From c4d4f64d33f57cc4b8fab0eb348af9f1377e6e49 Mon Sep 17 00:00:00 2001 From: Jaggzh Date: Mon, 12 Feb 2024 04:04:34 -0800 Subject: [PATCH 01/12] merged the changes from deepseeker models to main branch --- .gitignore | 17 ++ Makefile | 13 +- convert-hf-to-gguf.py | 147 +++++++++++++- llama.cpp | 229 ++++++++++------------ llama.h | 2 + models/ggml-vocab-deepseek-coder.gguf | Bin 0 -> 1156012 bytes models/ggml-vocab-deepseek-llm.gguf | Bin 0 -> 3970116 bytes tests/CMakeLists.txt | 29 +-- tests/test-tokenizer-0-deepseek-coder.cpp | 188 ++++++++++++++++++ tests/test-tokenizer-0-deepseek-coder.py | 83 ++++++++ tests/test-tokenizer-0-deepseek-llm.cpp | 188 ++++++++++++++++++ tests/test-tokenizer-0-deepseek-llm.py | 83 ++++++++ tests/test-tokenizer-0-falcon.cpp | 2 +- tests/test-tokenizer-0-falcon.py | 1 + unicode.h | 47 +++++ 15 files changed, 882 insertions(+), 147 deletions(-) create mode 100644 models/ggml-vocab-deepseek-coder.gguf create mode 100644 models/ggml-vocab-deepseek-llm.gguf create mode 100644 tests/test-tokenizer-0-deepseek-coder.cpp create mode 100644 tests/test-tokenizer-0-deepseek-coder.py create mode 100644 tests/test-tokenizer-0-deepseek-llm.cpp create mode 100644 tests/test-tokenizer-0-deepseek-llm.py diff --git a/.gitignore b/.gitignore index fdc5184a1e89b..08f8fc6c2764d 100644 --- a/.gitignore +++ b/.gitignore @@ -104,3 +104,20 @@ examples/jeopardy/results.txt poetry.lock poetry.toml nppBackup + +# Test binaries +/tests/test-grammar-parser +/tests/test-llama-grammar +/tests/test-double-float +/tests/test-grad0 +/tests/test-opt +/tests/test-quantize-fns +/tests/test-quantize-perf +/tests/test-sampling +/tests/test-tokenizer-0-llama +/tests/test-tokenizer-0-falcon +/tests/test-tokenizer-0-deepseek-coder +/tests/test-tokenizer-1-llama +/tests/test-tokenizer-1-bpe +/tests/test-rope +/tests/test-backend-ops diff --git a/Makefile b/Makefile index 7a69ad1b3c14f..6cb8934006fc9 100644 --- a/Makefile +++ b/Makefile @@ -6,7 +6,8 @@ BUILD_TARGETS = \ # Binaries only useful for tests TEST_TARGETS = \ - tests/test-llama-grammar tests/test-grammar-parser tests/test-double-float tests/test-grad0 tests/test-opt \ + tests/test-llama-grammar tests/test-tokenizer-0-deepseek-coder tests/test-tokenizer-0-deepseek-llm \ + tests/test-grammar-parser tests/test-double-float tests/test-grad0 tests/test-opt \ tests/test-quantize-fns tests/test-quantize-perf tests/test-sampling tests/test-tokenizer-0-llama \ tests/test-tokenizer-0-falcon tests/test-tokenizer-1-llama tests/test-tokenizer-1-bpe tests/test-rope \ tests/test-backend-ops tests/test-model-load-cancel tests/test-autorelease \ @@ -53,6 +54,10 @@ test: $(TEST_TARGETS) ./$$test_target $(CURDIR)/models/ggml-vocab-llama.gguf; \ elif [ "$$test_target" = "tests/test-tokenizer-0-falcon" ]; then \ ./$$test_target $(CURDIR)/models/ggml-vocab-falcon.gguf; \ + elif [ "$$test_target" = "tests/test-tokenizer-0-deepseek-coder" ]; then \ + ./$$test_target $(CURDIR)/models/ggml-vocab-deepseek-coder.gguf; \ + elif [ "$$test_target" = "tests/test-tokenizer-0-deepseek-llm" ]; then \ + ./$$test_target $(CURDIR)/models/ggml-vocab-deepseek-llm.gguf; \ elif [ "$$test_target" = "tests/test-tokenizer-1-llama" ]; then \ continue; \ elif [ "$$test_target" = "tests/test-tokenizer-1-bpe" ]; then \ @@ -962,6 +967,12 @@ tests/test-tokenizer-0-llama: tests/test-tokenizer-0-llama.cpp ggml.o llama.o $( $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) +tests/test-tokenizer-0-deepseek-coder: tests/test-tokenizer-0-deepseek-coder.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) + $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) + +tests/test-tokenizer-0-deepseek-llm: tests/test-tokenizer-0-deepseek-llm.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS) + $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) + tests/test-tokenizer-1-bpe: tests/test-tokenizer-1-bpe.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index e1ac09e024b11..95a5d030b5c21 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -213,6 +213,78 @@ def from_model_architecture(cls, arch): return cls._model_classes[arch] except KeyError: raise NotImplementedError(f'Architecture {arch!r} not supported!') from None + + @staticmethod + def from_model_architecture(model_architecture): + if model_architecture == "GPTNeoXForCausalLM": + return GPTNeoXModel + if model_architecture == "BloomForCausalLM": + return BloomModel + if model_architecture == "MPTForCausalLM": + return MPTModel + if model_architecture in ("BaichuanForCausalLM", "BaiChuanForCausalLM"): + return BaichuanModel + if model_architecture in ("FalconForCausalLM", "RWForCausalLM"): + return FalconModel + if model_architecture == "GPTBigCodeForCausalLM": + return StarCoderModel + if model_architecture == "GPTRefactForCausalLM": + return RefactModel + if model_architecture == "PersimmonForCausalLM": + return PersimmonModel + if model_architecture == "LlamaForCausalLM": + return DeepseekCoderModel + if model_architecture in ("StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM"): + return StableLMModel + if model_architecture == "QWenLMHeadModel": + return QwenModel + if model_architecture == "Qwen2ForCausalLM": + return Model + if model_architecture == "MixtralForCausalLM": + return MixtralModel + if model_architecture == "GPT2LMHeadModel": + return GPT2Model + if model_architecture == "PhiForCausalLM": + return Phi2Model + if model_architecture == "PlamoForCausalLM": + return PlamoModel + if model_architecture == "CodeShellForCausalLM": + return CodeShellModel + if model_architecture == "OrionForCausalLM": + return OrionModel + if model_architecture == "InternLM2ForCausalLM": + return InternLM2Model + if model_architecture == "MiniCPMForCausalLM": + return MiniCPMModel + if model_architecture == "BertModel": + return BertModel + + @staticmethod + def from_model_name(model_name: str): + model_name_lower = model_name.lower() + if model_name_lower in ("stablelmepoch", "llavastablelmepoch"): + return StableLMModel + if model_name_lower == "gptneox": + return GPTNeoXModel + if model_name_lower == "bloom": + return BloomModel + if model_name_lower == "mpt": + return MPTModel + if model_name_lower in ("baichuan"): + return BaichuanModel + if model_name_lower in ("falcon", "rw"): + return FalconModel + if model_name_lower == "gptbigcode": + return StarCoderModel + if model_name_lower == "gptrefact": + return RefactModel + if model_name_lower == "persimmon": + return PersimmonModel + if model_name_lower == "deepseekcoder": + return DeepseekCoderModel + if model_name_lower == "deepseekllm": + return DeepseekLLMModel + return Model def _is_model_safetensors(self) -> bool: return Model.count_model_parts(self.dir_model, ".safetensors") > 0 @@ -226,6 +298,53 @@ def _get_part_names(self): if self.num_parts == 1: # there's only one .bin file return ("pytorch_model.bin",) return (f"pytorch_model-{n:05}-of-{self.num_parts:05}.bin" for n in range(1, self.num_parts + 1)) + + def _get_model_architecture(self) -> gguf.MODEL_ARCH: + arch = self.hparams["architectures"][0] + if arch == "GPTNeoXForCausalLM": + return gguf.MODEL_ARCH.GPTNEOX + if arch == "BloomForCausalLM": + return gguf.MODEL_ARCH.BLOOM + if arch == "MPTForCausalLM": + return gguf.MODEL_ARCH.MPT + if arch in ("BaichuanForCausalLM", "BaiChuanForCausalLM"): + return gguf.MODEL_ARCH.BAICHUAN + if arch in ("FalconForCausalLM", "RWForCausalLM"): + return gguf.MODEL_ARCH.FALCON + if arch == "GPTBigCodeForCausalLM": + return gguf.MODEL_ARCH.STARCODER + if arch == "GPTRefactForCausalLM": + return gguf.MODEL_ARCH.REFACT + if arch == "PersimmonForCausalLM": + return gguf.MODEL_ARCH.PERSIMMON + if arch == "LlamaForCausalLM": + return gguf.MODEL_ARCH.LLAMA + if arch in ("StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM"): + return gguf.MODEL_ARCH.STABLELM + if arch == "QWenLMHeadModel": + return gguf.MODEL_ARCH.QWEN + if arch == "Qwen2ForCausalLM": + return gguf.MODEL_ARCH.QWEN2 + if arch == "MixtralForCausalLM": + return gguf.MODEL_ARCH.LLAMA + if arch == "GPT2LMHeadModel": + return gguf.MODEL_ARCH.GPT2 + if arch == "PhiForCausalLM": + return gguf.MODEL_ARCH.PHI2 + if arch == "PlamoForCausalLM": + return gguf.MODEL_ARCH.PLAMO + if arch == "CodeShellForCausalLM": + return gguf.MODEL_ARCH.CODESHELL + if arch == "OrionForCausalLM": + return gguf.MODEL_ARCH.ORION + if arch == "InternLM2ForCausalLM": + return gguf.MODEL_ARCH.INTERNLM2 + if arch == "MiniCPMForCausalLM": + return gguf.MODEL_ARCH.MINICPM + if arch == "BertModel": + return gguf.MODEL_ARCH.BERT + + raise NotImplementedError(f'Architecture "{arch}" not supported!') # used for GPT-2 BPE and WordPiece vocabs def get_basic_vocab(self) -> tuple[list[str], list[int]]: @@ -256,9 +375,10 @@ def get_basic_vocab(self) -> tuple[list[str], list[int]]: return tokens, toktypes - def _set_vocab_gpt2(self) -> None: + + def _set_vocab_gpt2(self, tokenizer_model:str = "gpt2") -> None: tokens, toktypes = self.get_basic_vocab() - self.gguf_writer.add_tokenizer_model("gpt2") + self.gguf_writer.add_tokenizer_model(tokenizer_model) self.gguf_writer.add_token_list(tokens) self.gguf_writer.add_token_types(toktypes) @@ -1181,7 +1301,29 @@ def write_tensors(self): n_dims = len(data.shape) print(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") self.gguf_writer.add_tensor(new_name, data) +@Model.register("LlamaForCausalLM") +class DeepseekCoderModel(Model): + def set_gguf_parameters(self): + super().set_gguf_parameters() + head_count = self.hparams["num_attention_heads"] + head_count_kv = self.hparams.get("num_key_value_heads", head_count) + self.gguf_writer.add_head_count(head_count) + self.gguf_writer.add_rope_dimension_count(self.hparams["hidden_size"] // self.hparams["num_attention_heads"]) + self.gguf_writer.add_head_count_kv(head_count_kv) + self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"]) + self.gguf_writer.add_rope_freq_base(self.hparams["rope_theta"]) + if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]: + if self.hparams["rope_scaling"].get("type") == "linear": + self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR) + self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"]) + + def set_vocab(self): + self._set_vocab_gpt2("deepseek_coder") + +class DeepseekLLMModel(DeepseekCoderModel): + def set_vocab(self): + self._set_vocab_gpt2("deepseek_llm") @Model.register("StableLmForCausalLM", "StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM") class StableLMModel(Model): @@ -2459,6 +2601,7 @@ def parse_args() -> argparse.Namespace: "model", type=Path, help="directory containing model file", ) + parser.add_argument("--model-name", type=str, default=None, help="name of the model") return parser.parse_args() diff --git a/llama.cpp b/llama.cpp index b93c1abcd85d6..6fb1564b06bab 100644 --- a/llama.cpp +++ b/llama.cpp @@ -4076,9 +4076,19 @@ static void llm_load_vocab( if (add_space_prefix_keyidx != -1) { vocab.add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx); } // The default value of add_space_prefix is true. - } else if (tokenizer_name == "gpt2") { - vocab.type = LLAMA_VOCAB_TYPE_BPE; - + } else { + if (tokenizer_name == "gpt2") { + vocab.type = LLAMA_VOCAB_TYPE_BPE; + } else if (tokenizer_name == "deepseek_coder") { + vocab.type = LLAMA_VOCAB_TYPE_DEEPSEEKCODER; + } else if (tokenizer_name == "deepseek_llm") { + vocab.type = LLAMA_VOCAB_TYPE_DEEPSEEKLLM; + } else { + LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_name.c_str()); + LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__); + vocab.type = LLAMA_VOCAB_TYPE_SPM; + return; + } // 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) { @@ -10988,6 +10998,7 @@ static uint8_t llama_token_to_byte(const llama_vocab& vocab, llama_token id) { auto buf = token_data.text.substr(3, 2); return strtol(buf.c_str(), NULL, 16); } + case LLAMA_VOCAB_TYPE_DEEPSEEKCODER: case LLAMA_VOCAB_TYPE_BPE: { GGML_ASSERT(false); return unicode_utf8_to_byte(token_data.text); @@ -11015,6 +11026,7 @@ static llama_token llama_byte_to_token(const llama_vocab & vocab, uint8_t ch) { return vocab.token_to_id.at(buf2); } case LLAMA_VOCAB_TYPE_WPM: + case LLAMA_VOCAB_TYPE_DEEPSEEKCODER: case LLAMA_VOCAB_TYPE_BPE: { return vocab.token_to_id.at(unicode_byte_to_utf8(ch)); } @@ -11212,7 +11224,21 @@ struct llm_tokenizer_bpe { void tokenize(const std::string & text, std::vector & output) { int final_prev_index = -1; - auto word_collection = bpe_gpt2_preprocess(text); + + std::vector word_collection; + switch (vocab.type) { + case LLAMA_VOCAB_TYPE_BPE: + word_collection = bpe_gpt2_preprocess(text); + break; + case LLAMA_VOCAB_TYPE_DEEPSEEKCODER: + word_collection = bpe_deepseek_coder_preprocess(text); + break; + case LLAMA_VOCAB_TYPE_DEEPSEEKLLM: + word_collection = bpe_deepseek_llm_preprocess(text); + break; + default: + break; + } symbols_final.clear(); @@ -11339,143 +11365,82 @@ struct llm_tokenizer_bpe { work_queue.push(bigram); } - std::vector bpe_gpt2_preprocess(const std::string & text) { - std::vector bpe_words; - std::vector bpe_encoded_words; - - std::string token = ""; - // GPT2 system regex: 's|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+ - bool collecting_numeric = false; - bool collecting_letter = false; - bool collecting_special = false; - bool collecting_whitespace_lookahead = false; - bool collecting = false; - - std::vector text_utf; - text_utf.reserve(text.size()); - bpe_words.reserve(text.size()); - bpe_encoded_words.reserve(text.size()); - - const auto cpts = unicode_cpts_from_utf8(text); - for (size_t i = 0; i < cpts.size(); ++i) - text_utf.emplace_back(unicode_cpt_to_utf8(cpts[i])); - - for (int i = 0; i < (int)text_utf.size(); i++) { - const std::string & utf_char = text_utf[i]; - bool split_condition = false; - int bytes_remain = text_utf.size() - i; - // forward backward lookups - const std::string & utf_char_next = (i + 1 < (int)text_utf.size()) ? text_utf[i + 1] : ""; - const std::string & utf_char_next_next = (i + 2 < (int)text_utf.size()) ? text_utf[i + 2] : ""; - - // handling contractions - if (!split_condition && bytes_remain >= 2) { - // 's|'t|'m|'d - if (utf_char == "\'" && (utf_char_next == "s" || utf_char_next == "t" || utf_char_next == "m" || utf_char_next == "d")) { - split_condition = true; - } - if (split_condition) { - if (token.size()) { - bpe_words.emplace_back(token); // push previous content as token - } - token = utf_char + utf_char_next; - bpe_words.emplace_back(token); - token = ""; - i++; - continue; - } - } - if (!split_condition && bytes_remain >= 3) { - // 're|'ve|'ll - if (utf_char == "\'" && ( - (utf_char_next == "r" && utf_char_next_next == "e") || - (utf_char_next == "v" && utf_char_next_next == "e") || - (utf_char_next == "l" && utf_char_next_next == "l")) - ) { - split_condition = true; - } - if (split_condition) { - // current token + next token can be defined - if (token.size()) { - bpe_words.emplace_back(token); // push previous content as token - } - token = utf_char + utf_char_next + utf_char_next_next; - bpe_words.emplace_back(token); // the contraction - token = ""; - i += 2; - continue; - } - } + std::vector byte_encoding_process(const std::vector & bpe_words) { + std::vectorbpe_encoded_words; + for (auto word : bpe_words) { + std::string text_utf = ""; + 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]); - if (!split_condition && !collecting) { - if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) { - collecting_letter = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) { - collecting_numeric = true; - collecting = true; - } - else if ( - ((unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) && (unicode_cpt_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) || - (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_DIGIT && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE) - ) { - collecting_special = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) { - collecting_whitespace_lookahead = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) { - split_condition = true; - } + std::string encoded_token = ""; + for (char & c : text_utf) { + encoded_token += unicode_byte_to_utf8(c); } - else if (!split_condition && collecting) { - if (collecting_letter && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER) { - split_condition = true; - } - else if (collecting_numeric && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) { - split_condition = true; - } - else if (collecting_special && (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) { - split_condition = true; - } - else if (collecting_whitespace_lookahead && (unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) { - split_condition = true; + bpe_encoded_words.emplace_back(encoded_token); + } + return bpe_encoded_words; + } + + std::vector regex_preprocess(const std::wstring & text, const std::vector & offsets, const std::wstring & regex_expr) { + std::wregex expr(regex_expr); + std::vector bpe_words; // stroe the offset of each word + bpe_words.reserve(offsets.size()); // Reserve memory for the approximate size + size_t start = 0; + for (auto offset : offsets) { + std::wcregex_iterator it(text.data() + start, text.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_words.emplace_back(match.position() - start_idx); } + bpe_words.emplace_back(match.length()); + start_idx = match.position() + match.length(); + ++it; } - if (utf_char_next == "") { - split_condition = true; // final - token += utf_char; + if (start_idx < (int64_t) offset) { + bpe_words.emplace_back(offset - start_idx); } + start += offset; + } - if (split_condition) { - if (token.size()) { - bpe_words.emplace_back(token); - } - token = utf_char; - collecting = false; - collecting_letter = false; - collecting_numeric = false; - collecting_special = false; - collecting_whitespace_lookahead = false; - } - else { - token += utf_char; - } + return bpe_words; + } + + std::vector regex_bpe_preprocess(const std::string & text, const std::vector & regex_exprs) { + std::wstring wtext = from_utf8(text); + + std::vector bpe_offsets = {wtext.size()}; + + for(auto & regex_expr : regex_exprs) { + bpe_offsets = regex_preprocess(wtext, bpe_offsets, regex_expr); } - for (std::string & word : bpe_words) { - std::string encoded_token = ""; - for (char & c : word) { - encoded_token += unicode_byte_to_utf8(c); - } - bpe_encoded_words.emplace_back(encoded_token); + std::vector bpe_words; + bpe_words.reserve(bpe_offsets.size()); // Reserve memory for the approximate size + size_t start = 0; + for(size_t & offset : bpe_offsets){ + bpe_words.emplace_back(to_utf8(std::wstring(wtext, start, offset))); + start += offset; } - return bpe_encoded_words; + return byte_encoding_process(bpe_words); + } + + std::vector bpe_gpt2_preprocess(const std::string & text) { + return regex_bpe_preprocess(text, gpt2_regex); + } + + std::vector bpe_deepseek_coder_preprocess(const std::string & text) { + return regex_bpe_preprocess(text, deepseek_coder_regex); + } + + std::vector bpe_deepseek_llm_preprocess(const std::string & text) { + return regex_bpe_preprocess(text, deepseek_llm_regex); } const llama_vocab & vocab; @@ -11795,6 +11760,8 @@ static std::vector llama_tokenize_internal(const llama_vocab & output.push_back(vocab.special_eos_id); } } break; + case LLAMA_VOCAB_TYPE_DEEPSEEKCODER: + case LLAMA_VOCAB_TYPE_DEEPSEEKLLM: case LLAMA_VOCAB_TYPE_BPE: { if (add_special && vocab.special_add_bos == 1) { @@ -16423,6 +16390,8 @@ int32_t llama_token_to_piece(const struct llama_model * model, llama_token token } break; } + case LLAMA_VOCAB_TYPE_DEEPSEEKCODER: + case LLAMA_VOCAB_TYPE_DEEPSEEKLLM: case LLAMA_VOCAB_TYPE_BPE: { // NOTE: we accept all unsupported token types, // suppressing them like CONTROL tokens. diff --git a/llama.h b/llama.h index b5da686f7b7e5..1b88208fd6c68 100644 --- a/llama.h +++ b/llama.h @@ -67,6 +67,8 @@ extern "C" { 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_DEEPSEEKCODER = 4, // Deepseek Coder + LLAMA_VOCAB_TYPE_DEEPSEEKLLM = 5, // Deepseek LLM }; // note: these values should be synchronized with ggml_rope diff --git a/models/ggml-vocab-deepseek-coder.gguf b/models/ggml-vocab-deepseek-coder.gguf new file mode 100644 index 0000000000000000000000000000000000000000..2531e1e1914ef67ce1f0daaa1e07f0d74fac6509 GIT binary patch literal 1156012 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${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf) -llama_test(test-tokenizer-0-falcon.cpp NAME test-tokenizer-0-falcon ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf) -llama_test(test-tokenizer-1-llama.cpp NAME test-tokenizer-1-llama ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf) -llama_test(test-tokenizer-1-llama.cpp NAME test-tokenizer-1-baichuan ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-baichuan.gguf) +llama_test(test-tokenizer-0-llama.cpp NAME test-tokenizer-0-llama ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf) +llama_test(test-tokenizer-0-falcon.cpp NAME test-tokenizer-0-falcon ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf) -llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-falcon ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf) -llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-aquila ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-aquila.gguf) -llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-mpt ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf) -llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-stablelm-3b-4e1t ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-stablelm-3b-4e1t.gguf) -llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-gpt-neox ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-neox.gguf) -llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-refact ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf) -llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-starcoder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf) -llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-gpt2 ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt2.gguf) -#llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-bloom ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-bloom.gguf) # BIG +llama_test(test-tokenizer-0-deepseek-coder.cpp NAME test-tokenizer-0-deepseek-coder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-deepseek-coder.gguf) + +llama_test(test-tokenizer-1-llama.cpp NAME test-tokenizer-1-llama ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf) +llama_test(test-tokenizer-1-llama.cpp NAME test-tokenizer-1-baichuan ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-baichuan.gguf) + +llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-falcon ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf) +llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-aquila ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-aquila.gguf) +llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-mpt ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf) +llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-stablelm-3b-4e1t ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-stablelm-3b-4e1t.gguf) +llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-gpt-neox ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-neox.gguf) +llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-refact ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf) +llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-starcoder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf) +llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-gpt2 ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt2.gguf) +#llama_test(test-tokenizer-1-bpe.cpp NAME test-tokenizer-1-bloom ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-bloom.gguf) # BIG