 +330,12 @@ static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string& te
}
size_t num_whitespaces = 0;
while (_get_flags(pos + num_whitespaces).is_whitespace) {
while (_get_flags(pos+num_whitespaces).is_whitespace) {
num_whitespaces++;
}
// regex: \s+(?!\S)
if (num_whitespaces > 1 && _get_cpt(pos + num_whitespaces) != OUT_OF_RANGE) {
if (num_whitespaces > 1 && _get_cpt(pos+num_whitespaces) != OUT_OF_RANGE) {
pos += num_whitespaces - 1;
_add_token(pos);
continue;
@@ -374,6 +356,207 @@ static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string& te
return bpe_offsets;
}
// LLAMA3 system regex: "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+"
static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string & text, const std::vector<size_t> & offsets) {
std::vector<size_t> bpe_offsets; // store the offset of each word
bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
const auto cpts = unicode_cpts_from_utf8(text);
size_t start = 0;
for (auto offset : offsets) {
const size_t offset_ini = start;
const size_t offset_end = start + offset;
assert(offset_end <= cpts.size());
start = offset_end;
static const uint32_t OUT_OF_RANGE = 0xFFFFFFFF;
auto _get_cpt = [&] (const size_t pos) -> uint32_t {
return (offset_ini <= pos && pos < offset_end) ? cpts[pos] : OUT_OF_RANGE;
};
auto _get_flags = [&] (const size_t pos) -> unicode_cpt_flags {
return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags_from_cpt(cpts[pos]) : unicode_cpt_flags{};
};
size_t _prev_end = offset_ini;
auto _add_token = [&] (const size_t end) -> size_t {
assert(_prev_end <= end && end <= offset_end);
size_t len = end - _prev_end;
if (len > 0) {
bpe_offsets.push_back(len);
}
_prev_end = end;
//if (len > 0) {
// std::string s = "";
// for(size_t p = end-len; p < end; p++)
// s += unicode_cpt_to_utf8(cpts[p]);
// printf(">>> '%s'\n", s.c_str());
//}
return len;
};
for (size_t pos = offset_ini; pos < offset_end; /*pos++*/ ) {
const uint32_t cpt = _get_cpt(pos);
const auto flags = _get_flags(pos);
// regex: (?i:'s|'t|'re|'ve|'m|'ll|'d) // case insensitive
if (cpt == '\'' && pos+1 < offset_end) {
uint32_t cpt_next = unicode_tolower(_get_cpt(pos+1));
if (cpt_next == 's' || cpt_next == 't' || cpt_next == 'm' || cpt_next == 'd') {
pos += _add_token(pos+2);
continue;
}
if (pos+2 < offset_end) {
uint32_t cpt_next_next = unicode_tolower(_get_cpt(pos+2));
if ((cpt_next == 'r' && cpt_next_next == 'e') ||
(cpt_next == 'v' && cpt_next_next == 'e') ||
(cpt_next == 'l' && cpt_next_next == 'l')) {
pos += _add_token(pos+3);
continue;
}
}
}
// regex: [^\r\n\p{L}\p{N}]?\p{L}+
if (!(cpt == '\r' || cpt == '\n' || flags.is_number)) {
if (flags.is_letter || _get_flags(pos+1).is_letter) { // one or more letters
pos++;
while (_get_flags(pos).is_letter) {
pos++;
}
_add_token(pos);
continue;
}
}
// regex: \p{N}{1,3}
if (flags.is_number) {
size_t ini = pos;
while (_get_flags(pos).is_number) {
if (++pos - ini >= 3 ) {
_add_token(pos);
ini = pos;
}
}
_add_token(pos);
continue;
}
// regex: <space>?[^\s\p{L}\p{N}]+[\r\n]*
auto flags2 = (cpt == ' ' ? _get_flags(pos+1) : flags);
if (!(flags2.is_whitespace | flags2.is_letter | flags2.is_number) && flags.as_uint()) {
pos += (cpt == ' ');
while (!(flags2.is_whitespace | flags2.is_letter | flags2.is_number) && flags2.as_uint()) {
