llama : vocab pimpl
ggml-ci
This commit is contained in:
Georgi Gerganov
parent
f4b6969b1d
commit
2c9f20d4bb
2 changed files with 62 additions and 58 deletions
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@ -66,12 +66,18 @@ struct naive_trie {
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//
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struct llm_tokenizer {
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llm_tokenizer() {}
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virtual ~llm_tokenizer() = default;
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llm_tokenizer() {}
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virtual ~llm_tokenizer() = default;
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};
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struct llama_vocab::impl {
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std::unique_ptr<llm_tokenizer> tokenizer;
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};
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llama_vocab::llama_vocab() : pimpl(new impl()) {
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}
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llama_vocab::~llama_vocab() {
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delete tokenizer;
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}
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int llama_vocab::find_bpe_rank(const std::string & token_left, const std::string & token_right) const {
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@ -194,7 +200,7 @@ struct llm_bigram_spm {
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};
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struct llm_tokenizer_spm : llm_tokenizer {
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llm_tokenizer_spm(const llama_vocab & /*vocab*/) : llm_tokenizer() {}
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llm_tokenizer_spm(const llama_vocab & /*vocab*/) {}
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};
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struct llm_tokenizer_spm_session {
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@ -364,7 +370,7 @@ struct llm_bigram_bpe {
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};
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struct llm_tokenizer_bpe : llm_tokenizer {
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llm_tokenizer_bpe(const llama_vocab & vocab) : llm_tokenizer() {
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llm_tokenizer_bpe(const llama_vocab & vocab) {
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GGML_ASSERT(vocab.type == LLAMA_VOCAB_TYPE_BPE);
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switch (vocab.type_pre) {
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case LLAMA_VOCAB_PRE_TYPE_LLAMA3:
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@ -499,8 +505,7 @@ struct llm_tokenizer_bpe : llm_tokenizer {
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};
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struct llm_tokenizer_bpe_session {
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llm_tokenizer_bpe_session(const llama_vocab & vocab) : vocab(vocab),
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bpe_tokenizer(static_cast<const llm_tokenizer_bpe *>(vocab.tokenizer)) {}
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llm_tokenizer_bpe_session(const llama_vocab & vocab, const llm_tokenizer_bpe & tokenizer) : vocab(vocab), tokenizer(tokenizer) {}
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static void append(const llama_vocab::id token_id, std::vector<llama_vocab::id> & output) {
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output.push_back(token_id);
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@ -541,7 +546,7 @@ struct llm_tokenizer_bpe_session {
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void tokenize(const std::string & text, std::vector<llama_vocab::id> & output) {
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int final_prev_index = -1;
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const auto word_collection = unicode_regex_split(text, bpe_tokenizer->regex_exprs);
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const auto word_collection = unicode_regex_split(text, tokenizer.regex_exprs);
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symbols_final.clear();
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@ -671,7 +676,7 @@ private:
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}
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const llama_vocab & vocab;
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const llm_tokenizer_bpe * bpe_tokenizer;
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const llm_tokenizer_bpe & tokenizer;
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std::vector<llm_symbol> symbols;
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std::vector<llm_symbol> symbols_final;
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@ -683,7 +688,7 @@ private:
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//
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struct llm_tokenizer_wpm : llm_tokenizer {
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llm_tokenizer_wpm(const llama_vocab & /*vocab*/) : llm_tokenizer() {}
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llm_tokenizer_wpm(const llama_vocab & /*vocab*/) {}
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};
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struct llm_tokenizer_wpm_session {
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@ -800,7 +805,7 @@ private:
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//
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struct llm_tokenizer_ugm : llm_tokenizer {
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llm_tokenizer_ugm(const llama_vocab & vocab) : llm_tokenizer() {
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llm_tokenizer_ugm(const llama_vocab & vocab) {
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if (vocab.precompiled_charsmap.size() > 0) {
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size_t charsmap_offset = 0;
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@ -867,8 +872,7 @@ struct llm_tokenizer_ugm : llm_tokenizer {
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};
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struct llm_tokenizer_ugm_session {
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llm_tokenizer_ugm_session(const llama_vocab & vocab) : vocab(vocab),
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ugm_tokenizer(static_cast<const llm_tokenizer_ugm *>(vocab.tokenizer)) {}
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llm_tokenizer_ugm_session(const llama_vocab & vocab, const llm_tokenizer_ugm & tokenizer) : vocab(vocab), tokenizer(tokenizer) {}
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/* This implementation is based on SentencePiece optimized Viterbi algorithm for
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* unigram language models. The general idea is to:
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@ -908,7 +912,7 @@ struct llm_tokenizer_ugm_session {
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// traverse the token matcher trie to find a matching token
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bool single_codepoint_token_found = false;
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const struct best_tokenization & current_best = tokenization_results[input_offset];
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const struct naive_trie * node = ugm_tokenizer->token_matcher.traverse(normalized[prefix_offset++]);
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const struct naive_trie * node = tokenizer.token_matcher.traverse(normalized[prefix_offset++]);
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while (prefix_offset <= input_len && node != NULL) {
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// check if we found valid token in prefix
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@ -938,7 +942,7 @@ struct llm_tokenizer_ugm_session {
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// if we didn't find a valid token corresponding to the whole UTF code point
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// then use unknown token as the tokenization of this UTF code point
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if (!single_codepoint_token_found) {
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const double challenger_score = current_best.score_sum + ugm_tokenizer->unknown_token_score;
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const double challenger_score = current_best.score_sum + tokenizer.unknown_token_score;
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prefix_offset = input_offset + n_utf8_code_units;
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struct best_tokenization & current_champ = tokenization_results[prefix_offset];
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if (challenger_score > current_champ.score_sum) {
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@ -982,7 +986,7 @@ private:
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normalized->clear();
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normalized->reserve(input.size() * 3);
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const std::string space = vocab.tokenizer_escape_whitespaces ? ugm_tokenizer->escaped_space : " ";
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const std::string space = vocab.tokenizer_escape_whitespaces ? tokenizer.escaped_space : " ";
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bool shall_prepend_space = !vocab.tokenizer_treat_whitespace_as_suffix && vocab.tokenizer_add_space_prefix;
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bool shall_append_space = vocab.tokenizer_treat_whitespace_as_suffix && vocab.tokenizer_add_space_prefix;
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@ -1078,7 +1082,7 @@ private:
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// if input prefix matches some user-defined token return this token as normalization result
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auto user_defined_token_match =
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ugm_tokenizer->user_defined_token_matcher.get_longest_prefix(&input[input_offset], input.size() - input_offset);
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tokenizer.user_defined_token_matcher.get_longest_prefix(&input[input_offset], input.size() - input_offset);
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if (user_defined_token_match.second > 0) {
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return { &input[input_offset], user_defined_token_match.second, user_defined_token_match.second };
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}
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@ -1086,8 +1090,8 @@ private:
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size_t longest_prefix_length = 0;
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size_t longest_prefix_offset = 0;
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if (ugm_tokenizer->xcda_array_size > 0) {
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struct xcda_array_view xcda_view(ugm_tokenizer->xcda_array, ugm_tokenizer->xcda_array_size);
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if (tokenizer.xcda_array_size > 0) {
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struct xcda_array_view xcda_view(tokenizer.xcda_array, tokenizer.xcda_array_size);
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// Find the longest normalized sequence matching the input prefix by walking
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// the XOR-compressed compact double array (XCDA) starting from the root node
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@ -1123,10 +1127,10 @@ private:
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if (longest_prefix_length > 0) {
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// we have a match, so return the replacement sequence
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if (longest_prefix_offset >= ugm_tokenizer->prefix_replacements_size) {
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if (longest_prefix_offset >= tokenizer.prefix_replacements_size) {
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throw std::runtime_error("Index out of array bounds in precompiled charsmap!");
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}
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const char * prefix_replacement = &(ugm_tokenizer->prefix_replacements)[longest_prefix_offset];
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const char * prefix_replacement = &(tokenizer.prefix_replacements)[longest_prefix_offset];
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return { prefix_replacement, strlen(prefix_replacement), longest_prefix_length };
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}
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@ -1143,7 +1147,7 @@ private:
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}
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const llama_vocab & vocab;
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const llm_tokenizer_ugm * ugm_tokenizer;
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const llm_tokenizer_ugm & tokenizer;
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};
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//
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@ -1205,7 +1209,7 @@ static std::vector<uint8_t> llama_unescape_rwkv_token(const std::string & escape
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}
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struct llm_tokenizer_rwkv : llm_tokenizer {
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llm_tokenizer_rwkv(const llama_vocab & vocab) : llm_tokenizer() {
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llm_tokenizer_rwkv(const llama_vocab & vocab) {
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// RWKV supports arbitrary byte tokens, but the vocab struct only supports string tokens.