llama_test(test-grammar-parser.cpp) llama_test(test-llama-grammar.cpp) diff --git a/tests/test-tokenizer-0-deepseek-coder.cpp b/tests/test-tokenizer-0-deepseek-coder.cpp new file mode 100644 index 0000000000000..16966e0726b33 --- /dev/null +++ b/tests/test-tokenizer-0-deepseek-coder.cpp @@ -0,0 +1,188 @@ +#include "llama.h" +#include "common.h" +#include "console.h" + +#include +#include +#include +#include +#include + +// generate using test-tokenizer-0-falcon.py +static const std::map> & k_tests() { + static std::map> _k_tests = { + { "" , { }, }, + { " " , { 207, }, }, + { " " , { 243, }, }, + { " " , { 315, }, }, + { "\t" , { 184, }, }, + { "\n" , { 185, }, }, + { "\t\n" , { 184, 185, }, }, + { "Hello world" , { 17535, 1835, }, }, + { " Hello world" , { 414, 9489, 1835, }, }, + { "Hello World" , { 17535, 5414, }, }, + { " Hello World" , { 414, 9489, 5414, }, }, + { " Hello World!" , { 414, 9489, 5414, 0, }, }, + { "Hello, world!" , { 17535, 11, 1835, 0, }, }, + { " Hello, world!" , { 414, 9489, 11, 1835, 0, }, }, + { " this is 🦙.cpp" , { 437, 317, 12394, 99, 234, 13, 14789, }, }, + { "w048 7tuijk dsdfhu" , { 86, 15, 19, 23, 207, 22, 83, 3963, 27659, 26078, 3934, 14072, }, }, + { "нещо на Български" , { 1593, 6478, 616, 2251, 14994, }, }, + { "កាន់តែពិសេសអាចខលចេញ" , { 155, 239, 209, 155, 239, 114, 155, 239, 228, 155, 240, 220, 155, 239, 224, 155, 240, 211, 155, 239, 231, 155, 239, 115, 155, 239, 240, 155, 240, 210, 155, 239, 240, 155, 239, 95, 155, 239, 114, 155, 239, 214, 155, 239, 210, 155, 239, 236, 155, 239, 214, 155, 240, 210, 155, 239, 218, }, }, + { "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", { 10047, 235, 209, 334, 8760, 8, 12394, 233, 114, 350, 222, 10047, 221, 104, 169, 116, 224, 334, 4684, 3909, 992, 24330, 262, 29651, 612, 8, 207, 156, 237, 214, 334, 5950, 992, 78, 12896, 344, 638, 891, 1372, 10736, 8, }, }, + { "Hello" , { 17535, }, }, + { " Hello" , { 414, 9489, }, }, + { " Hello" , { 207, 414, 9489, }, }, + { " Hello" , { 243, 414, 9489, }, }, + { " Hello" , { 315, 414, 9489, }, }, + { " Hello\n Hello" , { 315, 414, 9489, 185, 315, 414, 9489, }, }, + { "\n =" , { 185, 405, }, }, + { "' era" , { 6, 2895, }, }, + { "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～", { 17535, 11, 320, 6, 435, 0, 1717, 417, 340, 12394, 233, 210, 3015, 19100, 608, 9413, 2668, 16, 18, 16, 19, 16, 20, 16, 1393, 169, 121, 239, }, }, + + }; + + return _k_tests; +} + +int main(int argc, char **argv) { + if (argc < 2) { + fprintf(stderr, "Usage: %s vocab-file [text-file]\n", argv[0]); + return 1; + } + + const std::string fname = argv[1]; + + std::string fname_text; + if (argc > 2) { + fname_text = argv[2]; + } + + fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str()); + + llama_model * model; + llama_context * ctx; + + llama_backend_init(false); + + // load the vocab + { + auto mparams = llama_model_default_params(); + + mparams.vocab_only = true; + + model = llama_load_model_from_file(fname.c_str(), mparams); + + if (model == NULL) { + fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); + return 1; + } + + auto cparams = llama_context_default_params(); + + ctx = llama_new_context_with_model(model, cparams); + + if (ctx == NULL) { + fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); + llama_free_model(model); + return 1; + } + } + + if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_DEEPSEEKCODER) { + fprintf(stderr, "%s : error: vocab type is not DEEPSEEKCODER\n", __func__); + llama_free_model(model); + llama_free(ctx); + return 2; + } + +#ifdef _WIN32 + // We need this for unicode console support + console::init(false, false); + atexit([]() { console::cleanup(); }); +#endif + + bool success = true; + + for (const auto & test_kv : k_tests()) { + const std::vector res = llama_tokenize(ctx, test_kv.first, false); + + printf("\n"); + printf("src: '%s'\n", test_kv.first.c_str()); + printf("res: '%s'\n", llama_detokenize_bpe(ctx, res).c_str()); + printf("tok: "); + for (const auto & tok : res) { + printf("%d ", tok); + } + printf("\n"); + + bool correct = res.size() == test_kv.second.size(); + for (int i = 0; i < (int) res.size() && correct; ++i) { + if (test_kv.second[i] != res[i]) { + correct = false; + } + } + + if (!correct) { + fprintf(stderr, "%s : failed test: '%s'\n", __func__, test_kv.first.c_str()); + fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__, + llama_detokenize_bpe(ctx, res).c_str(), + llama_detokenize_bpe(ctx, test_kv.second).c_str()); + fprintf(stderr, "%s : expected tokens: ", __func__); + for (const auto & t : test_kv.second) { + fprintf(stderr, "%6d, ", t); + } + fprintf(stderr, "\n"); + fprintf(stderr, "%s : got tokens: ", __func__); + for (const auto & t : res) { + fprintf(stderr, "%6d, ", t); + } + fprintf(stderr, "\n"); + + success = false; + } + } + + if (!fname_text.empty()) { + fprintf(stderr, "%s : tokenizing: '%s'\n", __func__, fname_text.c_str()); + + std::string text; + { + std::ifstream ifs(fname_text); + if (!ifs) { + fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_text.c_str()); + return 1; + } + text = std::string(std::istreambuf_iterator(ifs), std::istreambuf_iterator()); + } + + fprintf(stderr, "%s : text size: %zu\n", __func__, text.size()); + + const std::vector res = llama_tokenize(ctx, text, false); + + fprintf(stderr, "%s : tokens: %zu\n", __func__, res.size()); + + { + const std::string fname_out = fname_text + ".tokcpp"; + + std::ofstream ofs(fname_out); + if (!ofs) { + fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str()); + return 1; + } + + for (const auto & tok : res) { + ofs << tok << " '" << llama_detokenize_bpe(ctx, std::vector{tok}) << "'" << std::endl; + } + } + + fprintf(stderr, "%s : tokens written to '%s'\n", __func__, (fname_text + ".tokcpp").c_str()); + } + + llama_free_model(model); + llama_free(ctx); + + llama_backend_free(); + + return success ? 0 : 3; +} diff --git a/tests/test-tokenizer-0-deepseek-coder.py b/tests/test-tokenizer-0-deepseek-coder.py new file mode 100644 index 0000000000000..b99840e1b9191 --- /dev/null +++ b/tests/test-tokenizer-0-deepseek-coder.py @@ -0,0 +1,83 @@ +# tests with BPE tokenizer + +import argparse + +from transformers import AutoTokenizer + +parser = argparse.ArgumentParser() +parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file") +parser.add_argument("--fname-tok", help="path to a text file to tokenize") +args = parser.parse_args() + +dir_tokenizer = args.dir_tokenizer + +tokenizer = AutoTokenizer.from_pretrained(dir_tokenizer) + +tests = [ + "", + " ", + " ", + " ", + "\t", + "\n", + "\t\n", + "Hello world", + " Hello world", + "Hello World", + " Hello World", + " Hello World!", + "Hello, world!", + " Hello, world!", + " this is 🦙.cpp", + "w048 7tuijk dsdfhu", + "нещо на Български", + "កាន់តែពិសេសអាចខលចេញ", + "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", + "Hello", + " Hello", + " Hello", + " Hello", + " Hello", + " Hello\n Hello", + "\n =", + "' era", + "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～", +] + +for text in tests: + print('text: ', text) + print(tokenizer.encode(text)) + print(tokenizer.decode(tokenizer.encode(text))) + +print("\n\ntests for C++:\n") +for text in tests: + res = tokenizer.encode(text) + + k = text.replace('\n', '\\n') + k = k.replace('\t', '\\t') + k = '"' + k + '"' + print("{ %-24s, { " % k, end='') + for x in res: + print("%7d," % x, end='') + print(" }, },") + +print(tokenizer.encode('hello')) +print(tokenizer.encode('world')) +print(tokenizer.encode(' world')) +print(tokenizer.encode('hello world')) + +fname_tok = args.fname_tok +if fname_tok: + print('tokenizing file: ', fname_tok) + fname_out = fname_tok + '.tok' + with open(fname_tok, 'r', encoding='utf-8') as f: + lines = f.readlines() + s = ''.join(lines) + res = tokenizer.encode(s) + # write to file + with open(fname_out, 'w', encoding='utf-8') as f: + for x in res: + f.write(str(x) + ' \'' + tokenizer.decode(x) + '\'\n') + print('len(res): ', len(res)) + print('len(lines): ', len(lines)) + print('results written to: ', fname_out) diff --git a/tests/test-tokenizer-0-deepseek-llm.cpp b/tests/test-tokenizer-0-deepseek-llm.cpp new file mode 100644 index 0000000000000..98d628615fe94 --- /dev/null +++ b/tests/test-tokenizer-0-deepseek-llm.cpp @@ -0,0 +1,188 @@ +#include "llama.h" +#include "common.h" +#include "console.h" + +#include +#include +#include +#include +#include + +// generate using test-tokenizer-0-falcon.py +static const std::map> & k_tests() { + static std::map> _k_tests = { + { "" , { }, }, + { " " , { 207, }, }, + { " " , { 243, }, }, + { " " , { 300, }, }, + { "\t" , { 184, }, }, + { "\n" , { 185, }, }, + { "\t\n" , { 184, 185, }, }, + { "Hello world" , { 17464, 1843, }, }, + { " Hello world" , { 37727, 1843, }, }, + { "Hello World" , { 17464, 5427, }, }, + { " Hello World" , { 37727, 5427, }, }, + { " Hello World!" , { 37727, 5427, 0, }, }, + { "Hello, world!" , { 17464, 11, 1843, 0, }, }, + { " Hello, world!" , { 37727, 11, 1843, 0, }, }, + { " this is 🦙.cpp" , { 437, 317, 12356, 99, 234, 13, 14743, }, }, + { "w048 7tuijk dsdfhu" , { 86, 15, 19, 23, 207, 22, 83, 3970, 27519, 26016, 3944, 14025, }, }, + { "нещо на Български" , { 1603, 6476, 620, 91754, }, }, + { "កាន់តែពិសេសអាចខលចេញ" , { 71374, 209, 71374, 114, 71374, 228, 155, 240, 220, 71374, 224, 155, 240, 211, 71374, 231, 71374, 115, 71374, 240, 155, 240, 210, 71374, 240, 71374, 95, 71374, 114, 71374, 214, 71374, 210, 71374, 236, 71374, 214, 155, 240, 210, 71374, 218, }, }, + { "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", { 10044, 95300, 334, 8754, 8, 33701, 114, 350, 222, 10044, 221, 104, 46713, 334, 34732, 996, 24250, 262, 80923, 8, 207, 37103, 214, 334, 5956, 89213, 344, 643, 895, 1377, 10728, 8, }, }, + { "Hello" , { 17464, }, }, + { " Hello" , { 37727, }, }, + { " Hello" , { 207, 37727, }, }, + { " Hello" , { 243, 37727, }, }, + { " Hello" , { 300, 37727, }, }, + { " Hello\n Hello" , { 300, 37727, 185, 300, 37727, }, }, + { "\n =" , { 185, 403, }, }, + { "' era" , { 6, 2906, }, }, + { "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～", { 17464, 11, 320, 6, 436, 0, 1724, 418, 340, 33701, 210, 3025, 19017, 612, 9407, 2681, 16, 18, 16, 19, 16, 20, 16, 1398, 68940, 239, }, }, + + }; + + return _k_tests; +} + +int main(int argc, char **argv) { + if (argc < 2) { + fprintf(stderr, "Usage: %s vocab-file [text-file]\n", argv[0]); + return 1; + } + + const std::string fname = argv[1]; + + std::string fname_text; + if (argc > 2) { + fname_text = argv[2]; + } + + fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str()); + + llama_model * model; + llama_context * ctx; + + llama_backend_init(false); + + // load the vocab + { + auto mparams = llama_model_default_params(); + + mparams.vocab_only = true; + + model = llama_load_model_from_file(fname.c_str(), mparams); + + if (model == NULL) { + fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); + return 1; + } + + auto cparams = llama_context_default_params(); + + ctx = llama_new_context_with_model(model, cparams); + + if (ctx == NULL) { + fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str()); + llama_free_model(model); + return 1; + } + } + + if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_DEEPSEEKLLM) { + fprintf(stderr, "%s : error: vocab type is not DEEPSEEKLLM\n", __func__); + llama_free_model(model); + llama_free(ctx); + return 2; + } + +#ifdef _WIN32 + // We need this for unicode console support + console::init(false, false); + atexit([]() { console::cleanup(); }); +#endif + + bool success = true; + + for (const auto & test_kv : k_tests()) { + const std::vector res = llama_tokenize(ctx, test_kv.first, false); + + printf("\n"); + printf("src: '%s'\n", test_kv.first.c_str()); + printf("res: '%s'\n", llama_detokenize_bpe(ctx, res).c_str()); + printf("tok: "); + for (const auto & tok : res) { + printf("%d ", tok); + } + printf("\n"); + + bool