flags2 = _get_flags(++pos);
}
uint32_t cpt2 = _get_cpt(pos);
while (cpt2 == '\r' || cpt2 == '\n') {
cpt2 = _get_cpt(++pos);
}
_add_token(pos);
continue;
}
size_t num_whitespaces = 0;
size_t last_end_r_or_n = 0;
while (_get_flags(pos+num_whitespaces).is_whitespace) {
uint32_t cpt2 = _get_cpt(pos+num_whitespaces);
if (cpt2 == '\r' || cpt2 == '\n') {
last_end_r_or_n = pos + num_whitespaces + 1;
}
num_whitespaces++;
}
// regex: \s*[\r\n]+
if (last_end_r_or_n > 0) {
pos = last_end_r_or_n;
_add_token(pos);
continue;
}
// regex: \s+(?!\S)
if (num_whitespaces > 1 && _get_cpt(pos+num_whitespaces) != OUT_OF_RANGE) {
pos += num_whitespaces - 1;
_add_token(pos);
continue;
}
// regex: \s+
if (num_whitespaces > 0) {
pos += num_whitespaces;
_add_token(pos);
continue;
}
// no matches
_add_token(++pos);
}
}
return bpe_offsets;
}
// use std::wregex to split the text
static std::vector<size_t> unicode_regex_split_stl(const std::wstring & wtext, const std::wstring & regex_expr, const std::vector<size_t> & offsets) {
std::wregex expr(regex_expr);
std::vector<size_t> bpe_offsets; // store the offset of each word
bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
size_t start = 0;
for (auto offset : offsets) {
std::wcregex_iterator it(wtext.data() + start, wtext.data() + start + offset, expr);
std::wcregex_iterator end;
int64_t start_idx = 0;
while (it != end) {
std::wcmatch match = *it;
if (match.position() > start_idx) {
bpe_offsets.emplace_back(match.position() - start_idx);
}
bpe_offsets.emplace_back(match.length());
start_idx = match.position() + match.length();
++it;
}
if (start_idx < (int64_t) offset) {
bpe_offsets.emplace_back(offset - start_idx);
}
start += offset;
}
return bpe_offsets;
}
// use std::regex to split the text
static std::vector<size_t> unicode_regex_split_stl(const std::string & text, const std::string & regex_expr, const std::vector<size_t> & offsets) {
std::regex expr(regex_expr);
std::vector<size_t> bpe_offsets; // store the offset of each word
bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
size_t start = 0;
for (auto offset : offsets) {
std::cregex_iterator it(text.data() + start, text.data() + start + offset, expr);
std::cregex_iterator end;
int64_t start_idx = 0;
while (it != end) {
std::cmatch match = *it;
if (match.position() > start_idx) {
bpe_offsets.emplace_back(match.position() - start_idx);
}
bpe_offsets.emplace_back(match.length());
start_idx = match.position() + match.length();
++it;
}
if (start_idx < (int64_t) offset) {
bpe_offsets.emplace_back(offset - start_idx);
}
start += offset;
}
return bpe_offsets;
}
// K2 system regex patterns (from tokenization_kimi.py):
// [\p{Han}]+|[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}&&[^\p{Han}]]*[\p{Ll}\p{Lm}\p{Lo}\p{M}&&[^\p{Han}]]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?|[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}&&[^\p{Han}]]+[\p{Ll}\p{Lm}\p{Lo}\p{M}&&[^\p{Han}]]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+
static std::vector<size_t> unicode_regex_split_custom_kimi_k2(const std::string & text, const std::vector<size_t> & offsets) {
@@ -394,8 +577,8 @@ static std::vector<size_t> unicode_regex_split_custom_kimi_k2(const std::string