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// For now, we decode the vocab here into the lookup we'll use for tokenization.
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@ -1221,13 +1225,12 @@ struct llm_tokenizer_rwkv : llm_tokenizer {
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};
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struct llm_tokenizer_rwkv_session {
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llm_tokenizer_rwkv_session(const llama_vocab & vocab) : vocab(vocab),
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rwkv_tokenizer(static_cast<const llm_tokenizer_rwkv &>(*vocab.tokenizer)) {}
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llm_tokenizer_rwkv_session(const llama_vocab & vocab, const llm_tokenizer_rwkv & tokenizer) : vocab(vocab), tokenizer(tokenizer) {}
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void tokenize(const std::string & text, std::vector<llama_vocab::id> & output) {
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uint32_t position = 0;
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while (position < text.size()) {
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const struct naive_trie * node = rwkv_tokenizer.token_matcher.traverse(text[position]);
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const struct naive_trie * node = tokenizer.token_matcher.traverse(text[position]);
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if (node == NULL) {
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// no matching token found, add unknown token
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output.push_back(vocab.special_unk_id);
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@ -1254,25 +1257,25 @@ struct llm_tokenizer_rwkv_session {
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private:
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const llama_vocab & vocab;
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const llm_tokenizer_rwkv & rwkv_tokenizer;
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const llm_tokenizer_rwkv & tokenizer;
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};
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void llama_vocab::init_tokenizer() {
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switch (type) {
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case LLAMA_VOCAB_TYPE_SPM:
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tokenizer = new llm_tokenizer_spm(*this);
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pimpl->tokenizer = std::make_unique<llm_tokenizer_spm>(*this);
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break;
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case LLAMA_VOCAB_TYPE_BPE:
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tokenizer = new llm_tokenizer_bpe(*this);
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pimpl->tokenizer = std::make_unique<llm_tokenizer_bpe>(*this);
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break;
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case LLAMA_VOCAB_TYPE_WPM:
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tokenizer = new llm_tokenizer_wpm(*this);
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pimpl->tokenizer = std::make_unique<llm_tokenizer_wpm>(*this);
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break;
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case LLAMA_VOCAB_TYPE_UGM:
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tokenizer = new llm_tokenizer_ugm(*this);
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pimpl->tokenizer = std::make_unique<llm_tokenizer_ugm>(*this);
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break;
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case LLAMA_VOCAB_TYPE_RWKV:
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tokenizer = new llm_tokenizer_rwkv(*this);
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pimpl->tokenizer = std::make_unique<llm_tokenizer_rwkv>(*this);
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break;
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default:
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GGML_ABORT("unsupported vocab type");
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@ -1566,7 +1569,7 @@ std::vector<llama_vocab::id> llama_vocab::tokenize(
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std::string raw_text,
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bool add_special,
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bool parse_special) const {
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GGML_ASSERT(tokenizer && "Tokenizer not initialized. Call llama_vocab::init_tokenizer() first.");
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GGML_ASSERT(pimpl->tokenizer && "Tokenizer not initialized. Call llama_vocab::init_tokenizer() first.");
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std::vector<id> output;
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std::forward_list<fragment_buffer_variant> fragment_buffer;
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@ -1628,7 +1631,7 @@ std::vector<llama_vocab::id> llama_vocab::tokenize(
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} break;
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case LLAMA_VOCAB_TYPE_BPE:
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{
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llm_tokenizer_bpe_session session(*this);
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llm_tokenizer_bpe_session session(*this, *static_cast<const llm_tokenizer_bpe *>(pimpl->tokenizer.get()));
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// it calls some other methods that are not exist in llm_tokenizer,
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// here just cast it to bpe tokenizer object
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if (add_special) {
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@ -1685,7 +1688,7 @@ std::vector<llama_vocab::id> llama_vocab::tokenize(
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GGML_ASSERT(special_bos_id != LLAMA_TOKEN_NULL);
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output.push_back(special_bos_id);
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}
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llm_tokenizer_ugm_session session(*this);
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llm_tokenizer_ugm_session session(*this, *static_cast<const llm_tokenizer_ugm *>(pimpl->tokenizer.get()));