correct = res.size() == test_kv.second.size(); + for (int i = 0; i < (int) res.size() && correct; ++i) { + if (test_kv.second[i] != res[i]) { + correct = false; + } + } + + if (!correct) { + fprintf(stderr, "%s : failed test: '%s'\n", __func__, test_kv.first.c_str()); + fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__, + llama_detokenize_bpe(ctx, res).c_str(), + llama_detokenize_bpe(ctx, test_kv.second).c_str()); + fprintf(stderr, "%s : expected tokens: ", __func__); + for (const auto & t : test_kv.second) { + fprintf(stderr, "%6d, ", t); + } + fprintf(stderr, "\n"); + fprintf(stderr, "%s : got tokens: ", __func__); + for (const auto & t : res) { + fprintf(stderr, "%6d, ", t); + } + fprintf(stderr, "\n"); + + success = false; + } + } + + if (!fname_text.empty()) { + fprintf(stderr, "%s : tokenizing: '%s'\n", __func__, fname_text.c_str()); + + std::string text; + { + std::ifstream ifs(fname_text); + if (!ifs) { + fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_text.c_str()); + return 1; + } + text = std::string(std::istreambuf_iterator(ifs), std::istreambuf_iterator()); + } + + fprintf(stderr, "%s : text size: %zu\n", __func__, text.size()); + + const std::vector res = llama_tokenize(ctx, text, false); + + fprintf(stderr, "%s : tokens: %zu\n", __func__, res.size()); + + { + const std::string fname_out = fname_text + ".tokcpp"; + + std::ofstream ofs(fname_out); + if (!ofs) { + fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str()); + return 1; + } + + for (const auto & tok : res) { + ofs << tok << " '" << llama_detokenize_bpe(ctx, std::vector{tok}) << "'" << std::endl; + } + } + + fprintf(stderr, "%s : tokens written to '%s'\n", __func__, (fname_text + ".tokcpp").c_str()); + } + + llama_free_model(model); + llama_free(ctx); + + llama_backend_free(); + + return success ? 0 : 3; +} diff --git a/tests/test-tokenizer-0-deepseek-llm.py b/tests/test-tokenizer-0-deepseek-llm.py new file mode 100644 index 0000000000000..b99840e1b9191 --- /dev/null +++ b/tests/test-tokenizer-0-deepseek-llm.py @@ -0,0 +1,83 @@ +# tests with BPE tokenizer + +import argparse + +from transformers import AutoTokenizer + +parser = argparse.ArgumentParser() +parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file") +parser.add_argument("--fname-tok", help="path to a text file to tokenize") +args = parser.parse_args() + +dir_tokenizer = args.dir_tokenizer + +tokenizer = AutoTokenizer.from_pretrained(dir_tokenizer) + +tests = [ + "", + " ", + " ", + " ", + "\t", + "\n", + "\t\n", + "Hello world", + " Hello world", + "Hello World", + " Hello World", + " Hello World!", + "Hello, world!", + " Hello, world!", + " this is 🦙.cpp", + "w048 7tuijk dsdfhu", + "нещо на Български", + "កាន់តែពិសេសអាចខលចេញ", + "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", + "Hello", + " Hello", + " Hello", + " Hello", + " Hello", + " Hello\n Hello", + "\n =", + "' era", + "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～", +] + +for text in tests: + print('text: ', text) + print(tokenizer.encode(text)) + print(tokenizer.decode(tokenizer.encode(text))) + +print("\n\ntests for C++:\n") +for text in tests: + res = tokenizer.encode(text) + + k = text.replace('\n', '\\n') + k = k.replace('\t', '\\t') + k = '"' + k + '"' + print("{ %-24s, { " % k, end='') + for x in res: + print("%7d," % x, end='') + print(" }, },") + +print(tokenizer.encode('hello')) +print(tokenizer.encode('world')) +print(tokenizer.encode(' world')) +print(tokenizer.encode('hello world')) + +fname_tok = args.fname_tok +if fname_tok: + print('tokenizing file: ', fname_tok) + fname_out = fname_tok + '.tok' + with open(fname_tok, 'r', encoding='utf-8') as f: + lines = f.readlines() + s = ''.join(lines) + res = tokenizer.encode(s) + # write to file + with open(fname_out, 'w', encoding='utf-8') as f: + for x in res: + f.write(str(x) + ' \'' + tokenizer.decode(x) + '\'\n') + print('len(res): ', len(res)) + print('len(lines): ', len(lines)) + print('results written to: ', fname_out) diff --git a/tests/test-tokenizer-0-falcon.cpp b/tests/test-tokenizer-0-falcon.cpp index 472b0b3a8f436..aabac5bb05927 100644 --- a/tests/test-tokenizer-0-falcon.cpp +++ b/tests/test-tokenizer-0-falcon.cpp @@ -38,6 +38,7 @@ static const std::map> & k_tests() { { " Hello\n Hello" , { 466, 23090, 742, 23090, }, }, { "\n =" , { 1212, 40, }, }, { "' era" , { 18, 4932, }, }, + { "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～", { 9856, 23, 291, 18, 436, 12, 1265, 362, 299, 8196, 207, 204, 42, 50087, 123, 2727, 20300, 32022, 133, 234, 17419, 30137, 28, 7858, 181, 133, 236, }, }, }; return _k_tests; @@ -115,7 +116,6 @@ int main(int argc, char **argv) { printf("\n"); bool correct = res.size() == test_kv.second.size(); - for (int i = 0; i < (int) res.size() && correct; ++i) { if (test_kv.second[i] != res[i]) { correct = false; diff --git a/tests/test-tokenizer-0-falcon.py b/tests/test-tokenizer-0-falcon.py index 4f06ec9bbba5b..b99840e1b9191 100644 --- a/tests/test-tokenizer-0-falcon.py +++ b/tests/test-tokenizer-0-falcon.py @@ -41,6 +41,7 @@ " Hello\n Hello", "\n =", "' era", + "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～", ] for text in tests: diff --git a/unicode.h b/unicode.h index 6a0be393a46b4..b064aaf1089b0 100644 --- a/unicode.h +++ b/unicode.h @@ -3,6 +3,8 @@ #include #include #include +#include +#include #define CODEPOINT_TYPE_UNIDENTIFIED 0 #define CODEPOINT_TYPE_DIGIT 1 @@ -26,3 +28,48 @@ uint8_t unicode_utf8_to_byte(const std::string & utf8); // simple tolower that only implements one-to-one mapping, not one-to-many char32_t unicode_tolower(char32_t cp); +static const std::vector gpt2_regex = { + // //punc: \{p} and ascii puncs + L"[\U00000021-\U0000002F\U0000003A-\U00000040\\\U0000005B-\U00000060\U0000007B-\U0000007E\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", + // //'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S) + L"'s|'t|'re|'ve|'m|'ll|'d| 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+ L"[0-9][0-9][0-9]" + }; + +static const std::vector deepseek_coder_regex = { + L"[\r\n]", + //\s?\p{L}+ + 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4C7\U00011580-\U000115AE\U000115D8-\U000115DB\U00011600-\U0001162F\U00011644-\U00011644\U00011680-\U000116AA\U000116B8-\U000116B8\U00011700-\U0001171A\U00011800-\U0001182B\U000118A0-\U000118DF\U000118FF-\U00011906\U00011909-\U00011909\U0001190C-\U00011913\U00011915-\U00011916\U00011918-\U0001192F\U0001193F-\U0001193F\U00011941-\U00011941\U000119A0-\U000119A7\U000119AA-\U000119D0\U000119E1-\U000119E1\U000119E3-\U000119E3\U00011A00-\U00011A00\U00011A0B-\U00011A32\U00011A3A-\U00011A3A\U00011A50-\U00011A50\U00011A5C-\U00011A89\U00011A9D-\U00011A9D\U00011AC0-\U00011AF8\U00011C00-\U00011C08\U00011C0A-\U00011C2E\U00011C40-\U00011C40\U00011C72-\U00011C8F\U00011D00-\U00011D06\U00011D08-\U00011D09\U00011D0B-\U00011D30\U00011D46-\U00011D46\U00011D60-\U00011D65\U00011D67-\U00011D68\U00011D6A-\U00011D89\U00011D98-\U00011D98\U00011EE0-\U00011EF2\U00011FB0-\U00011FB0\U00012000-\U00012399\U00012480-\U00012543\U00013000-\U0001342E\U00014400-\U00014646\U00016800-\U00016A38\U00016A40-\U00016A5E\U00016AD0-\U00016AED\U00016B00-\U00016B2F\U00016B40-\U00016B43\U00016B63-\U00016B77\U00016B7D-\U00016B8F\U00016E40-\U00016E7F\U00016F00-\U00016F4A\U00016F50-\U00016F50\U00016F93-\U00016F9F\U00016FE0-\U00016FE1\U00016FE3-\U00016FE3\U00017000-\U000187F7\U00018800-\U00018CD5\U00018D00-\U00018D08\U0001B000-\U0001B11E\U0001B150-\U0001B152\U0001B164-\U0001B167\U0001B170-\U0001B2FB\U0001BC00-\U0001BC6A\U0001BC70-\U0001BC7C\U0001BC80-\U0001BC88\U0001BC90-\U0001BC99\U0001D400-\U0001D454\U0001D456-\U0001D49C\U0001D49E-\U0001D49F\U0001D4A2-\U0001D4A2\U0001D4A5-\U0001D4A6\U0001D4A9-\U0001D4AC\U0001D4AE-\U0001D4B9\U0001D4BB-\U0001D4BB\U0001D4BD-\U0001D4C3\U0001D4C5-\U0001D505\U0001D507-\U0001D50A\U0001D50D-\U0001D514\U0001D516-\U0001D51C\U0001D51E-\U0001D539\U0001D53B-\U0001D53E\U0001D540-\U0001D544\U0001D546-\U0001D546\U0001D54A-\U0001D550\U0001D552-\U0001D6A5\U0001D6A8-\U0001D6C0\U0001D6C2-\U0001D6DA\U0001D6DC-\U0001D6FA\U0001D6FC-\U0001D714\U0001D716-\U0001D734\U0001D736-\U0001D74E\U0001D750-\U0001D76E\U0001D770-\U0001D788\U0001D78A-\U0001D7A8\U0001D7AA-\U0001D7C2\U0001D7C4-\U0001D7CB\U0001E100-\U0001E12C\U0001E137-\U0001E13D\U0001E14E-\U0001E14E\U0001E2C0-\U0001E2EB\U0001E800-\U0001E8C4\U0001E900-\U0001E943\U0001E94B-\U0001E94B\U0001EE00-\U0001EE03\U0001EE05-\U0001EE1F\U0001EE21-\U0001EE22\U0001EE24-\U0001EE24\U0001EE27-\U0001EE27\U0001EE29-\U0001EE32\U0001EE34-\U0001EE37\U0001EE39-\U0001EE39\U0001EE3B-\U0001EE3B\U0001EE42-\U0001EE42\U0001EE47-\U0001EE47\U0001EE49-\U0001EE49\U0001EE4B-\U0001EE4B\U0001EE4D-\U0001EE4F\U0001EE51-\U0001EE52\U0001EE54-\U0001EE54\U0001EE57-\U0001EE57\U0001EE59-\U0001EE59\U0001EE5B-\U0001EE5B\U0001EE5D-\U0001EE5D\U0001EE5F-\U0001EE5F\U0001EE61-\U0001EE62\U0001EE64-\U0001EE64\U0001EE67-\U0001EE6A\U0001EE6C-\U0001EE72\U0001EE74-\U0001EE77\U0001EE79-\U0001EE7C\U0001EE7E-\U0001EE7E\U0001EE80-\U0001EE89\U0001EE8B-\U0001EE9B\U0001EEA1-\U0001EEA3\U0001EEA5-\U0001EEA9\U0001EEAB-\U0001EEBB\U00020000-\U0002A6DD\U0002A700-\U0002B734\U0002B740-\U0002B81D\U0002B820-\U0002CEA1\U0002CEB0-\U0002EBE0\U0002F800-\U0002FA1D\U00030000-\U0003134A]+", + //\s?\p{P}+ + L"\\s?[\U00000021-\U00000023\U00000025-\\\U0000002A\U0000002C-\U0000002F\U0000003A-\U0000003B\\\U0000003F-\U00000040\\\U0000005B-\\\U0000005D\U0000005F-\U0000005F\U0000007B-\U0000007B\U0000007D-\U0000007D\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", + //cjk + L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", + //digits + L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" + }; + +static const std::vector deepseek_llm_regex = { + L"[\r\n]", + L"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", + L"\\s?[\u0021-\u002f\u003a-\u007e\uff01-\uff0f\uff1a-\uff5e\u2018-\u201f\u3000-\u3002]+", + L"\\s+$", + L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", + L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" + }; + +inline std::wstring from_utf8(const std::string & s) +{ + std::wstring_convert> conv; + return conv.from_bytes(s); +} + +inline std::string to_utf8(const std::wstring & ws) +{ + // code to convert from utf32/utf16 to utf8 + std::wstring_convert, wchar_t> converter; + std::string utf8 = converter.to_bytes(ws); + return utf8; +} + From c848f8866e8df3474a4aa74560a310c4b5451d2d Mon Sep 17 00:00:00 2001 From: Kazim Abrar Mahi Date: Sat, 23 Mar 2024 01:13:08 +0600 Subject: [PATCH 02/12] Moved regex patterns to unicode.cpp and updated unicode.h --- llama.cpp | 45 +++++++++++++++++------------------------- unicode.cpp | 57 +++++++++++++++++++++++++++++++++++++++++++++++++++++ unicode.h | 49 +++++---------------------------------------- 3 files changed, 80 insertions(+), 71 deletions(-) diff --git a/llama.cpp b/llama.cpp index 6fb1564b06bab..f66213c8c20e6 100644 --- a/llama.cpp +++ b/llama.cpp @@ -4076,6 +4076,16 @@ static void llm_load_vocab( if (add_space_prefix_keyidx != -1) { vocab.add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx); } // The default value of add_space_prefix is true. + } else if (tokenizer_name == "bert") { + vocab.type = LLAMA_VOCAB_TYPE_WPM; + + // default special tokens + vocab.special_bos_id = 101; + vocab.special_eos_id = 102; + vocab.special_unk_id = 100; + vocab.special_sep_id = -1; + vocab.special_pad_id = -1; + vocab.add_space_prefix = false; } else { if (tokenizer_name == "gpt2") { vocab.type = LLAMA_VOCAB_TYPE_BPE; @@ -4115,30 +4125,11 @@ static void llm_load_vocab( } // default special tokens - 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_name == "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; - vocab.add_space_prefix = false; - } else { - LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_name.c_str()); - LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__); - - vocab.type = LLAMA_VOCAB_TYPE_SPM; + 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; } } @@ -11432,15 +11423,15 @@ struct llm_tokenizer_bpe { } std::vector bpe_gpt2_preprocess(const std::string & text) { - return regex_bpe_preprocess(text, gpt2_regex); + return regex_bpe_preprocess(text, get_gpt2_regex()); } std::vector bpe_deepseek_coder_preprocess(const std::string & text) { - return regex_bpe_preprocess(text, deepseek_coder_regex); + return regex_bpe_preprocess(text, get_deepseek_coder_regex()); } std::vector bpe_deepseek_llm_preprocess(const std::string & text) { - return regex_bpe_preprocess(text, deepseek_llm_regex); + return regex_bpe_preprocess(text, get_deepseek_llm_regex()); } const llama_vocab & vocab; diff --git a/unicode.cpp b/unicode.cpp index df8c5f5813471..2477d4ae17157 100644 --- a/unicode.cpp +++ b/unicode.cpp @@ -275,3 +275,60 @@ char32_t unicode_tolower(char32_t cp) { auto it = unicode_map_lowercase.find(cp); return it == unicode_map_lowercase.end() ? cp : it->second; } +static const std::vector gpt2_regex = { + // //punc: \{p} and ascii puncs + L"[\U00000021-\U0000002F\U0000003A-\U00000040\\\U0000005B-\U00000060\U0000007B-\U0000007E\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", + // //'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S) + L"'s|'t|'re|'ve|'m|'ll|'d| 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+ L"[0-9][0-9][0-9]" + }; + +static const std::vector deepseek_coder_regex = { + L"[\r\n]", + //\s?