return (offset_ini <= pos && pos < offset_end) ? cpts[pos] : OUT_OF_RANGE;
};
auto _get_flags = [&] (const size_t pos) -> codepoint_flags {
return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : codepoint_flags{};
auto _get_flags = [&] (const size_t pos) -> unicode_cpt_flags {
return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags_from_cpt(cpts[pos]) : unicode_cpt_flags{};
};
size_t _prev_end = offset_ini;
@@ -546,220 +729,17 @@ static std::vector<size_t> unicode_regex_split_custom_kimi_k2(const std::string
return bpe_offsets;
}
// LLAMA3 system regex: "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+"
static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string& text, const std::vector<size_t>& offsets) {
std::vector<size_t> bpe_offsets; // store the offset of each word
bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
const auto cpts = unicode_cpts_from_utf8(text);
size_t start = 0;
for (auto offset : offsets) {
const size_t offset_ini = start;
const size_t offset_end = start + offset;
assert(offset_end <= cpts.size());
start = offset_end;
static const uint32_t OUT_OF_RANGE = 0xFFFFFFFF;
auto _get_cpt = [&](const size_t pos) -> uint32_t {
return (offset_ini <= pos && pos < offset_end) ? cpts[pos] : OUT_OF_RANGE;
};
auto _get_flags = [&](const size_t pos) -> codepoint_flags {
return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : codepoint_flags{};
};
size_t _prev_end = offset_ini;
auto _add_token = [&](const size_t end) -> size_t {
assert(_prev_end <= end && end <= offset_end);
size_t len = end - _prev_end;
if (len > 0) {
bpe_offsets.push_back(len);
}
_prev_end = end;
//if (len > 0) {
// std::string s = "";
// for(size_t p = end-len; p < end; p++)
// s += unicode_cpt_to_utf8(cpts[p]);
// printf(">>> '%s'\n", s.c_str());
//}
return len;
};
for (size_t pos = offset_ini; pos < offset_end; /*pos++*/) {
const uint32_t cpt = _get_cpt(pos);
const auto flags = _get_flags(pos);
// regex: (?i:'s|'t|'re|'ve|'m|'ll|'d) // case insensitive
if (cpt == '\'' && pos + 1 < offset_end) {
uint32_t cpt_next = unicode_tolower(_get_cpt(pos + 1));
if (cpt_next == 's' || cpt_next == 't' || cpt_next == 'm' || cpt_next == 'd') {
pos += _add_token(pos + 2);
continue;
}
if (pos + 2 < offset_end) {
uint32_t cpt_next_next = unicode_tolower(_get_cpt(pos + 2));
if ((cpt_next == 'r' && cpt_next_next == 'e') ||
(cpt_next == 'v' && cpt_next_next == 'e') ||
(cpt_next == 'l' && cpt_next_next == 'l')) {
pos += _add_token(pos + 3);
continue;
}
}
}
// regex: [^\r\n\p{L}\p{N}]?\p{L}+
if (!(cpt == '\r' || cpt == '\n' || flags.is_number)) {
if (flags.is_letter || _get_flags(pos + 1).is_letter) { // one or more letters
pos++;
while (_get_flags(pos).is_letter) {
pos++;
}
_add_token(pos);
continue;
}
}
// regex: \p{N}{1,3}
if (flags.is_number) {
size_t ini = pos;
while (_get_flags(pos).is_number) {
if (++pos - ini >= 3) {
_add_token(pos);
ini = pos;
}
}
_add_token(pos);
continue;
}
// regex: <space>?[^\s\p{L}\p{N}]+[\r\n]*
auto flags2 = (cpt == ' ' ? _get_flags(pos + 1) : flags);
if (!(flags2.is_whitespace | flags2.is_letter | flags2.is_number) && flags.as_uint()) {
pos += (cpt == ' ');
while (!(flags2.is_whitespace | flags2.is_letter | flags2.is_number) && flags2.as_uint()) {
flags2 = _get_flags(++pos);
