Per token attributes (#7685)
* Add per token attributes enum
* Using phi-3 for testing 'rstrip'
* Using jina-v2 for testing 'lstrip'
* Brute force test for 'lstrip' and 'rstrip'
* Implement 'rstrip' and 'lstrip'
* Update phi-3 GGUF file (obsolete since 917dc8c)
* Replace llama_token_type with llama_token_attribs
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jaime-m-p
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4 changed files with 155 additions and 62 deletions
149
llama.cpp
149
llama.cpp
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@ -2149,12 +2149,12 @@ struct llama_control_vector {
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struct llama_vocab {
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using id = int32_t;
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using token = std::string;
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using ttype = llama_token_type;
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using tattr = llama_token_attr;
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struct token_data {
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token text;
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float score;
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ttype type;
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tattr attr;
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};
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enum llama_vocab_type type = LLAMA_VOCAB_TYPE_SPM;
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@ -4750,7 +4750,20 @@ static void llm_load_vocab(
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auto & token_data = vocab.id_to_token[i];
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token_data.text = std::move(word);
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token_data.score = scores ? scores[i] : 0.0f;
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token_data.type = toktypes ? (llama_token_type) toktypes[i] : LLAMA_TOKEN_TYPE_NORMAL;
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token_data.attr = LLAMA_TOKEN_ATTR_NORMAL;
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if (toktypes) { //TODO: remove, required until per token attributes are available from GGUF file
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switch(toktypes[i]) {
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case LLAMA_TOKEN_TYPE_UNKNOWN: token_data.attr = LLAMA_TOKEN_ATTR_UNKNOWN; break;
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case LLAMA_TOKEN_TYPE_UNUSED: token_data.attr = LLAMA_TOKEN_ATTR_UNUSED; break;
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case LLAMA_TOKEN_TYPE_NORMAL: token_data.attr = LLAMA_TOKEN_ATTR_NORMAL; break;
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case LLAMA_TOKEN_TYPE_CONTROL: token_data.attr = LLAMA_TOKEN_ATTR_CONTROL; break;
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case LLAMA_TOKEN_TYPE_USER_DEFINED: token_data.attr = LLAMA_TOKEN_ATTR_USER_DEFINED; break;
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case LLAMA_TOKEN_TYPE_BYTE: token_data.attr = LLAMA_TOKEN_ATTR_BYTE; break;
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case LLAMA_TOKEN_TYPE_UNDEFINED: token_data.attr = LLAMA_TOKEN_ATTR_UNDEFINED; break;
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default: token_data.attr = LLAMA_TOKEN_ATTR_UNDEFINED; break;
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}
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}
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}
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GGML_ASSERT(vocab.id_to_token.size() == vocab.token_to_id.size());
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@ -4841,7 +4854,7 @@ static void llm_load_vocab(
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// build special tokens cache
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{
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for (llama_vocab::id id = 0; id < (llama_vocab::id)n_vocab; ++id) {
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if (vocab.id_to_token[id].type != LLAMA_TOKEN_TYPE_NORMAL) {
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if (!(vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_NORMAL)) {
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vocab.cache_special_tokens.push_back(id);
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}
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}
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@ -4871,6 +4884,59 @@ static void llm_load_vocab(
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LLAMA_LOG_INFO("%s: token to piece cache size = %.4f MB\n", __func__, size_cache / 1024.0 / 1024.0);
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}
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// Handle per token attributes
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//NOTE: Each model customizes per token attributes.
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//NOTE: Per token attributes are missing from the GGUF file.
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//TODO: Extract attributes from GGUF file.