\p{L}+ + 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4C7\U00011580-\U000115AE\U000115D8-\U000115DB\U00011600-\U0001162F\U00011644-\U00011644\U00011680-\U000116AA\U000116B8-\U000116B8\U00011700-\U0001171A\U00011800-\U0001182B\U000118A0-\U000118DF\U000118FF-\U00011906\U00011909-\U00011909\U0001190C-\U00011913\U00011915-\U00011916\U00011918-\U0001192F\U0001193F-\U0001193F\U00011941-\U00011941\U000119A0-\U000119A7\U000119AA-\U000119D0\U000119E1-\U000119E1\U000119E3-\U000119E3\U00011A00-\U00011A00\U00011A0B-\U00011A32\U00011A3A-\U00011A3A\U00011A50-\U00011A50\U00011A5C-\U00011A89\U00011A9D-\U00011A9D\U00011AC0-\U00011AF8\U00011C00-\U00011C08\U00011C0A-\U00011C2E\U00011C40-\U00011C40\U00011C72-\U00011C8F\U00011D00-\U00011D06\U00011D08-\U00011D09\U00011D0B-\U00011D30\U00011D46-\U00011D46\U00011D60-\U00011D65\U00011D67-\U00011D68\U00011D6A-\U00011D89\U00011D98-\U00011D98\U00011EE0-\U00011EF2\U00011FB0-\U00011FB0\U00012000-\U00012399\U00012480-\U00012543\U00013000-\U0001342E\U00014400-\U00014646\U00016800-\U00016A38\U00016A40-\U00016A5E\U00016AD0-\U00016AED\U00016B00-\U00016B2F\U00016B40-\U00016B43\U00016B63-\U00016B77\U00016B7D-\U00016B8F\U00016E40-\U00016E7F\U00016F00-\U00016F4A\U00016F50-\U00016F50\U00016F93-\U00016F9F\U00016FE0-\U00016FE1\U00016FE3-\U00016FE3\U00017000-\U000187F7\U00018800-\U00018CD5\U00018D00-\U00018D08\U0001B000-\U0001B11E\U0001B150-\U0001B152\U0001B164-\U0001B167\U0001B170-\U0001B2FB\U0001BC00-\U0001BC6A\U0001BC70-\U0001BC7C\U0001BC80-\U0001BC88\U0001BC90-\U0001BC99\U0001D400-\U0001D454\U0001D456-\U0001D49C\U0001D49E-\U0001D49F\U0001D4A2-\U0001D4A2\U0001D4A5-\U0001D4A6\U0001D4A9-\U0001D4AC\U0001D4AE-\U0001D4B9\U0001D4BB-\U0001D4BB\U0001D4BD-\U0001D4C3\U0001D4C5-\U0001D505\U0001D507-\U0001D50A\U0001D50D-\U0001D514\U0001D516-\U0001D51C\U0001D51E-\U0001D539\U0001D53B-\U0001D53E\U0001D540-\U0001D544\U0001D546-\U0001D546\U0001D54A-\U0001D550\U0001D552-\U0001D6A5\U0001D6A8-\U0001D6C0\U0001D6C2-\U0001D6DA\U0001D6DC-\U0001D6FA\U0001D6FC-\U0001D714\U0001D716-\U0001D734\U0001D736-\U0001D74E\U0001D750-\U0001D76E\U0001D770-\U0001D788\U0001D78A-\U0001D7A8\U0001D7AA-\U0001D7C2\U0001D7C4-\U0001D7CB\U0001E100-\U0001E12C\U0001E137-\U0001E13D\U0001E14E-\U0001E14E\U0001E2C0-\U0001E2EB\U0001E800-\U0001E8C4\U0001E900-\U0001E943\U0001E94B-\U0001E94B\U0001EE00-\U0001EE03\U0001EE05-\U0001EE1F\U0001EE21-\U0001EE22\U0001EE24-\U0001EE24\U0001EE27-\U0001EE27\U0001EE29-\U0001EE32\U0001EE34-\U0001EE37\U0001EE39-\U0001EE39\U0001EE3B-\U0001EE3B\U0001EE42-\U0001EE42\U0001EE47-\U0001EE47\U0001EE49-\U0001EE49\U0001EE4B-\U0001EE4B\U0001EE4D-\U0001EE4F\U0001EE51-\U0001EE52\U0001EE54-\U0001EE54\U0001EE57-\U0001EE57\U0001EE59-\U0001EE59\U0001EE5B-\U0001EE5B\U0001EE5D-\U0001EE5D\U0001EE5F-\U0001EE5F\U0001EE61-\U0001EE62\U0001EE64-\U0001EE64\U0001EE67-\U0001EE6A\U0001EE6C-\U0001EE72\U0001EE74-\U0001EE77\U0001EE79-\U0001EE7C\U0001EE7E-\U0001EE7E\U0001EE80-\U0001EE89\U0001EE8B-\U0001EE9B\U0001EEA1-\U0001EEA3\U0001EEA5-\U0001EEA9\U0001EEAB-\U0001EEBB\U00020000-\U0002A6DD\U0002A700-\U0002B734\U0002B740-\U0002B81D\U0002B820-\U0002CEA1\U0002CEB0-\U0002EBE0\U0002F800-\U0002FA1D\U00030000-\U0003134A]+", + //\s?\p{P}+ + L"\\s?[\U00000021-\U00000023\U00000025-\\\U0000002A\U0000002C-\U0000002F\U0000003A-\U0000003B\\\U0000003F-\U00000040\\\U0000005B-\\\U0000005D\U0000005F-\U0000005F\U0000007B-\U0000007B\U0000007D-\U0000007D\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", + //cjk + L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", + //digits + L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" + }; + +static const std::vector deepseek_llm_regex = { + L"[\r\n]", + L"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", + L"\\s?[\u0021-\u002f\u003a-\u007e\uff01-\uff0f\uff1a-\uff5e\u2018-\u201f\u3000-\u3002]+", + L"\\s+$", + L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", + L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" + }; + +std::vector get_gpt2_regex() { + return gpt2_regex; +} + +std::vector get_deepseek_coder_regex() { + return deepseek_coder_regex; +} + +std::vector get_deepseek_llm_regex() { + return deepseek_llm_regex; +} + +inline std::wstring from_utf8(const std::string & s) +{ + std::wstring_convert> conv; + return conv.from_bytes(s); +} + +inline std::string to_utf8(const std::wstring & ws) +{ + // code to convert from utf32/utf16 to utf8 + std::wstring_convert, wchar_t> converter; + std::string utf8 = converter.to_bytes(ws); + return utf8; +} + diff --git a/unicode.h b/unicode.h index b064aaf1089b0..4481358b63feb 100644 --- a/unicode.h +++ b/unicode.h @@ -26,50 +26,11 @@ int unicode_cpt_type(const std::string & utf8); std::string unicode_byte_to_utf8(uint8_t byte); uint8_t unicode_utf8_to_byte(const std::string & utf8); -// simple tolower that only implements one-to-one mapping, not one-to-many char32_t unicode_tolower(char32_t cp); -static const std::vector gpt2_regex = { - // //punc: \{p} and ascii puncs - 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- //\s?\p{P}+ - L"\\s?[\U00000021-\U00000023\U00000025-\\\U0000002A\U0000002C-\U0000002F\U0000003A-\U0000003B\\\U0000003F-\U00000040\\\U0000005B-\\\U0000005D\U0000005F-\U0000005F\U0000007B-\U0000007B\U0000007D-\U0000007D\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", - //cjk - L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", - //digits - L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" - }; - -static const std::vector deepseek_llm_regex = { - L"[\r\n]", - L"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", - L"\\s?[\u0021-\u002f\u003a-\u007e\uff01-\uff0f\uff1a-\uff5e\u2018-\u201f\u3000-\u3002]+", - L"\\s+$", - L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", - L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" - }; - -inline std::wstring from_utf8(const std::string & s) -{ - std::wstring_convert> conv; - return conv.from_bytes(s); -} - -inline std::string to_utf8(const std::wstring & ws) -{ - // code to convert from utf32/utf16 to utf8 - std::wstring_convert, wchar_t> converter; - std::string utf8 = converter.to_bytes(ws); - return utf8; -} +std::vector get_gpt2_regex(); +std::vector get_deepseek_coder_regex(); +std::vector get_deepseek_llm_regex(); +inline std::wstring from_utf8(const std::string & s); +inline std::string to_utf8(const std::wstring & ws); \ No newline at end of file From 4812c79779aa7545c814e87dd0a45b52cb0fb456 Mon Sep 17 00:00:00 2001 From: Kazim Abrar Mahi Date: Sat, 23 Mar 2024 01:16:04 +0600 Subject: [PATCH 03/12] Moved header files --- unicode.cpp | 2 ++ unicode.h | 2 -- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/unicode.cpp b/unicode.cpp index 2477d4ae17157..73db0e1ce40bf 100644 --- a/unicode.cpp +++ b/unicode.cpp @@ -10,6 +10,8 @@ #include #include #include +#include +#include static std::string unicode_cpts_to_utf8(const std::vector & cps) { std::string result; diff --git a/unicode.h b/unicode.h index 4481358b63feb..efe04ce99c525 100644 --- a/unicode.h +++ b/unicode.h @@ -3,8 +3,6 @@ #include #include #include -#include -#include #define CODEPOINT_TYPE_UNIDENTIFIED 0 #define CODEPOINT_TYPE_DIGIT 1 From de86bb0eb3f9f92bb187e14d61d0e5c67ad64251 Mon Sep 17 00:00:00 2001 From: Kazim Abrar Mahi Date: Sat, 23 Mar 2024 14:38:06 +0600 Subject: [PATCH 04/12] Resolved issues --- tests/CMakeLists.txt | 1 + tests/test-tokenizer-0-deepseek-coder.cpp | 2 +- tests/test-tokenizer-0-deepseek-llm.cpp | 2 +- unicode.cpp | 14 -------------- unicode.h | 17 +++++++++++++++-- 5 files changed, 18 insertions(+), 18 deletions(-) diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt index f7ea1b561cd9f..a1c143f5ff0c3 100644 --- a/tests/CMakeLists.txt +++ b/tests/CMakeLists.txt @@ -46,6 +46,7 @@ llama_test(test-tokenizer-0-llama.cpp NAME test-tokenizer-0-llama llama_test(test-tokenizer-0-falcon.cpp NAME test-tokenizer-0-falcon ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf) llama_test(test-tokenizer-0-deepseek-coder.cpp NAME test-tokenizer-0-deepseek-coder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-deepseek-coder.gguf) +llama_test(test-tokenizer-0-deepseek-llm.cpp NAME test-tokenizer-0-deepseek-llm ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-deepseek-llm.gguf) llama_test(test-tokenizer-1-llama.cpp NAME test-tokenizer-1-llama ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf) llama_test(test-tokenizer-1-llama.cpp NAME test-tokenizer-1-baichuan ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-baichuan.gguf) diff --git a/tests/test-tokenizer-0-deepseek-coder.cpp b/tests/test-tokenizer-0-deepseek-coder.cpp index 16966e0726b33..1be6b7ab71dd2 100644 --- a/tests/test-tokenizer-0-deepseek-coder.cpp +++ b/tests/test-tokenizer-0-deepseek-coder.cpp @@ -63,7 +63,7 @@ int main(int argc, char **argv) { llama_model * model; llama_context * ctx; - llama_backend_init(false); + llama_backend_init(); // load the vocab { diff --git a/tests/test-tokenizer-0-deepseek-llm.cpp b/tests/test-tokenizer-0-deepseek-llm.cpp index 98d628615fe94..8afc0a81f3cef 100644 --- a/tests/test-tokenizer-0-deepseek-llm.cpp +++ b/tests/test-tokenizer-0-deepseek-llm.cpp @@ -63,7 +63,7 @@ int main(int argc, char **argv) { llama_model * model; llama_context * ctx; - llama_backend_init(false); + llama_backend_init(); // load the vocab { diff --git a/unicode.cpp b/unicode.cpp index 73db0e1ce40bf..0a2863ea004b7 100644 --- a/unicode.cpp +++ b/unicode.cpp @@ -10,8 +10,6 @@ #include #include #include -#include -#include static std::string unicode_cpts_to_utf8(const std::vector & cps) { std::string result; @@ -320,17 +318,5 @@ std::vector get_deepseek_llm_regex() { return deepseek_llm_regex; } -inline std::wstring from_utf8(const std::string & s) -{ - std::wstring_convert> conv; - return conv.from_bytes(s); -} -inline std::string to_utf8(const std::wstring & ws) -{ - // code to convert from utf32/utf16 to utf8 - std::wstring_convert, wchar_t> converter; - std::string utf8 = converter.to_bytes(ws); - return utf8; -} diff --git a/unicode.h b/unicode.h index efe04ce99c525..cf2f8e976f8ee 100644 --- a/unicode.h +++ b/unicode.h @@ -3,6 +3,8 @@ #include #include #include +#include +#include #define CODEPOINT_TYPE_UNIDENTIFIED 0 #define CODEPOINT_TYPE_DIGIT 1 @@ -30,5 +32,16 @@ std::vector get_gpt2_regex(); std::vector get_deepseek_coder_regex(); std::vector get_deepseek_llm_regex(); -inline std::wstring from_utf8(const std::string & s); -inline std::string to_utf8(const std::wstring & ws); \ No newline at end of file +inline