}
uint32_t cpt2 = _get_cpt(pos);
while (cpt2 == '\r' || cpt2 == '\n') {
cpt2 = _get_cpt(++pos);
}
_add_token(pos);
continue;
}
size_t num_whitespaces = 0;
size_t last_end_r_or_n = 0;
while (_get_flags(pos + num_whitespaces).is_whitespace) {
uint32_t cpt2 = _get_cpt(pos + num_whitespaces);
if (cpt2 == '\r' || cpt2 == '\n') {
last_end_r_or_n = pos + num_whitespaces + 1;
}
num_whitespaces++;
}
// regex: \s*[\r\n]+
if (last_end_r_or_n > 0) {
pos = last_end_r_or_n;
_add_token(pos);
continue;
}
// regex: \s+(?!\S)
if (num_whitespaces > 1 && _get_cpt(pos + num_whitespaces) != OUT_OF_RANGE) {
pos += num_whitespaces - 1;
_add_token(pos);
continue;
}
// regex: \s+
if (num_whitespaces > 0) {
pos += num_whitespaces;
_add_token(pos);
continue;
}
// no matches
_add_token(++pos);
}
}
return bpe_offsets;
}
// use std::wregex to split the text
static std::vector<size_t> unicode_regex_split_stl(const std::wstring& wtext, const std::wstring& regex_expr, const std::vector<size_t>& offsets) {
std::wregex expr(regex_expr);
std::vector<size_t> bpe_offsets; // store the offset of each word
bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
size_t start = 0;
for (auto offset : offsets) {
std::wcregex_iterator it(wtext.data() + start, wtext.data() + start + offset, expr);
std::wcregex_iterator end;
int64_t start_idx = 0;
while (it != end) {
std::wcmatch match = *it;
if (match.position() > start_idx) {
bpe_offsets.emplace_back(match.position() - start_idx);
}
bpe_offsets.emplace_back(match.length());
start_idx = match.position() + match.length();
++it;
}
if (start_idx < (int64_t)offset) {
bpe_offsets.emplace_back(offset - start_idx);
}
start += offset;
}
return bpe_offsets;
}
// use std::regex to split the text
static std::vector<size_t> unicode_regex_split_stl(const std::string& text, const std::string& regex_expr, const std::vector<size_t>& offsets) {
std::regex expr(regex_expr);
std::vector<size_t> bpe_offsets; // store the offset of each word
bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
size_t start = 0;
for (auto offset : offsets) {
std::cregex_iterator it(text.data() + start, text.data() + start + offset, expr);
std::cregex_iterator end;
int64_t start_idx = 0;
while (it != end) {
std::cmatch match = *it;
if (match.position() > start_idx) {
bpe_offsets.emplace_back(match.position() - start_idx);
}
bpe_offsets.emplace_back(match.length());
start_idx = match.position() + match.length();
++it;
}
if (start_idx < (int64_t)offset) {
bpe_offsets.emplace_back(offset - start_idx);
}
start += offset;
}
return bpe_offsets;
}
static std::vector<size_t> unicode_regex_split_custom(const std::string& text, const std::string& regex_expr, const std::vector<size_t>& offsets) {
static std::vector<size_t> unicode_regex_split_custom(const std::string & text, const std::string & regex_expr, const std::vector<size_t> & offsets) {
std::vector<size_t> bpe_offsets;
if (regex_expr == "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)") {
bpe_offsets = unicode_regex_split_custom_gpt2(text, offsets);
}
else if (
regex_expr == "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+" ||
regex_expr == "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+") {
} else if (