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{
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auto _contains_any = [] (const std::string &str, const std::vector<std::string> &substrs) -> bool {
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for (auto substr : substrs) {
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if (str.find(substr) < std::string::npos) {
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return true;
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}
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}
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return false;
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};
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auto _set_tokenid_attr = [&] (const llama_vocab::id id, llama_token_attr attr, bool value) {
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uint32_t current = vocab.id_to_token.at(id).attr;
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current = value ? (current | attr) : (current & ~attr);
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vocab.id_to_token[id].attr = (llama_token_attr) current;
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};
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auto _set_token_attr = [&] (const std::string & token, llama_token_attr attr, bool value) {
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_set_tokenid_attr(vocab.token_to_id.at(token), attr, value);
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};
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std::string model_name;
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std::string tokenizer_pre;
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ml.get_key(LLM_KV_GENERAL_NAME, model_name, false);
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ml.get_key(LLM_KV_TOKENIZER_PRE, tokenizer_pre, false);
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// model name to lowercase
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std::transform(model_name.begin(), model_name.end(), model_name.begin(),
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[] (const std::string::value_type x) {
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return std::tolower(x);
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}
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);
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// set attributes by model/tokenizer name
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if (_contains_any(tokenizer_pre, {"jina-v2-es", "jina-v2-de"})) {
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_set_token_attr("<mask>", LLAMA_TOKEN_ATTR_LSTRIP, true);
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} else if (_contains_any(model_name, {"phi-3", "phi3"})) {
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for (auto id : vocab.cache_special_tokens) {
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_set_tokenid_attr(id, LLAMA_TOKEN_ATTR_RSTRIP, true);
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}
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for (auto token : {"</s>"}) {
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_set_token_attr(token, LLAMA_TOKEN_ATTR_RSTRIP, true);
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}
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for (auto token : {"<unk>", "<s>", "<|endoftext|>"}) {
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_set_token_attr(token, LLAMA_TOKEN_ATTR_RSTRIP, false);
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}
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}
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}
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}
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static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
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@ -12620,27 +12686,27 @@ static enum llama_vocab_type llama_vocab_get_type(const llama_vocab & vocab) {
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static bool llama_is_normal_token(const llama_vocab & vocab, llama_token id) {
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GGML_ASSERT(vocab.type != LLAMA_VOCAB_TYPE_NONE);
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return vocab.id_to_token[id].type == LLAMA_TOKEN_TYPE_NORMAL;
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return vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_NORMAL;
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}
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static bool llama_is_unknown_token(const llama_vocab & vocab, llama_token id) {
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GGML_ASSERT(vocab.type != LLAMA_VOCAB_TYPE_NONE);
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return vocab.id_to_token[id].type == LLAMA_TOKEN_TYPE_UNKNOWN;
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return vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_UNKNOWN;
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}
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static bool llama_is_control_token(const llama_vocab & vocab, llama_token id) {
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GGML_ASSERT(vocab.type != LLAMA_VOCAB_TYPE_NONE);
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return vocab.id_to_token[id].type == LLAMA_TOKEN_TYPE_CONTROL;
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return vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_CONTROL;
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}
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static bool llama_is_byte_token(const llama_vocab & vocab, llama_token id) {
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GGML_ASSERT(vocab.type != LLAMA_VOCAB_TYPE_NONE);
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return vocab.id_to_token[id].type == LLAMA_TOKEN_TYPE_BYTE;
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return vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_BYTE;
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}
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static bool llama_is_user_defined_token(const llama_vocab& vocab, llama_token id) {
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GGML_ASSERT(vocab.type != LLAMA_VOCAB_TYPE_NONE);
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return vocab.id_to_token[id].type == LLAMA_TOKEN_TYPE_USER_DEFINED;
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return vocab.id_to_token[id].attr & LLAMA_TOKEN_ATTR_USER_DEFINED;
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}
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static uint8_t llama_token_to_byte(const llama_vocab& vocab, llama_token id) {
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@ -13258,7 +13324,8 @@ struct fragment_buffer_variant {
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static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list<fragment_buffer_variant> & buffer) {
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// for each special token
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for (const llama_vocab::id special_id : vocab.cache_special_tokens) {
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const auto & special_token = vocab.id_to_token[special_id].text;
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const auto & data = vocab.id_to_token[special_id];
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const auto & special_token = data.text;
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// for each text fragment
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std::forward_list<fragment_buffer_variant>::iterator it = buffer.begin();
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@ -13295,13 +13362,22 @@ static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list<
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if (match > raw_text_base_offset) {
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// left
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const int64_t left_reminder_offset = raw_text_base_offset + 0;
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const int64_t left_reminder_length = match - raw_text_base_offset;
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buffer.emplace_after(it, raw_text, left_reminder_offset, left_reminder_length);
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int64_t left_reminder_length = match - raw_text_base_offset;
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if (data.attr & LLAMA_TOKEN_ATTR_LSTRIP) {
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while (left_reminder_length > 0 && isspace(raw_text[left_reminder_offset + left_reminder_length - 1])) {