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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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@ -1713,7 +1716,7 @@ std::vector<llama_vocab::id> llama_vocab::tokenize(
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} break;
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case LLAMA_VOCAB_TYPE_RWKV:
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{
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llm_tokenizer_rwkv_session session(*this);
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llm_tokenizer_rwkv_session session(*this, *static_cast<const llm_tokenizer_rwkv *>(pimpl->tokenizer.get()));
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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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auto raw_text = fragment.raw_text.substr(fragment.offset, fragment.length);
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@ -1872,7 +1875,7 @@ int32_t llama_vocab::detokenize(
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return 0;
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}
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GGML_ASSERT(tokenizer && "Tokenizer not initialized. Call llama_vocab::init_tokenizer() first.");
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GGML_ASSERT(pimpl->tokenizer && "Tokenizer not initialized. Call llama_vocab::init_tokenizer() first.");
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int32_t avail = text_len_max;
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int32_t total = 0;
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@ -7,8 +7,7 @@
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#include <unordered_map>
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#include <map>
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#include <set>
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struct llm_tokenizer;
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#include <memory>
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struct llama_vocab {
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using id = llama_token;
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@ -73,9 +72,7 @@ struct llama_vocab {
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std::vector<char> precompiled_charsmap;
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llm_tokenizer * tokenizer = nullptr;
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llama_vocab() = default;
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llama_vocab();
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~llama_vocab();
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int find_bpe_rank(const std::string & token_left, const std::string & token_right) const;
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@ -131,30 +128,30 @@ struct llama_vocab {
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bool add_eos_token() const;
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std::vector<id> tokenize(
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std::string raw_text,
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bool add_special,
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bool parse_special = false) const;
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std::string raw_text,
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bool add_special,
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bool parse_special = false) const;
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int32_t tokenize(
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const char * text,
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int32_t text_len,
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llama_token * tokens,
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int32_t n_tokens_max,
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bool add_special,
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bool parse_special) const;
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const char * text,
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int32_t text_len,
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llama_token * tokens,
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int32_t n_tokens_max,
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bool add_special,
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bool parse_special) const;
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// does not write null-terminator to buf
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int32_t token_to_piece(
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llama_token token,
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char * buf,
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int32_t length,
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int32_t lstrip,
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bool special) const;
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llama_token token,
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char * buf,
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int32_t length,
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int32_t lstrip,
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bool special) const;
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// check if token0 is contained as a prefix in token1
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bool token_is_prefix(
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llama_token token0,
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llama_token token1) const;
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llama_token token0,
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llama_token token1) const;
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int32_t detokenize(
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const llama_token * tokens,
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@ -167,4 +164,8 @@ struct llama_vocab {
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std::string detokenize(
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const std::vector<llama_token> & tokens,
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bool special) const;
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private:
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struct impl;
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std::unique_ptr<impl> pimpl;
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};
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