regex_expr == "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+" ||
regex_expr == "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+") {
bpe_offsets = unicode_regex_split_custom_llama3(text, offsets);
}
else if (regex_expr == "\\p{Han}+") {
} else if (regex_expr == "\\p{Han}+") {
// K2's first pattern - handle all K2 patterns together
bpe_offsets = unicode_regex_split_custom_kimi_k2(text, offsets);
}
@@ -771,71 +751,100 @@ static std::vector<size_t> unicode_regex_split_custom(const std::string& text, c
// interface
//
std::string unicode_cpt_to_utf8(uint32_t cp) {
std::string unicode_cpt_to_utf8(uint32_t cpt) {
std::string result;
if (/* 0x00 <= cp && */ cp <= 0x7f) {
result.push_back(cp);
if (/* 0x00 <= cpt && */ cpt <= 0x7f) {
result.push_back(cpt);
return result;
}
if (0x80 <= cp && cp <= 0x7ff) {
result.push_back(0xc0 | ((cp >> 6) & 0x1f));
result.push_back(0x80 | (cp & 0x3f));
if (0x80 <= cpt && cpt <= 0x7ff) {
result.push_back(0xc0 | ((cpt >> 6) & 0x1f));
result.push_back(0x80 | (cpt & 0x3f));
return result;
}
if (0x800 <= cp && cp <= 0xffff) {
result.push_back(0xe0 | ((cp >> 12) & 0x0f));
result.push_back(0x80 | ((cp >> 6) & 0x3f));
result.push_back(0x80 | (cp & 0x3f));
if (0x800 <= cpt && cpt <= 0xffff) {
result.push_back(0xe0 | ((cpt >> 12) & 0x0f));
result.push_back(0x80 | ((cpt >> 6) & 0x3f));
result.push_back(0x80 | (cpt & 0x3f));
return result;
}
if (0x10000 <= cp && cp <= 0x10ffff) {
result.push_back(0xf0 | ((cp >> 18) & 0x07));
result.push_back(0x80 | ((cp >> 12) & 0x3f));
result.push_back(0x80 | ((cp >> 6) & 0x3f));
result.push_back(0x80 | (cp & 0x3f));
if (0x10000 <= cpt && cpt <= 0x10ffff) {
result.push_back(0xf0 | ((cpt >> 18) & 0x07));
result.push_back(0x80 | ((cpt >> 12) & 0x3f));
result.push_back(0x80 | ((cpt >> 6) & 0x3f));
result.push_back(0x80 | (cpt & 0x3f));
return result;
}
throw std::invalid_argument("invalid codepoint");
}
std::vector<uint32_t> unicode_cpts_normalize_nfd(const std::vector<uint32_t>& cpts) {
auto comp = [](const uint32_t cpt, const range_nfd& range) {
std::vector<uint32_t> unicode_cpts_normalize_nfd(const std::vector<uint32_t> & cpts) {
auto comp = [] (const uint32_t cpt, const range_nfd & range) {
return cpt < range.first;
};
std::vector<uint32_t> result(cpts.size());
for (size_t i = 0; i < cpts.size(); ++i) {
const uint32_t cpt = cpts[i];
auto it = std::upper_bound(unicode_ranges_nfd.cbegin(), unicode_ranges_nfd.cend(), cpt, comp) - 1;
auto it = std::upper_bound(unicode_ranges_nfd.begin(), unicode_ranges_nfd.end(), cpt, comp) - 1;
result[i] = (it->first <= cpt && cpt <= it->last) ? it->nfd : cpt;
}
return result;
}
std::vector<uint32_t> unicode_cpts_from_utf8(const std::string& utf8) {
std::vector<uint32_t> unicode_cpts_from_utf8(const std::string & utf8) {
std::vector<uint32_t> result;
result.reserve(utf8.size());
size_t offset = 0;
while (offset < utf8.size()) {
result.push_back(unicode_cpt_from_utf8(utf8, offset));
try {
result.push_back(unicode_cpt_from_utf8(utf8, offset));
}
catch (const std::invalid_argument & /*ex*/) {
// Silently ignore invalid UTF-8 input to avoid leaking the exception beyond llama_tokenize
++offset;
result.emplace_back(0xFFFD); // replacement character
}
}
return result;
}
codepoint_flags unicode_cpt_flags(const uint32_t cp) {
