};
using llama_mlocks = std::vector<std::unique_ptr<llama_mlock>>;
-static std::string llama_token_to_piece(const struct llama_context * ctx, llama_token token, bool special) {
+// NOTE: avoid ever using this except for building the token_to_piece caches
+static std::string llama_token_to_piece(const struct llama_model * model, llama_token token, bool special) {
std::vector<char> result(8, 0);
- const int n_tokens = llama_token_to_piece(llama_get_model(ctx), token, result.data(), result.size(), special);
+ const int n_tokens = llama_token_to_piece(model, token, result.data(), result.size(), special);
if (n_tokens < 0) {
result.resize(-n_tokens);
- int check = llama_token_to_piece(llama_get_model(ctx), token, result.data(), result.size(), special);
+ int check = llama_token_to_piece(model, token, result.data(), result.size(), special);
GGML_ASSERT(check == -n_tokens);
}
else {
std::unordered_map<token, id> token_to_id;
std::vector<token_data> id_to_token;
- std::vector<id> special_tokens_cache;
+ std::vector<id> cache_special_tokens;
+ std::vector<token> cache_token_to_piece; // llama_token_to_piece(special = false);
+ std::vector<token> cache_token_to_piece_special; // llama_token_to_piece(special = true);
std::map<std::pair<std::string, std::string>, int> bpe_ranks;
vocab.special_cls_id = 101;
vocab.special_mask_id = 103;
vocab.add_space_prefix = false;
- } else {
- if (tokenizer_model == "gpt2") {
- vocab.type = LLAMA_VOCAB_TYPE_BPE;
+ } else if (tokenizer_model == "gpt2") {
+ vocab.type = LLAMA_VOCAB_TYPE_BPE;
- const int add_space_prefix_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_ADD_PREFIX).c_str());
- if (add_space_prefix_keyidx != -1) {
- vocab.add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx);
- }
- } else {
- LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_model.c_str());
- LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__);
- vocab.type = LLAMA_VOCAB_TYPE_SPM;
- return;
+ const int add_space_prefix_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_ADD_PREFIX).c_str());
+ if (add_space_prefix_keyidx != -1) {
+ vocab.add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx);
}
+
// 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) {
vocab.special_pad_id = -1;
vocab.special_cls_id = -1;
vocab.special_mask_id = -1;
+ } else {
+ throw std::runtime_error(format("unknown tokenizer: '%s'", tokenizer_model.c_str()));
}
// for now, only BPE models have pre-tokenizers
{
for (llama_vocab::id id = 0; id < (llama_vocab::id)n_vocab; ++id) {
if (vocab.id_to_token[id].type != LLAMA_TOKEN_TYPE_NORMAL) {
- vocab.special_tokens_cache.push_back(id);
+ vocab.cache_special_tokens.push_back(id);
}
}
- std::sort( vocab.special_tokens_cache.begin(), vocab.special_tokens_cache.end(),
+ 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.special_tokens_cache.size());
+ LLAMA_LOG_INFO("%s: special tokens cache size = %u\n", __func__, (uint32_t)vocab.cache_special_tokens.size());
+ }
+
+ // build token to piece caches
+ {
+ size_t size_cache = 0;
+
+ std::vector<llama_vocab::token> cache_token_to_piece (n_vocab);
+ std::vector<llama_vocab::token> cache_token_to_piece_special(n_vocab);
+
+ for (uint32_t id = 0; id < n_vocab; ++id) {
+ cache_token_to_piece[id] = llama_token_to_piece(&model, id, false);
+ cache_token_to_piece_special[id] = llama_token_to_piece(&model, id, true);
+
+ size_cache += cache_token_to_piece[id].size();
+ size_cache += cache_token_to_piece_special[id].size();
+ }
+
+ std::swap(vocab.cache_token_to_piece, cache_token_to_piece);
+ std::swap(vocab.cache_token_to_piece_special, cache_token_to_piece_special);
+
+ LLAMA_LOG_INFO("%s: token to piece cache size = %.4f MB\n", __func__, size_cache / 1024.0 / 1024.0);
}
}
static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list<fragment_buffer_variant> & buffer) {
// for each special token
- for (const llama_vocab::id special_id : vocab.special_tokens_cache) {
+ for (const llama_vocab::id special_id : vocab.cache_special_tokens) {
const auto & special_token = vocab.id_to_token[special_id].text;
// for each text fragment
void llama_sample_grammar(struct llama_context * ctx, llama_token_data_array * candidates, const struct llama_grammar * grammar) {
GGML_ASSERT(ctx);
- const int64_t t_start_sample_us = ggml_time_us();
+ int64_t t_start_sample_us = ggml_time_us();
bool allow_eog = false;
for (const auto & stack : grammar->stacks) {
std::vector<std::pair<std::vector<uint32_t>, llama_partial_utf8>> candidates_decoded;
candidates_decoded.reserve(candidates->size);
- std::vector<llama_grammar_candidate> candidates_grammar;
+
+ std::vector<llama_grammar_candidate> candidates_grammar;
candidates_grammar.reserve(candidates->size);
for (size_t i = 0; i < candidates->size; ++i) {
- const llama_token id = candidates->data[i].id;
- const std::string piece = llama_token_to_piece(ctx, id, false);
+ const llama_token id = candidates->data[i].id;
+ const std::string & piece = ctx->model.vocab.cache_token_to_piece.at(id);
if (llama_token_is_eog(&ctx->model, id)) {
if (!allow_eog) {
GGML_ASSERT(false);
}
- const std::string piece = llama_token_to_piece(ctx, token, false);
+ const std::string & piece = ctx->model.vocab.cache_token_to_piece.at(token);
// Note terminating 0 in decoded string
const auto decoded = decode_utf8(piece, grammar->partial_utf8);
// does not write null-terminator to buf
int32_t llama_token_to_piece(const struct llama_model * model, llama_token token, char * buf, int32_t length, bool special) {
+ // if we have a cache - use it
+ {
+ const auto & cache = special ? model->vocab.cache_token_to_piece_special : model->vocab.cache_token_to_piece;
+
+ if (!cache.empty()) {
+ const auto & res = cache.at(token);
+ if (length < (int) res.size()) {
+ return -(int) res.size();
+ }
+ memcpy(buf, res.c_str(), res.size());
+ return res.size();
+ }
+ }
+
if (0 <= token && token < llama_n_vocab(model)) {
switch (llama_vocab_get_type(model->vocab)) {
- case LLAMA_VOCAB_TYPE_WPM:
- case LLAMA_VOCAB_TYPE_SPM: {
- // NOTE: we accept all unsupported token types,
- // suppressing them like CONTROL tokens.