std::wstring from_utf8(const std::string & s) +{ + std::wstring_convert> conv; + return conv.from_bytes(s); +} + +inline std::string to_utf8(const std::wstring & ws) +{ + // code to convert from utf32/utf16 to utf8 + std::wstring_convert, wchar_t> converter; + std::string utf8 = converter.to_bytes(ws); + return utf8; +} \ No newline at end of file From bb8029048267050e60d0d439040212b1f2cdf6fb Mon Sep 17 00:00:00 2001 From: Kazim Abrar Mahi Date: Mon, 1 Apr 2024 00:48:49 +0600 Subject: [PATCH 05/12] added and refactored unicode_regex_split and related functions --- llama.cpp | 113 +++++++----------------- unicode.cpp | 247 ++++++++++++++++++++++++++++++++++++++++++++++++---- unicode.h | 7 +- 3 files changed, 264 insertions(+), 103 deletions(-) diff --git a/llama.cpp b/llama.cpp index f66213c8c20e6..3c0cea817b186 100644 --- a/llama.cpp +++ b/llama.cpp @@ -11219,13 +11219,13 @@ struct llm_tokenizer_bpe { std::vector word_collection; switch (vocab.type) { case LLAMA_VOCAB_TYPE_BPE: - word_collection = bpe_gpt2_preprocess(text); + word_collection = unicode_regex_split(text, gpt2_regex); break; case LLAMA_VOCAB_TYPE_DEEPSEEKCODER: - word_collection = bpe_deepseek_coder_preprocess(text); + word_collection = unicode_regex_split(text, deepseek_coder_regex); break; case LLAMA_VOCAB_TYPE_DEEPSEEKLLM: - word_collection = bpe_deepseek_llm_preprocess(text); + word_collection = unicode_regex_split(text, deepseek_llm_regex); break; default: break; @@ -11356,90 +11356,41 @@ struct llm_tokenizer_bpe { work_queue.push(bigram); } - std::vector byte_encoding_process(const std::vector & bpe_words) { - std::vectorbpe_encoded_words; - for (auto word : bpe_words) { - std::string text_utf = ""; - 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) { - encoded_token += unicode_byte_to_utf8(c); - } - bpe_encoded_words.emplace_back(encoded_token); - } - return bpe_encoded_words; - } - - std::vector regex_preprocess(const std::wstring & text, const std::vector & offsets, const std::wstring & regex_expr) { - std::wregex expr(regex_expr); - std::vector bpe_words; // stroe the offset of each word - bpe_words.reserve(offsets.size()); // Reserve memory for the approximate size - size_t start = 0; - for (auto offset : offsets) { - std::wcregex_iterator it(text.data() + start, text.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_words.emplace_back(match.position() - start_idx); - } - bpe_words.emplace_back(match.length()); - start_idx = match.position() + match.length(); - ++it; - } - - if (start_idx < (int64_t) offset) { - bpe_words.emplace_back(offset - start_idx); - } - start += offset; - } - - return bpe_words; - } - - std::vector regex_bpe_preprocess(const std::string & text, const std::vector & regex_exprs) { - std::wstring wtext = from_utf8(text); - - std::vector bpe_offsets = {wtext.size()}; - - for(auto & regex_expr : regex_exprs) { - bpe_offsets = regex_preprocess(wtext, bpe_offsets, regex_expr); - } - - std::vector bpe_words; - bpe_words.reserve(bpe_offsets.size()); // Reserve memory for the approximate size - size_t start = 0; - for(size_t & offset : bpe_offsets){ - bpe_words.emplace_back(to_utf8(std::wstring(wtext, start, offset))); - start += offset; - } - - return byte_encoding_process(bpe_words); - } - - std::vector bpe_gpt2_preprocess(const std::string & text) { - return regex_bpe_preprocess(text, get_gpt2_regex()); - } - - std::vector bpe_deepseek_coder_preprocess(const std::string & text) { - return regex_bpe_preprocess(text, get_deepseek_coder_regex()); - } - - std::vector bpe_deepseek_llm_preprocess(const std::string & text) { - return regex_bpe_preprocess(text, get_deepseek_llm_regex()); - } - const llama_vocab & vocab; std::vector symbols; std::vector symbols_final; llm_bigram_bpe::queue work_queue; + + const std::vector gpt2_regex = { + // //punc: \{p} and ascii puncs + L"[\U00000021-\U0000002F\U0000003A-\U00000040\\\U0000005B-\U00000060\U0000007B-\U0000007E\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", + // //'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S) + L"'s|'t|'re|'ve|'m|'ll|'d| 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+ L"[0-9][0-9][0-9]" + }; + const std::vector deepseek_coder_regex = { + L"[\r\n]", + //\s?\p{L}+ + 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4C7\U00011580-\U000115AE\U000115D8-\U000115DB\U00011600-\U0001162F\U00011644-\U00011644\U00011680-\U000116AA\U000116B8-\U000116B8\U00011700-\U0001171A\U00011800-\U0001182B\U000118A0-\U000118DF\U000118FF-\U00011906\U00011909-\U00011909\U0001190C-\U00011913\U00011915-\U00011916\U00011918-\U0001192F\U0001193F-\U0001193F\U00011941-\U00011941\U000119A0-\U000119A7\U000119AA-\U000119D0\U000119E1-\U000119E1\U000119E3-\U000119E3\U00011A00-\U00011A00\U00011A0B-\U00011A32\U00011A3A-\U00011A3A\U00011A50-\U00011A50\U00011A5C-\U00011A89\U00011A9D-\U00011A9D\U00011AC0-\U00011AF8\U00011C00-\U00011C08\U00011C0A-\U00011C2E\U00011C40-\U00011C40\U00011C72-\U00011C8F\U00011D00-\U00011D06\U00011D08-\U00011D09\U00011D0B-\U00011D30\U00011D46-\U00011D46\U00011D60-\U00011D65\U00011D67-\U00011D68\U00011D6A-\U00011D89\U00011D98-\U00011D98\U00011EE0-\U00011EF2\U00011FB0-\U00011FB0\U00012000-\U00012399\U00012480-\U00012543\U00013000-\U0001342E\U00014400-\U00014646\U00016800-\U00016A38\U00016A40-\U00016A5E\U00016AD0-\U00016AED\U00016B00-\U00016B2F\U00016B40-\U00016B43\U00016B63-\U00016B77\U00016B7D-\U00016B8F\U00016E40-\U00016E7F\U00016F00-\U00016F4A\U00016F50-\U00016F50\U00016F93-\U00016F9F\U00016FE0-\U00016FE1\U00016FE3-\U00016FE3\U00017000-\U000187F7\U00018800-\U00018CD5\U00018D00-\U00018D08\U0001B000-\U0001B11E\U0001B150-\U0001B152\U0001B164-\U0001B167\U0001B170-\U0001B2FB\U0001BC00-\U0001BC6A\U0001BC70-\U0001BC7C\U0001BC80-\U0001BC88\U0001BC90-\U0001BC99\U0001D400-\U0001D454\U0001D456-\U0001D49C\U0001D49E-\U0001D49F\U0001D4A2-\U0001D4A2\U0001D4A5-\U0001D4A6\U0001D4A9-\U0001D4AC\U0001D4AE-\U0001D4B9\U0001D4BB-\U0001D4BB\U0001D4BD-\U0001D4C3\U0001D4C5-\U0001D505\U0001D507-\U0001D50A\U0001D50D-\U0001D514\U0001D516-\U0001D51C\U0001D51E-\U0001D539\U0001D53B-\U0001D53E\U0001D540-\U0001D544\U0001D546-\U0001D546\U0001D54A-\U0001D550\U0001D552-\U0001D6A5\U0001D6A8-\U0001D6C0\U0001D6C2-\U0001D6DA\U0001D6DC-\U0001D6FA\U0001D6FC-\U0001D714\U0001D716-\U0001D734\U0001D736-\U0001D74E\U0001D750-\U0001D76E\U0001D770-\U0001D788\U0001D78A-\U0001D7A8\U0001D7AA-\U0001D7C2\U0001D7C4-\U0001D7CB\U0001E100-\U0001E12C\U0001E137-\U0001E13D\U0001E14E-\U0001E14E\U0001E2C0-\U0001E2EB\U0001E800-\U0001E8C4\U0001E900-\U0001E943\U0001E94B-\U0001E94B\U0001EE00-\U0001EE03\U0001EE05-\U0001EE1F\U0001EE21-\U0001EE22\U0001EE24-\U0001EE24\U0001EE27-\U0001EE27\U0001EE29-\U0001EE32\U0001EE34-\U0001EE37\U0001EE39-\U0001EE39\U0001EE3B-\U0001EE3B\U0001EE42-\U0001EE42\U0001EE47-\U0001EE47\U0001EE49-\U0001EE49\U0001EE4B-\U0001EE4B\U0001EE4D-\U0001EE4F\U0001EE51-\U0001EE52\U0001EE54-\U0001EE54\U0001EE57-\U0001EE57\U0001EE59-\U0001EE59\U0001EE5B-\U0001EE5B\U0001EE5D-\U0001EE5D\U0001EE5F-\U0001EE5F\U0001EE61-\U0001EE62\U0001EE64-\U0001EE64\U0001EE67-\U0001EE6A\U0001EE6C-\U0001EE72\U0001EE74-\U0001EE77\U0001EE79-\U0001EE7C\U0001EE7E-\U0001EE7E\U0001EE80-\U0001EE89\U0001EE8B-\U0001EE9B\U0001EEA1-\U0001EEA3\U0001EEA5-\U0001EEA9\U0001EEAB-\U0001EEBB\U00020000-\U0002A6DD\U0002A700-\U0002B734\U0002B740-\U0002B81D\U0002B820-\U0002CEA1\U0002CEB0-\U0002EBE0\U0002F800-\U0002FA1D\U00030000-\U0003134A]+", + //\s?\p{P}+ + L"\\s?[\U00000021-\U00000023\U00000025-\\\U0000002A\U0000002C-\U0000002F\U0000003A-\U0000003B\\\U0000003F-\U00000040\\\U0000005B-\\\U0000005D\U0000005F-\U0000005F\U0000007B-\U0000007B\U0000007D-\U0000007D\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", + //cjk + L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", + //digits + L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" + }; + const std::vector deepseek_llm_regex = { + L"[\r\n]", + L"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", + L"\\s?[\u0021-\u002f\u003a-\u007e\uff01-\uff0f\uff1a-\uff5e\u2018-\u201f\u3000-\u3002]+", + L"\\s+$", + L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", + L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" + }; }; struct llm_tokenizer_wpm { diff --git a/unicode.cpp b/unicode.cpp index 0a2863ea004b7..5395bf128b55a 100644 --- a/unicode.cpp +++ b/unicode.cpp @@ -5,11 +5,14 @@ #include #include #include +#include #include #include #include #include #include +#include +#include static std::string unicode_cpts_to_utf8(const std::vector & cps) { std::string result; @@ -194,6 +197,207 @@ static std::unordered_map unicode_utf8_to_byte_map() { return map; } +static inline std::wstring unicode_wstring_from_utf8(const std::string & s) +{ + std::wstring_convert> conv; + return conv.from_bytes(s); +} + +static inline std::string unicode_wstring_to_utf8(const std::wstring & ws) +{ + // code to convert from utf32/utf16 to utf8 + std::wstring_convert, wchar_t> converter; + std::string utf8 = converter.to_bytes(ws); + return utf8; +} + +static std::vector unicode_byte_encoding_process(const std::vector & bpe_words) { + std::vectorbpe_encoded_words; + for (auto word : bpe_words) { + std::string text_utf = ""; + 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) { + encoded_token += unicode_byte_to_utf8(c); + } + bpe_encoded_words.emplace_back(encoded_token); + } + return bpe_encoded_words; +} + +static std::vector unicode_custom_preprocess(const std::string & text) { + std::vector bpe_words; + + std::string token = ""; + // GPT2 system regex: 's|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+ + bool collecting_numeric = false; + bool collecting_letter = false; + bool collecting_special = false; + bool collecting_whitespace_lookahead = false; + bool collecting = false; + + std::vector text_utf; + text_utf.reserve(text.size()); + bpe_words.reserve(text.size()); + + const auto cpts = unicode_cpts_from_utf8(text); + for (size_t i = 0; i < cpts.size(); ++i) + text_utf.emplace_back(unicode_cpt_to_utf8(cpts[i])); + + for (int i = 0; i < (int)text_utf.size(); i++) { + const std::string & utf_char = text_utf[i]; + bool split_condition = false; + int bytes_remain = text_utf.size() - i; + // forward backward lookups + const std::string & utf_char_next = (i + 1 < (int)text_utf.size()) ? text_utf[i + 1] : ""; + const std::string & utf_char_next_next = (i + 2 < (int)text_utf.size()) ? text_utf[i + 2] : ""; + + // handling contractions + if (!split_condition && bytes_remain >= 2) { + // 's|'t|'m|'d + if (utf_char == "\'" && (utf_char_next == "s" || utf_char_next == "t" || utf_char_next == "m" || utf_char_next == "d")) { + split_condition = true; + } + if (split_condition) { + if (token.size()) { + bpe_words.emplace_back(token); // push previous content as token + } + token = utf_char + utf_char_next; + bpe_words.emplace_back(token); + token = ""; + i++; + continue; + } + } + if (!split_condition && bytes_remain >= 3) { + // 're|'ve|'ll + if (utf_char == "\'" && ( + (utf_char_next == "r" && utf_char_next_next == "e") || + (utf_char_next == "v" && utf_char_next_next == "e") || + (utf_char_next == "l" && utf_char_next_next == "l")) + ) { + split_condition = true; + } + if (split_condition) { + // current token + next token can be defined + if (token.size()) { + bpe_words.emplace_back(token); // push previous content as token + } + token = utf_char + utf_char_next + utf_char_next_next; + bpe_words.emplace_back(token); // the contraction + token = ""; + i += 2; + continue; + } + } + + if (!split_condition && !collecting) { + if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) { + collecting_letter = true; + collecting = true; + } + else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) { + collecting_numeric = true; + collecting = true; + } + else if ( + ((unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) && (unicode_cpt_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) || + (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_DIGIT && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE) + ) { + collecting_special = true; + collecting = true; + } + else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) { + collecting_whitespace_lookahead = true; + collecting = true; + } + else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) { + split_condition = true; + } + } + else if (!split_condition && collecting) { + if (collecting_letter && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER) { + split_condition = true; + } + else if (collecting_numeric && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) { + split_condition = true; + } + else if (collecting_special && (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) { + split_condition = true; + } + else if (collecting_whitespace_lookahead && (unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) { + split_condition = true; + } + } + + if (utf_char_next == "") { + split_condition = true; // final + token += utf_char; + } + + if (split_condition) { + if (token.size()) { + bpe_words.emplace_back(token); + } + token = utf_char; + collecting = false; + collecting_letter = false; + collecting_numeric = false; + collecting_special = false; + collecting_whitespace_lookahead = false; + } + else { + token += utf_char; + } + } + + return bpe_words; +} + +static std::vector unicode_regex_preprocess(const std::wstring & text, const std::vector & offsets, const std::wstring & regex_expr) { + std::wregex expr(regex_expr); + std::vector bpe_offsets; // stroe 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(text.data() + start, text.