static const codepoint_flags undef(codepoint_flags::UNDEFINED);
unicode_cpt_flags unicode_cpt_flags_from_cpt(const uint32_t cpt) {
static const unicode_cpt_flags undef(unicode_cpt_flags::UNDEFINED);
static const auto cpt_flags = unicode_cpt_flags_array();
return cp < cpt_flags.size() ? cpt_flags[cp] : undef;
return cpt < cpt_flags.size() ? cpt_flags[cpt] : undef;
}
codepoint_flags unicode_cpt_flags(const std::string& utf8) {
static const codepoint_flags undef(codepoint_flags::UNDEFINED);
unicode_cpt_flags unicode_cpt_flags_from_utf8(const std::string & utf8) {
static const unicode_cpt_flags undef(unicode_cpt_flags::UNDEFINED);
if (utf8.empty()) {
return undef; // undefined
}
size_t offset = 0;
return unicode_cpt_flags(unicode_cpt_from_utf8(utf8, offset));
return unicode_cpt_flags_from_cpt(unicode_cpt_from_utf8(utf8, offset));
}
std::string unicode_byte_to_utf8(uint8_t byte) {
static std::unordered_map<uint8_t, std::string> map = unicode_byte_to_utf8_map();
return map.at(byte);
}
uint8_t unicode_utf8_to_byte(const std::string & utf8) {
static std::unordered_map<std::string, uint8_t> map = unicode_utf8_to_byte_map();
return map.at(utf8);
}
uint32_t unicode_tolower(uint32_t cpt) {
// binary search
auto it = std::lower_bound(unicode_map_lowercase.begin(), unicode_map_lowercase.end(), cpt,
[](const std::pair<uint32_t, uint32_t> & pair, uint32_t value) {
return pair.first < value;
});
if (it != unicode_map_lowercase.end() && it->first == cpt) {
return it->second;
}
return cpt; // Return the original code point if no lowercase mapping is found
}
bool unicode_cpt_is_han(uint32_t cpt) {
@@ -870,53 +879,37 @@ bool unicode_cpt_is_han(uint32_t cpt) {
return false;
}
std::string unicode_byte_to_utf8(uint8_t byte) {
static std::unordered_map<uint8_t, std::string> map = unicode_byte_to_utf8_map();
return map.at(byte);
}
uint8_t unicode_utf8_to_byte(const std::string& utf8) {
static std::unordered_map<std::string, uint8_t> map = unicode_utf8_to_byte_map();
return map.at(utf8);
}
uint32_t unicode_tolower(uint32_t cp) {
auto it = unicode_map_lowercase.find(cp);
return it == unicode_map_lowercase.end() ? cp : it->second;
}
std::vector<std::string> unicode_regex_split(const std::string& text, const std::vector<std::string>& regex_exprs) {
std::vector<std::string> unicode_regex_split(const std::string & text, const std::vector<std::string> & regex_exprs) {
// unicode categories
static const std::map<std::string, int> k_ucat_enum = {
{ "\\p{N}", codepoint_flags::NUMBER },
{ "\\p{L}", codepoint_flags::LETTER },
{ "\\p{P}", codepoint_flags::PUNCTUATION },
{ "\\p{M}", codepoint_flags::ACCENT_MARK },
{ "\\p{S}", codepoint_flags::SYMBOL },
{ "\\p{N}", unicode_cpt_flags::NUMBER },
{ "\\p{L}", unicode_cpt_flags::LETTER },
{ "\\p{P}", unicode_cpt_flags::PUNCTUATION },
{ "\\p{M}", unicode_cpt_flags::ACCENT_MARK },
{ "\\p{S}", unicode_cpt_flags::SYMBOL },
};
static const std::map<int, int> k_ucat_cpt = {
{ codepoint_flags::NUMBER, 0xD1 },
{ codepoint_flags::LETTER, 0xD2 },
{ codepoint_flags::PUNCTUATION, 0xD3 },
{ codepoint_flags::ACCENT_MARK, 0xD4 },
{ codepoint_flags::SYMBOL, 0xD5 },
{ unicode_cpt_flags::NUMBER, 0xD1 },
{ unicode_cpt_flags::LETTER, 0xD2 },
{ unicode_cpt_flags::PUNCTUATION, 0xD3 },
{ unicode_cpt_flags::ACCENT_MARK, 0xD4 },