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left_reminder_length--;
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}
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}
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if (left_reminder_length > 0) {
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buffer.emplace_after(it, raw_text, left_reminder_offset, left_reminder_length);
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it++;
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}
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#ifdef PRETOKENIZERDEBUG
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LLAMA_LOG_WARN("FL: (%ld %ld) '%s'\n", left_reminder_offset, left_reminder_length, raw_text->substr(left_reminder_offset, left_reminder_length).c_str());
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#endif
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it++;
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}
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// special token
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@ -13310,16 +13386,25 @@ static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list<
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// right
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if (match + special_token.length() < raw_text_base_offset + raw_text_base_length) {
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const int64_t right_reminder_offset = match + special_token.length();
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const int64_t right_reminder_length = raw_text_base_length - ((match - raw_text_base_offset) + special_token.length());
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buffer.emplace_after(it, raw_text, right_reminder_offset, right_reminder_length);
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int64_t right_reminder_offset = match + special_token.length();
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int64_t right_reminder_length = raw_text_base_length - ((match - raw_text_base_offset) + special_token.length());
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if (data.attr & LLAMA_TOKEN_ATTR_RSTRIP) {
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while (right_reminder_length > 0 && isspace(raw_text[right_reminder_offset])) {
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right_reminder_offset++;
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right_reminder_length--;
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}
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}
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if (right_reminder_length > 0) {
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buffer.emplace_after(it, raw_text, right_reminder_offset, right_reminder_length);
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it++;
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}
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#ifdef PRETOKENIZERDEBUG
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LLAMA_LOG_WARN("FR: (%ld %ld) '%s'\n", right_reminder_offset, right_reminder_length, raw_text->substr(right_reminder_offset, right_reminder_length).c_str());
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#endif
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it++;
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if (source == 0) {
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buffer.erase_after(buffer.before_begin());
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} else {
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@ -13365,9 +13450,7 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
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// tokenizer.encode('', add_special_tokens=True) returns [1]
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// tokenizer.encode('', add_special_tokens=False) returns []
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static const bool rtrim = true; //TODO: as param
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bool is_prev_special = false;
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bool special_token_rtrim = false;
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if (add_special && vocab.special_add_bos != 0) {
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GGML_ASSERT(vocab.special_bos_id != -1);
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@ -13377,25 +13460,8 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
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for (const auto & fragment : fragment_buffer) {
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if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT) {
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// without adding this leading whitespace, we do not get the same results as the original tokenizer
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// TODO: It's likely possible to get rid of this string copy entirely
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// by modifying llm_tokenizer_x to operate with string offsets like pre-tokenizer
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// and passing 'add space prefix' as bool argument
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//
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auto raw_text = fragment.raw_text.substr(fragment.offset, fragment.length);
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if (special_token_rtrim) {
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size_t num_whitespaces = 0;
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while (isspace(raw_text[num_whitespaces])) {
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num_whitespaces++;
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}
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if (num_whitespaces == raw_text.size()) {
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continue; // skip if all whitespaces
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}
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raw_text = raw_text.substr(num_whitespaces);
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}
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if (vocab.add_space_prefix) {
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if (!output.size() || is_prev_special) { // prefix with space if first token
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raw_text = " " + raw_text;
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@ -13411,11 +13477,6 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
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} else { // if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN)
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output.push_back(fragment.token);
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is_prev_special = true;
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// phi-3 special tokens without rtrim, works fine for llama-spm too
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special_token_rtrim = rtrim
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&& fragment.token != vocab.special_bos_id
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&& fragment.token != vocab.special_unk_id
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&& fragment.token != vocab.special_eos_id;
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}
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}
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@ -18221,9 +18282,9 @@ float llama_token_get_score(const struct llama_model * model, llama_token token)
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return model->vocab.id_to_token[token].score;
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}
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llama_token_type llama_token_get_type(const struct llama_model * model, llama_token token) {
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llama_token_attr llama_token_get_attr(const struct llama_model * model, llama_token token) {
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GGML_ASSERT(model->vocab.type != LLAMA_VOCAB_TYPE_NONE);
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return model->vocab.id_to_token[token].type;
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return model->vocab.id_to_token[token].attr;
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}
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bool llama_token_is_eog(const struct llama_model * model, llama_token token) {
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