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; +} + +static bool unicode_regex_matched(const std::wstring & text, const std::vector & regex_exprs) { + + for(auto & regex_expr: regex_exprs) { + std::wregex expr(regex_expr); + if(std::regex_match(text, expr)) { + return true; + } + } + + return false; +} + // // interface // @@ -275,6 +479,7 @@ char32_t unicode_tolower(char32_t cp) { auto it = unicode_map_lowercase.find(cp); return it == unicode_map_lowercase.end() ? cp : it->second; } + static const std::vector gpt2_regex = { // //punc: \{p} and ascii puncs L"[\U00000021-\U0000002F\U0000003A-\U00000040\\\U0000005B-\U00000060\U0000007B-\U0000007E\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", @@ -296,27 +501,31 @@ static const std::vector deepseek_coder_regex = { //digits L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" }; + +std::vector unicode_regex_split(const std::string & text, const std::vector & regex_exprs) { + std::wstring wtext = unicode_wstring_from_utf8(text); -static const std::vector deepseek_llm_regex = { - L"[\r\n]", - L"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", - L"\\s?[\u0021-\u002f\u003a-\u007e\uff01-\uff0f\uff1a-\uff5e\u2018-\u201f\u3000-\u3002]+", - L"\\s+$", - L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", - L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" - }; - -std::vector get_gpt2_regex() { - return gpt2_regex; -} - -std::vector get_deepseek_coder_regex() { - return deepseek_coder_regex; -} + std::vector bpe_offsets = {wtext.size()}; -std::vector get_deepseek_llm_regex() { - return deepseek_llm_regex; -} + for(auto & regex_expr : regex_exprs) { + bpe_offsets = unicode_regex_preprocess(wtext, bpe_offsets, regex_expr); + } + std::vector bpe_words; + bpe_words.reserve(bpe_offsets.size()); // Reserve memory for the approximate size + size_t start = 0; + for(size_t & offset : bpe_offsets){ + const auto temp_word = std::wstring(wtext, start, offset); + if(unicode_regex_matched(temp_word, regex_exprs)) { + bpe_words.emplace_back(unicode_wstring_to_utf8(temp_word)); + } else { + auto custom_bpe_words = unicode_custom_preprocess(unicode_wstring_to_utf8(temp_word)); + bpe_words.insert(bpe_words.end(), custom_bpe_words.begin(), custom_bpe_words.end()); + } + + start += offset; + } + return unicode_byte_encoding_process(bpe_words); +} \ No newline at end of file diff --git a/unicode.h b/unicode.h index cf2f8e976f8ee..dc74c40133f4b 100644 --- a/unicode.h +++ b/unicode.h @@ -1,10 +1,10 @@ #pragma once +#include #include +#include #include #include -#include -#include #define CODEPOINT_TYPE_UNIDENTIFIED 0 #define CODEPOINT_TYPE_DIGIT 1 @@ -44,4 +44,5 @@ inline std::string to_utf8(const std::wstring & ws) std::wstring_convert, wchar_t> converter; std::string utf8 = converter.to_bytes(ws); return utf8; -} \ No newline at end of file +} +std::vector unicode_regex_split(const std::string & text, const std::vector & regex_exprs); From 360849169fb1721b1e2e575c19004077d017be2e Mon Sep 17 00:00:00 2001 From: Jaggzh Date: Mon, 12 Feb 2024 04:18:06 -0800 Subject: [PATCH 06/12] Updated/merged the deepseek coder pr --- llama.cpp | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/llama.cpp b/llama.cpp index 3c0cea817b186..3d34b5b9c2434 100644 --- a/llama.cpp +++ b/llama.cpp @@ -4076,16 +4076,6 @@ static void llm_load_vocab( if (add_space_prefix_keyidx != -1) { vocab.add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx); } // The default value of add_space_prefix is true. - } else if (tokenizer_name == "bert") { - vocab.type = LLAMA_VOCAB_TYPE_WPM; - - // default special tokens - vocab.special_bos_id = 101; - vocab.special_eos_id = 102; - vocab.special_unk_id = 100; - vocab.special_sep_id = -1; - vocab.special_pad_id = -1; - vocab.add_space_prefix = false; } else { if (tokenizer_name == "gpt2") { vocab.type = LLAMA_VOCAB_TYPE_BPE; @@ -4093,6 +4083,16 @@ static void llm_load_vocab( vocab.type = LLAMA_VOCAB_TYPE_DEEPSEEKCODER; } else if (tokenizer_name == "deepseek_llm") { vocab.type = LLAMA_VOCAB_TYPE_DEEPSEEKLLM; + } else if (tokenizer_name == "bert") { + vocab.type = LLAMA_VOCAB_TYPE_WPM; + + // default special tokens + vocab.special_bos_id = 101; + vocab.special_eos_id = 102; + vocab.special_unk_id = 100; + vocab.special_sep_id = -1; + vocab.special_pad_id = -1; + vocab.add_space_prefix = false; } else { LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_name.c_str()); LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__); From e5dda78bf59c971f347101fd78f55a96e9cd432f Mon Sep 17 00:00:00 2001 From: Kazim Abrar Mahi Date: Sat, 13 Apr 2024 19:33:06 +0600 Subject: [PATCH 07/12] Refactored code --- convert-hf-to-gguf.py | 2 ++ models/ggml-vocab-deepseek-coder.gguf | Bin 1156012 -> 1157268 bytes 2 files changed, 2 insertions(+) diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 95a5d030b5c21..a701ac03336fb 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -1303,6 +1303,8 @@ def write_tensors(self): self.gguf_writer.add_tensor(new_name, data) @Model.register("LlamaForCausalLM") class DeepseekCoderModel(Model): + model_arch = gguf.MODEL_ARCH.LLAMA + def set_gguf_parameters(self): super().set_gguf_parameters() head_count = self.hparams["num_attention_heads"] diff --git a/models/ggml-vocab-deepseek-coder.gguf b/models/ggml-vocab-deepseek-coder.gguf index 2531e1e1914ef67ce1f0daaa1e07f0d74fac6509..640ee63d8742a9db73cd66673e74c7a6978870e9 100644 GIT binary patch delta 1345 zcmah|&1(}u6wfw^w)Lwyv=u4(w2iAY35Yi_;zvy>2!f~}Rl|1oZ8~-{v)!3(Nz)j? zLoXf-5fs5*y!PI^2R#e<2fTUqFYwJ~(=^r6f#0$-^FDs>z2EHoD1G=@%FNF{DJ2vA zHPy;IFs52BCz96+*IS`!oNaxXF>bfMWsTw1Z!`U7Jdrrpes5e%r^son{m#gx#^|s8 z$CxoL)5T=FW1PQ~i6d5!V_CwXbcgOgcKo7 zI7T>57~bs|Bi}#mzWzM2liVt8j}S%)CkQ7ArwFGBX9#1vrR~hGRC>ITNL*;I4o!T# z`!(~bIT_PaVg)(dz@T6+TdJ(E>U);LVY<#}rnKr=U@mZ>z;c{&w;sg=FZ+S0`U;o? z2VKU|fox-xtR)_1S_IefBto_s86tNma^#ecytsrSaI1>aw`{!PijX_S$mJ^JV>?#_ zKnBvPATZwhmC-%Ws%P_>Z)~z?2Es%01r&>5%9^ACO){nY+Ey=ZuNiY$i1HBw6@)kt zuS>MYfOeWhw5=}*S&o|6XvCRyr}lz%jm&2v1S>$WINVtPKWK_dU{$M(SHO~zNo8@B zgHSP#ZRkU_j4+4jOT-npCmf`j>FedF)obVppPIc?+iz0!Endq}0taf8OmMG88@W!N zt077~FbM(b;X0t20&E&ysOVbS47rU3C{a?}*$qh*oO2l-ZbF-n58OLas;~l&=>9BY6(0 Date: Mon, 15 Apr 2024 23:48:04 +0600 Subject: [PATCH 08/12] Adding unicode regex mappings --- unicode-data.cpp | 4 ++++ unicode-data.h | 2 ++ 2 files changed, 6 insertions(+) diff --git a/unicode-data.cpp b/unicode-data.cpp index 22f8b0f0b2928..30ea60f613470 100644 --- a/unicode-data.cpp +++ b/unicode-data.cpp @@ -1649,3 +1649,7 @@ const std::map unicode_map_lowercase = { {0x1E917, 0x1E939}, {0x1E918, 0x1E93A}, {0x1E919, 0x1E93B}, {0x1E91A, 0x1E93C}, {0x1E91B, 0x1E93D}, {0x1E91C, 0x1E93E}, {0x1E91D, 0x1E93F}, {0x1E91E, 0x1E940}, {0x1E91F, 0x1E941}, {0x1E920, 0x1E942}, {0x1E921, 0x1E943}, }; + +const std::map unicode_regex_to_wregex = { + +}; \ No newline at end of file diff --git a/unicode-data.h b/unicode-data.h index b99500b8f3a2a..46b774668a903 100644 --- a/unicode-data.h +++ b/unicode-data.h @@ -14,3 +14,5 @@ extern const std::vector> unicode_ranges_symbol; extern const std::vector> unicode_ranges_control; extern const std::multimap unicode_map_nfd; extern const std::map unicode_map_lowercase; +extern const std::map unicode_regex_to_wregex; +extern const std::map unicode_regex_to_regex; \ No newline at end of file From 0c991bebb4bb8e5c2dcc2884eaf3b0f2dca76b2e Mon Sep 17 00:00:00 2001 From: Kazim Abrar Mahi Date: Tue, 16 Apr 2024 01:52:33 +0600 Subject: [PATCH 09/12] Adding unicode regex function --- unicode-data.cpp | 12 +++++++++++- unicode-data.h | 3 +-- unicode.cpp | 24 +++--------------------- unicode.h | 18 +----------------- 4 files changed, 16 insertions(+), 41 deletions(-) diff --git a/unicode-data.cpp b/unicode-data.cpp index 30ea60f613470..004a16fbeb0a5 100644 --- a/unicode-data.cpp +++ b/unicode-data.cpp @@ -1651,5 +1651,15 @@ const std::map unicode_map_lowercase = { }; const std::map unicode_regex_to_wregex = { - + {"\\p{P}+", 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+ {"\\s?\\p{P}+", L"\\s?[\U00000021-\U00000023\U00000025-\U00000027\U0000002A\U0000002C-\U0000002F\U0000003A-\U0000003B\U0000003F-\U00000040\U0000005B-\U0000005D\U0000005F-\U0000005F\U0000007B-\U0000007B\U0000007D-\U0000007D\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+"}, + {"[一-龥ࠀ-一가-퟿]+", L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+"}, + {"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", L"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+"}, + {"\\s?[!-/:-~！-／：-～‘-‟　-。]+", L"\\s?[\u0021-\u002f\u003a-\u007e\uff01-\uff0f\uff1a-\uff5e\u2018-\u201f\u3000-\u3002]+"}, + {"\\s+$", L"\\s+$"} }; \ No newline at end of file diff --git a/unicode-data.h b/unicode-data.h index 46b774668a903..0cc7cf89504b1 100644 --- a/unicode-data.h +++ b/unicode-data.h @@ -14,5 +14,4 @@ extern const std::vector> unicode_ranges_symbol; extern const std::vector> unicode_ranges_control; extern const std::multimap unicode_map_nfd; extern const std::map unicode_map_lowercase; -extern const std::map unicode_regex_to_wregex; -extern const std::map unicode_regex_to_regex; \ No newline at end of file +extern const std::map unicode_regex_to_wregex; \ No newline at end of file diff --git a/unicode.cpp b/unicode.cpp index 5395bf128b55a..f25117b1e02e7 100644 --- a/unicode.cpp +++ b/unicode.cpp @@ -480,27 +480,9 @@ char32_t unicode_tolower(char32_t cp) { return it == unicode_map_lowercase.end() ? cp : it->second; } -static const std::vector gpt2_regex = { - // //punc: \{p} and ascii puncs - 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- // //'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S) - L"'s|'t|'re|'ve|'m|'ll|'d| 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- //\s?\p{P}+ - L"\\s?