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https://github.com/ggerganov/llama.cpp.git
synced 2024-12-23 21:17:54 +01:00
Fix spm whitespaces (#2806)
* llama.cpp : fix spm whitespace escaping + clean up * main.cpp : spm - add whitespace in front of prompt * test-tokenizer-0.cpp : spm - add whitespace in front of prompt
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klosax
GitHub
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2ba83c8685
@ -189,12 +189,19 @@ int main(int argc, char ** argv) {
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}
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}
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const bool is_spm = llama_vocab_type(ctx) == LLAMA_VOCAB_TYPE_SPM;
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// Add BOS if SPM tokenizer
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const bool add_bos = llama_vocab_type(ctx) == LLAMA_VOCAB_TYPE_SPM;
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// tokenize the prompt
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std::vector<llama_token> embd_inp;
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if (llama_vocab_type(ctx) == LLAMA_VOCAB_TYPE_SPM) {
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// Add a space in front of the first character to match OG llama tokenizer behavior
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params.prompt.insert(0, 1, ' ');
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}
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if (params.interactive_first || params.instruct || !params.prompt.empty() || session_tokens.empty()) {
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embd_inp = ::llama_tokenize(ctx, params.prompt, is_spm);
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embd_inp = ::llama_tokenize(ctx, params.prompt, add_bos);
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} else {
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embd_inp = session_tokens;
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}
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@ -210,9 +217,9 @@ int main(int argc, char ** argv) {
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int original_prompt_len = 0;
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if (ctx_guidance) {
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params.cfg_negative_prompt.insert(0, 1, ' ');
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guidance_inp = ::llama_tokenize(ctx_guidance, params.cfg_negative_prompt, is_spm);
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guidance_inp = ::llama_tokenize(ctx_guidance, params.cfg_negative_prompt, add_bos);
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std::vector<llama_token> original_inp = ::llama_tokenize(ctx, params.prompt, is_spm);
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std::vector<llama_token> original_inp = ::llama_tokenize(ctx, params.prompt, add_bos);
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original_prompt_len = original_inp.size();
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guidance_offset = (int)guidance_inp.size() - original_prompt_len;
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}
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@ -259,7 +266,7 @@ int main(int argc, char ** argv) {
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}
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// prefix & suffix for instruct mode
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const auto inp_pfx = ::llama_tokenize(ctx, "\n\n### Instruction:\n\n", is_spm);
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const auto inp_pfx = ::llama_tokenize(ctx, "\n\n### Instruction:\n\n", add_bos);
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const auto inp_sfx = ::llama_tokenize(ctx, "\n\n### Response:\n\n", false);
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// in instruct mode, we inject a prefix and a suffix to each input by the user
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48
llama.cpp
48
llama.cpp
@ -1635,7 +1635,7 @@ static void llm_load_hparams(
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}
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// TODO: This should probably be in llama.h
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static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & vocab, const std::string & raw_text, bool bos, bool escape);
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static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & vocab, const std::string & raw_text, bool bos);
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static void llm_load_vocab(
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llama_model_loader & ml,
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@ -1737,7 +1737,7 @@ static void llm_load_vocab(
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}
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// determine the newline token: LLaMA "<0x0A>" == 10 == '\n', Falcon 193 == '\n'
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vocab.linefeed_id = llama_tokenize_internal(vocab, "\n", false, false)[0];
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vocab.linefeed_id = llama_tokenize_internal(vocab, "\n", false)[0];
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// special tokens
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GGUF_GET_KEY(ctx, vocab.special_bos_id, gguf_get_val_u32, GGUF_TYPE_UINT32, false, kv(LLM_KV_TOKENIZER_BOS_ID));
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@ -3027,14 +3027,8 @@ static llama_token llama_byte_to_token(const llama_vocab & vocab, uint8_t ch) {
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}
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static std::string llama_escape_whitespace(const std::string& text) {
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std::string result = "\xe2\x96\x81";
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for (size_t offs = 0; offs < text.length(); ++offs) {
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if (text[offs] == ' ') {
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result += "\xe2\x96\x81";
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} else {
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result += text[offs];
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}
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}
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std::string result = text;
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replace_all(result, " ", "\xe2\x96\x81");
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return result;
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}
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@ -3219,7 +3213,7 @@ struct llm_bigram_bpe {
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};
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struct llm_tokenizer_bpe {
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llm_tokenizer_bpe(const llama_vocab & vocab, bool g2ws): vocab(vocab) { flag_g2ws = g2ws; }
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llm_tokenizer_bpe(const llama_vocab & vocab): vocab(vocab) {}
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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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@ -3371,8 +3365,6 @@ private:
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return words;
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}
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bool flag_g2ws = false;
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const llama_vocab & vocab;
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std::vector<llm_symbol> symbols;
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@ -3381,39 +3373,26 @@ private:
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llm_bigram_bpe::queue work_queue;
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};
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static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & vocab, const std::string & raw_text, bool bos, bool escape) {
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static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & vocab, const std::string & raw_text, bool bos) {
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std::vector<llama_vocab::id> output;
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if (raw_text.empty()) {
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return output;
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}
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if (bos && vocab.special_bos_id != -1) {
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output.push_back(vocab.special_bos_id);
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}
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switch (vocab.type) {
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case LLAMA_VOCAB_TYPE_SPM:
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{
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llm_tokenizer_spm tokenizer(vocab);
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if (bos) {
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output.push_back(vocab.special_bos_id);
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}
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std::string text;
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if (escape) {
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text = llama_escape_whitespace(raw_text);
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} else {
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text = raw_text;
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}
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tokenizer.tokenize(text, output);
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tokenizer.tokenize(llama_escape_whitespace(raw_text), output);
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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 tokenizer(vocab, escape);
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if (bos && vocab.special_bos_id != -1) {
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output.push_back(vocab.special_bos_id);
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}
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llm_tokenizer_bpe tokenizer(vocab);
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tokenizer.tokenize(raw_text, output);
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} break;
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};
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@ -6095,8 +6074,7 @@ int llama_tokenize_with_model(
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llama_token * tokens,
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int n_max_tokens,
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bool add_bos) {
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auto escape = llama_vocab_get_type(model->vocab) == LLAMA_VOCAB_TYPE_SPM;
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auto res = llama_tokenize_internal(model->vocab, text, add_bos, escape);
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auto res = llama_tokenize_internal(model->vocab, text, add_bos);
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if (n_max_tokens < (int) res.size()) {
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LLAMA_LOG_ERROR("%s: too many tokens\n", __func__);
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@ -100,7 +100,8 @@ int main(int argc, char **argv) {
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bool success = true;
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for (const auto & test_kv : k_tests()) {
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std::vector<llama_token> res = llama_tokenize(ctx, test_kv.first, true);
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// Add a space in front of the first character to match OG llama tokenizer behavior
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std::vector<llama_token> res = llama_tokenize(ctx, " " + test_kv.first, true);
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fprintf(stderr, "%s : '%s' tokenized to '%s'\n",
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__func__, test_kv.first.c_str(), unescape_whitespace(ctx, res).c_str());
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