{ unicode_cpt_flags::SYMBOL, 0xD5 },
};
static const std::map<int, std::string> k_ucat_map = {
{ codepoint_flags::NUMBER, "\x30-\x39" }, // 0-9
{ codepoint_flags::LETTER, "\x41-\x5A\x61-\x7A" }, // A-Za-z
{ codepoint_flags::PUNCTUATION, "\x21-\x23\x25-\x2A\x2C-\x2F\x3A-\x3B\x3F-\x40\\\x5B-\\\x5D\x5F\\\x7B\\\x7D" }, // !-#%-*,-/:-;?-@\[-\]_\{\}i
{ codepoint_flags::ACCENT_MARK, "" }, // no sub-128 codepoints
{ codepoint_flags::SYMBOL, "\\\x24\\\x2B\x3C-\x3E\x5E\x60\\\x7C" }, // $+<=>^`|
{ unicode_cpt_flags::NUMBER, "\x30-\x39" }, // 0-9
{ unicode_cpt_flags::LETTER, "\x41-\x5A\x61-\x7A" }, // A-Za-z
{ unicode_cpt_flags::PUNCTUATION, "\x21-\x23\x25-\x2A\x2C-\x2F\x3A-\x3B\x3F-\x40\\\x5B-\\\x5D\x5F\\\x7B\\\x7D" }, // !-#%-*,-/:-;?-@\[-\]_\{\}
{ unicode_cpt_flags::ACCENT_MARK, "" }, // no sub-128 codepoints
{ unicode_cpt_flags::SYMBOL, "\\\x24\\\x2B\x3C-\x3E\x5E\x60\\\x7C" }, // $+<=>^`|
};
// compute collapsed codepoints only if needed by at least one regex
bool need_collapse = false;
for (auto& regex_expr : regex_exprs) {
for (const auto & regex_expr : regex_exprs) {
// search for unicode categories
for (const auto& ucat : k_ucat_enum) {
for (const auto & ucat : k_ucat_enum) {
if (std::string::npos != regex_expr.find(ucat.first)) {
need_collapse = true;
break;
@@ -927,7 +920,7 @@ std::vector<std::string> unicode_regex_split(const std::string& text, const std:
const auto cpts = unicode_cpts_from_utf8(text);
// generate a "collapsed" representation of the text, where all codepoints are replaced by a single byte
// ref: https://github.com/ggerganov/llama.cpp/pull/6920#issuecomment-2081479935
// ref: https://github.com/ggml-org/llama.cpp/pull/6920#issuecomment-2081479935
std::string text_collapsed;
if (need_collapse) {
// collapse all unicode categories
@@ -940,25 +933,23 @@ std::vector<std::string> unicode_regex_split(const std::string& text, const std:
continue;
}
const auto flags = unicode_cpt_flags(cpts[i]);
const auto flags = unicode_cpt_flags_from_cpt(cpts[i]);
if (flags.is_whitespace) {
//NOTE: C++ std::regex \s does not mach 0x85, Rust and Python regex does.
//text_collapsed[i] = (char) 0x85; // <Next Line> as whitespace fallback
text_collapsed[i] = (char)0x0B; // <vertical tab> as whitespace fallback
}
else if (k_ucat_cpt.find(flags.category_flag()) != k_ucat_cpt.end()) {
text_collapsed[i] = (char) 0x0B; // <vertical tab> as whitespace fallback
} else if (k_ucat_cpt.find(flags.category_flag()) != k_ucat_cpt.end()) {
text_collapsed[i] = k_ucat_cpt.at(flags.category_flag());
}
else {
text_collapsed[i] = (char)0xD0; // fallback
} else {
text_collapsed[i] = (char) 0xD0; // fallback
}
}
}
std::vector<size_t> bpe_offsets = { cpts.size() };
for (auto& regex_expr : regex_exprs) {
for (const auto & regex_expr : regex_exprs) {
// first, see if we have an efficient custom regex implementation
auto tmp = unicode_regex_split_custom(text, regex_expr, bpe_offsets);
@@ -972,7 +963,7 @@ std::vector<std::string> unicode_regex_split(const std::string& text, const std:
// if a unicode category is used in the regex, we use the collapsed text and replace the unicode category
// with the corresponding collapsed representation
bool use_collapsed = false;
for (auto& ucat : k_ucat_enum) {