- if (llama_is_normal_token(model->vocab, token)) {
- std::string result = model->vocab.id_to_token[token].text;
- llama_unescape_whitespace(result);
- if (length < (int) result.length()) {
- return -(int) result.length();
- }
- memcpy(buf, result.c_str(), result.length());
- return result.length();
- } else if (
- (llama_is_user_defined_token(model->vocab, token)) ||
- (llama_is_control_token (model->vocab, token) && special)) {
- std::string result = model->vocab.id_to_token[token].text;
- if (length < (int) result.length()) {
- return -(int) result.length();
- }
- memcpy(buf, result.c_str(), result.length());
- return result.length();
- } else if (llama_is_unknown_token(model->vocab, token)) { // NOLINT
- if (length < 3) {
- return -3;
- }
- memcpy(buf, "\xe2\x96\x85", 3);
- return 3;
- } else if (llama_is_byte_token(model->vocab, token)) {
- if (length < 1) {
- return -1;
+ case LLAMA_VOCAB_TYPE_WPM:
+ case LLAMA_VOCAB_TYPE_SPM: {
+ // NOTE: we accept all unsupported token types,
+ // suppressing them like CONTROL tokens.
+ if (llama_is_normal_token(model->vocab, token)) {
+ std::string result = model->vocab.id_to_token[token].text;
+ llama_unescape_whitespace(result);
+ if (length < (int) result.length()) {
+ return -(int) result.length();
+ }
+ memcpy(buf, result.c_str(), result.length());
+ return result.length();
+ } else if (
+ (llama_is_user_defined_token(model->vocab, token)) ||
+ (llama_is_control_token (model->vocab, token) && special)) {
+ std::string result = model->vocab.id_to_token[token].text;
+ if (length < (int) result.length()) {
+ return -(int) result.length();
+ }
+ memcpy(buf, result.c_str(), result.length());
+ return result.length();
+ } else if (llama_is_unknown_token(model->vocab, token)) { // NOLINT
+ if (length < 3) {
+ return -3;
+ }
+ memcpy(buf, "\xe2\x96\x85", 3);
+ return 3;
+ } else if (llama_is_byte_token(model->vocab, token)) {
+ if (length < 1) {
+ return -1;
+ }
+ buf[0] = llama_token_to_byte(model->vocab, token);
+ return 1;
}
- buf[0] = llama_token_to_byte(model->vocab, token);
- return 1;
+ break;
}
- break;
- }
- case LLAMA_VOCAB_TYPE_BPE: {
- // NOTE: we accept all unsupported token types,
- // suppressing them like CONTROL tokens.
- if (llama_is_normal_token(model->vocab, token)) {
- std::string result = model->vocab.id_to_token[token].text;
- result = llama_decode_text(result);
- if (length < (int) result.length()) {
- return -(int) result.length();
- }
- memcpy(buf, result.c_str(), result.length());
- return result.length();
- } else if (
- (llama_is_user_defined_token(model->vocab, token)) ||
- (llama_is_control_token (model->vocab, token) && special)) {
- std::string result = model->vocab.id_to_token[token].text;
- if (length < (int) result.length()) {
- return -(int) result.length();
+ case LLAMA_VOCAB_TYPE_BPE: {
+ // NOTE: we accept all unsupported token types,
+ // suppressing them like CONTROL tokens.
+ if (llama_is_normal_token(model->vocab, token)) {
+ std::string result = model->vocab.id_to_token[token].text;
+ result = llama_decode_text(result);
+ if (length < (int) result.length()) {
+ return -(int) result.length();
+ }
+ memcpy(buf, result.c_str(), result.length());
+ return result.length();
+ } else if (
+ (llama_is_user_defined_token(model->vocab, token)) ||
+ (llama_is_control_token (model->vocab, token) && special)) {
+ std::string result = model->vocab.id_to_token[token].text;
+ if (length < (int) result.length()) {
+ return -(int) result.length();
+ }
+ memcpy(buf, result.c_str(), result.length());
+ return result.length();
}
- memcpy(buf, result.c_str(), result.length());
- return result.length();
+ break;
}
- break;
- }
- default:
- GGML_ASSERT(false);
+ default:
+ GGML_ASSERT(false);
}
}
return 0;
overview / pkg / ggml / sources / llama.cpp / commitdiff