for (const auto & ucat : k_ucat_enum) {
if (std::string::npos != regex_expr.find(ucat.first)) {
use_collapsed = true;
break;
@@ -1031,15 +1022,14 @@ std::vector<std::string> unicode_regex_split(const std::string& text, const std:
//printf("text_collapsed: %s\n", text_collapsed.c_str());
//printf("regex_expr_collapsed: %s\n", regex_expr_collapsed.c_str());
bpe_offsets = unicode_regex_split_stl(text_collapsed, regex_expr_collapsed, bpe_offsets);
}
else {
} else {
// no unicode category used, we can use std::wregex directly
const std::wstring wregex_expr = unicode_wstring_from_utf8(regex_expr);
// std::wregex \s does not mach non-ASCII whitespaces, using 0x0B as fallback
std::wstring wtext(cpts.begin(), cpts.end());
for (size_t i = 0; i < wtext.size(); ++i) {
if (wtext[i] > 0x7F && unicode_cpt_flags(wtext[i]).is_whitespace) {
if (wtext[i] > 0x7F && unicode_cpt_flags_from_cpt(wtext[i]).is_whitespace) {
wtext[i] = 0x0B;
}
}
@@ -1048,8 +1038,7 @@ std::vector<std::string> unicode_regex_split(const std::string& text, const std:
//printf("regex_expr: %s\n", regex_expr.c_str());
bpe_offsets = unicode_regex_split_stl(wtext, wregex_expr, bpe_offsets);
}
}
catch (std::regex_error& e) {
} catch (std::regex_error & e) {
fprintf(stderr, "Failed to process regex: '%s'\n", regex_expr.c_str());
fprintf(stderr, "Regex error: %s\n", e.what());
throw std::runtime_error("Failed to process regex");
@@ -1060,7 +1049,7 @@ std::vector<std::string> unicode_regex_split(const std::string& text, const std:
bpe_words.reserve(bpe_offsets.size()); // reserve memory for the approximate size
size_t start = 0;
for (size_t& offset : bpe_offsets) {
for (size_t & offset : bpe_offsets) {
bpe_words.emplace_back();
for (size_t i = start; i < start + offset; ++i) {
bpe_words.back() += unicode_cpt_to_utf8(cpts[i]);

19
src/unicode.h
View File

@@ -4,9 +4,7 @@
#include <string>
#include <vector>
// TODO: prefix all symbols with "llama_"
struct codepoint_flags {
struct unicode_cpt_flags {
enum {
UNDEFINED = 0x0001,
NUMBER = 0x0002, // regex: \p{N}
@@ -35,7 +33,7 @@ struct codepoint_flags {
uint16_t is_nfd : 1;
// decode from uint16
inline codepoint_flags(const uint16_t flags=0) {
inline unicode_cpt_flags(const uint16_t flags = 0) {
*reinterpret_cast<uint16_t*>(this) = flags;
}
@@ -50,19 +48,20 @@ struct codepoint_flags {
size_t unicode_len_utf8(char src);
std::string unicode_cpt_to_utf8(uint32_t cp);
uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset);
std::string unicode_cpt_to_utf8 (uint32_t cpt);
uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset);
std::vector<uint32_t> unicode_cpts_from_utf8(const std::string & utf8);
std::vector<uint32_t> unicode_cpts_normalize_nfd(const std::vector<uint32_t> & cpts);
codepoint_flags unicode_cpt_flags(const uint32_t cp);
codepoint_flags unicode_cpt_flags(const std::string & utf8);
unicode_cpt_flags unicode_cpt_flags_from_cpt (uint32_t cpt);
unicode_cpt_flags unicode_cpt_flags_from_utf8(const std::string & utf8);
std::string unicode_byte_to_utf8(uint8_t byte);
uint8_t unicode_utf8_to_byte(const std::string & utf8);
uint8_t unicode_utf8_to_byte(const std::string & utf8);
uint32_t unicode_tolower(uint32_t cp);
uint32_t unicode_tolower(uint32_t cpt);
bool unicode_cpt_is_han(uint32_t cpt);