[\U00000021-\U00000023\U00000025-\\\U0000002A\U0000002C-\U0000002F\U0000003A-\U0000003B\\\U0000003F-\U00000040\\\U0000005B-\\\U0000005D\U0000005F-\U0000005F\U0000007B-\U0000007B\U0000007D-\U0000007D\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", - //cjk - L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", - //digits - L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" - }; +bool unicode_wregex_exists(const std::string & regex) { + return unicode_regex_to_wregex.find(regex) != unicode_regex_to_wregex.end(); +} std::vector unicode_regex_split(const std::string & text, const std::vector & regex_exprs) { std::wstring wtext = unicode_wstring_from_utf8(text); diff --git a/unicode.h b/unicode.h index dc74c40133f4b..dda0b5ba53dd7 100644 --- a/unicode.h +++ b/unicode.h @@ -28,21 +28,5 @@ uint8_t unicode_utf8_to_byte(const std::string & utf8); char32_t unicode_tolower(char32_t cp); -std::vector get_gpt2_regex(); -std::vector get_deepseek_coder_regex(); -std::vector get_deepseek_llm_regex(); - -inline std::wstring from_utf8(const std::string & s) -{ - std::wstring_convert> conv; - return conv.from_bytes(s); -} - -inline std::string to_utf8(const std::wstring & ws) -{ - // code to convert from utf32/utf16 to utf8 - std::wstring_convert, wchar_t> converter; - std::string utf8 = converter.to_bytes(ws); - return utf8; -} +bool unicode_wregex_exists(const std::string & regex); std::vector unicode_regex_split(const std::string & text, const std::vector & regex_exprs); From 6c80b3c5043e2dcbf2fcbc131efcaf6d903c7812 Mon Sep 17 00:00:00 2001 From: Kazim Abrar Mahi Date: Tue, 16 Apr 2024 04:56:35 +0600 Subject: [PATCH 10/12] Added needed functionality, testing remains --- llama.cpp | 53 ++++----- unicode-data.cpp | 6 +- unicode-data.h | 5 +- unicode.cpp | 281 ++++++++++++++++++++++++----------------------- unicode.h | 3 +- 5 files changed, 175 insertions(+), 173 deletions(-) diff --git a/llama.cpp b/llama.cpp index 3d34b5b9c2434..1988e46f31973 100644 --- a/llama.cpp +++ b/llama.cpp @@ -11219,13 +11219,31 @@ struct llm_tokenizer_bpe { std::vector word_collection; switch (vocab.type) { case LLAMA_VOCAB_TYPE_BPE: - word_collection = unicode_regex_split(text, gpt2_regex); + word_collection = unicode_regex_split(text, { + "\\p{P}+", + "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)", + "\\p{N}+", + "[0-9][0-9][0-9]" + }); break; case LLAMA_VOCAB_TYPE_DEEPSEEKCODER: - word_collection = unicode_regex_split(text, deepseek_coder_regex); + word_collection = unicode_regex_split(text, { + "[\r\n]", + "\\s?\\p{L}+", + "\\s?\\p{P}+", + "[一-龥ࠀ-一가-퟿]+", + "\\p{N}+" + }); break; case LLAMA_VOCAB_TYPE_DEEPSEEKLLM: - word_collection = unicode_regex_split(text, deepseek_llm_regex); + word_collection = unicode_regex_split(text, { + "[\r\n]", + "\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", + "\\s?[!-/:-~！-／：-～‘-‟　-。]+", + "\\s+$", + "[一-龥ࠀ-一가-퟿]+", + "\\p{N}+" + }); break; default: break; @@ -11362,35 +11380,6 @@ struct llm_tokenizer_bpe { std::vector symbols_final; llm_bigram_bpe::queue work_queue; - - const std::vector gpt2_regex = { - // //punc: \{p} and ascii puncs - 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- // //'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S) - L"'s|'t|'re|'ve|'m|'ll|'d| 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- //\s?\p{P}+ - L"\\s?[\U00000021-\U00000023\U00000025-\\\U0000002A\U0000002C-\U0000002F\U0000003A-\U0000003B\\\U0000003F-\U00000040\\\U0000005B-\\\U0000005D\U0000005F-\U0000005F\U0000007B-\U0000007B\U0000007D-\U0000007D\U000000A1-\U000000A1\U000000A7-\U000000A7\U000000AB-\U000000AB\U000000B6-\U000000B7\U000000BB-\U000000BB\U000000BF-\U000000BF\U0000037E-\U0000037E\U00000387-\U00000387\U0000055A-\U0000055F\U00000589-\U0000058A\U000005BE-\U000005BE\U000005C0-\U000005C0\U000005C3-\U000005C3\U000005C6-\U000005C6\U000005F3-\U000005F4\U00000609-\U0000060A\U0000060C-\U0000060D\U0000061B-\U0000061B\U0000061E-\U0000061F\U0000066A-\U0000066D\U000006D4-\U000006D4\U00000700-\U0000070D\U000007F7-\U000007F9\U00000830-\U0000083E\U0000085E-\U0000085E\U00000964-\U00000965\U00000970-\U00000970\U000009FD-\U000009FD\U00000A76-\U00000A76\U00000AF0-\U00000AF0\U00000C77-\U00000C77\U00000C84-\U00000C84\U00000DF4-\U00000DF4\U00000E4F-\U00000E4F\U00000E5A-\U00000E5B\U00000F04-\U00000F12\U00000F14-\U00000F14\U00000F3A-\U00000F3D\U00000F85-\U00000F85\U00000FD0-\U00000FD4\U00000FD9-\U00000FDA\U0000104A-\U0000104F\U000010FB-\U000010FB\U00001360-\U00001368\U00001400-\U00001400\U0000166E-\U0000166E\U0000169B-\U0000169C\U000016EB-\U000016ED\U00001735-\U00001736\U000017D4-\U000017D6\U000017D8-\U000017DA\U00001800-\U0000180A\U00001944-\U00001945\U00001A1E-\U00001A1F\U00001AA0-\U00001AA6\U00001AA8-\U00001AAD\U00001B5A-\U00001B60\U00001BFC-\U00001BFF\U00001C3B-\U00001C3F\U00001C7E-\U00001C7F\U00001CC0-\U00001CC7\U00001CD3-\U00001CD3\U00002010-\U00002027\U00002030-\U00002043\U00002045-\U00002051\U00002053-\U0000205E\U0000207D-\U0000207E\U0000208D-\U0000208E\U00002308-\U0000230B\U00002329-\U0000232A\U00002768-\U00002775\U000027C5-\U000027C6\U000027E6-\U000027EF\U00002983-\U00002998\U000029D8-\U000029DB\U000029FC-\U000029FD\U00002CF9-\U00002CFC\U00002CFE-\U00002CFF\U00002D70-\U00002D70\U00002E00-\U00002E2E\U00002E30-\U00002E4F\U00002E52-\U00002E52\U00003001-\U00003003\U00003008-\U00003011\U00003014-\U0000301F\U00003030-\U00003030\U0000303D-\U0000303D\U000030A0-\U000030A0\U000030FB-\U000030FB\U0000A4FE-\U0000A4FF\U0000A60D-\U0000A60F\U0000A673-\U0000A673\U0000A67E-\U0000A67E\U0000A6F2-\U0000A6F7\U0000A874-\U0000A877\U0000A8CE-\U0000A8CF\U0000A8F8-\U0000A8FA\U0000A8FC-\U0000A8FC\U0000A92E-\U0000A92F\U0000A95F-\U0000A95F\U0000A9C1-\U0000A9CD\U0000A9DE-\U0000A9DF\U0000AA5C-\U0000AA5F\U0000AADE-\U0000AADF\U0000AAF0-\U0000AAF1\U0000ABEB-\U0000ABEB\U0000FD3E-\U0000FD3F\U0000FE10-\U0000FE19\U0000FE30-\U0000FE52\U0000FE54-\U0000FE61\U0000FE63-\U0000FE63\U0000FE68-\U0000FE68\U0000FE6A-\U0000FE6B\U0000FF01-\U0000FF03\U0000FF05-\U0000FF0A\U0000FF0C-\U0000FF0F\U0000FF1A-\U0000FF1B\U0000FF1F-\U0000FF20\U0000FF3B-\U0000FF3D\U0000FF3F-\U0000FF3F\U0000FF5B-\U0000FF5B\U0000FF5D-\U0000FF5D\U0000FF5F-\U0000FF65\U00010100-\U00010102\U0001039F-\U0001039F\U000103D0-\U000103D0\U0001056F-\U0001056F\U00010857-\U00010857\U0001091F-\U0001091F\U0001093F-\U0001093F\U00010A50-\U00010A58\U00010A7F-\U00010A7F\U00010AF0-\U00010AF6\U00010B39-\U00010B3F\U00010B99-\U00010B9C\U00010EAD-\U00010EAD\U00010F55-\U00010F59\U00011047-\U0001104D\U000110BB-\U000110BC\U000110BE-\U000110C1\U00011140-\U00011143\U00011174-\U00011175\U000111C5-\U000111C8\U000111CD-\U000111CD\U000111DB-\U000111DB\U000111DD-\U000111DF\U00011238-\U0001123D\U000112A9-\U000112A9\U0001144B-\U0001144F\U0001145A-\U0001145B\U0001145D-\U0001145D\U000114C6-\U000114C6\U000115C1-\U000115D7\U00011641-\U00011643\U00011660-\U0001166C\U0001173C-\U0001173E\U0001183B-\U0001183B\U00011944-\U00011946\U000119E2-\U000119E2\U00011A3F-\U00011A46\U00011A9A-\U00011A9C\U00011A9E-\U00011AA2\U00011C41-\U00011C45\U00011C70-\U00011C71\U00011EF7-\U00011EF8\U00011FFF-\U00011FFF\U00012470-\U00012474\U00016A6E-\U00016A6F\U00016AF5-\U00016AF5\U00016B37-\U00016B3B\U00016B44-\U00016B44\U00016E97-\U00016E9A\U00016FE2-\U00016FE2\U0001BC9F-\U0001BC9F\U0001DA87-\U0001DA8B\U0001E95E-\U0001E95F]+", - //cjk - L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", - //digits - L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" - }; - const std::vector deepseek_llm_regex = { - L"[\r\n]", - L"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", - L"\\s?[\u0021-\u002f\u003a-\u007e\uff01-\uff0f\uff1a-\uff5e\u2018-\u201f\u3000-\u3002]+", - L"\\s+$", - L"[\u4e00-\u9fa5\u0800-\u4e00\uac00-\ud7ff]+", - L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]" - }; }; struct llm_tokenizer_wpm { diff --git a/unicode-data.cpp b/unicode-data.cpp index 004a16fbeb0a5..17ba8f3d1e894 100644 --- a/unicode-data.cpp +++ b/unicode-data.cpp @@ -1650,7 +1650,7 @@ const std::map unicode_map_lowercase = { {0x1E91D, 0x1E93F}, {0x1E91E, 0x1E940}, {0x1E91F, 0x1E941}, {0x1E920, 0x1E942}, {0x1E921, 0x1E943}, }; -const std::map unicode_regex_to_wregex = { +const std::map unicode_regex_equivalent_wregex = { {"\\p{P}+", 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{"\\p{N}+", L"[\U00000030-\U00000039\U000000B2-\U000000B3\U000000B9-\U000000B9\U00000660-\U00000669\U000006F0-\U000006F9\U000007C0-\U000007C9\U00000966-\U0000096F\U000009E6-\U000009EF\U00000A66-\U00000A6F\U00000AE6-\U00000AEF\U00000B66-\U00000B6F\U00000BE6-\U00000BEF\U00000C66-\U00000C6F\U00000CE6-\U00000CEF\U00000D66-\U00000D6F\U00000DE6-\U00000DEF\U00000E50-\U00000E59\U00000ED0-\U00000ED9\U00000F20-\U00000F29\U00001040-\U00001049\U00001090-\U00001099\U00001369-\U00001371\U000017E0-\U000017E9\U00001810-\U00001819\U00001946-\U0000194F\U000019D0-\U000019DA\U00001A80-\U00001A89\U00001A90-\U00001A99\U00001B50-\U00001B59\U00001BB0-\U00001BB9\U00001C40-\U00001C49\U00001C50-\U00001C59\U00002070-\U00002070\U00002074-\U00002079\U00002080-\U00002089\U00002460-\U00002468\U00002474-\U0000247C\U00002488-\U00002490\U000024EA-\U000024EA\U000024F5-\U000024FD\U000024FF-\U000024FF\U00002776-\U0000277E\U00002780-\U00002788\U0000278A-\U00002792\U0000A620-\U0000A629\U0000A8D0-\U0000A8D9\U0000A900-\U0000A909\U0000A9D0-\U0000A9D9\U0000A9F0-\U0000A9F9\U0000AA50-\U0000AA59\U0000ABF0-\U0000ABF9\U0000FF10-\U0000FF19\U000104A0-\U000104A9\U00010A40-\U00010A43\U00010D30-\U00010D39\U00010E60-\U00010E68\U00011052-\U0001105A\U00011066-\U0001106F\U000110F0-\U000110F9\U00011136-\U0001113F\U000111D0-\U000111D9\U000112F0-\U000112F9\U00011450-\U00011459\U000114D0-\U000114D9\U00011650-\U00011659\U000116C0-\U000116C9\U00011730-\U00011739\U000118E0-\U000118E9\U00011950-\U00011959\U00011C50-\U00011C59\U00011D50-\U00011D59\U00011DA0-\U00011DA9\U00016A60-\U00016A69\U00016B50-\U00016B59\U0001D7CE-\U0001D7FF\U0001E140-\U0001E149\U0001E2F0-\U0001E2F9\U0001E950-\U0001E959\U0001F100-\U0001F10A\U0001FBF0-\U0001FBF9]+"}, @@ -1662,4 +1662,8 @@ const std::map unicode_regex_to_wregex = { {"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+", L"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+"}, {"\\s?[!-/:-~！-／：-～‘-‟　-。]+", L"\\s?[\u0021-\u002f\u003a-\u007e\uff01-\uff0f\uff1a-\uff5e\u2018-\u201f\u3000-\u3002]+"}, {"\\s+$", L"\\s+$"} +}; + +const std::set unicode_regex_with_custom_preprocessor = { + "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)" }; \ No newline at end of file diff --git a/unicode-data.h b/unicode-data.h index 0cc7cf89504b1..e19cef0bfe695 100644 --- a/unicode-data.h +++ b/unicode-data.h @@ -2,6 +2,8 @@ #include #include +#include +#include #include #include @@ -14,4 +16,5 @@ extern const std::vector> unicode_ranges_symbol; extern const std::vector> unicode_ranges_control; extern const std::multimap unicode_map_nfd; extern const std::map unicode_map_lowercase; -extern const std::map unicode_regex_to_wregex; \ No newline at end of file +extern const std::map unicode_regex_equivalent_wregex; +extern const std::set unicode_regex_with_custom_preprocessor; \ No newline at end of file diff --git a/unicode.cpp b/unicode.cpp index f25117b1e02e7..0394f485fcf09 100644 --- a/unicode.cpp +++ b/unicode.cpp @@ -228,133 +228,138 @@ static std::vector unicode_byte_encoding_process(const std::vector< return bpe_encoded_words; } -static std::vector unicode_custom_preprocess(const std::string & text) { - std::vector bpe_words; +static std::vector unicode_gpt2_regex_preprocess(const std::wstring & wtext, const std::vector & offsets) { + std::vector bpe_offsets; // stroe the offset of each word + bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size + size_t start = 0; - std::string token = ""; - // GPT2 system regex: 's|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+ - bool collecting_numeric = false; - bool collecting_letter = false; - bool collecting_special = false; - bool collecting_whitespace_lookahead = false; - bool collecting = false; - - std::vector text_utf; - text_utf.reserve(text.size()); - bpe_words.reserve(text.size()); - - const auto cpts = unicode_cpts_from_utf8(text); - for (size_t i = 0; i < cpts.size(); ++i) - text_utf.emplace_back(unicode_cpt_to_utf8(cpts[i])); - - for (int i = 0; i < (int)text_utf.size(); i++) { - const std::string & utf_char = text_utf[i]; - bool split_condition = false; - int bytes_remain = text_utf.size() - i; - // forward backward lookups - const std::string & utf_char_next = (i + 1 < (int)text_utf.size()) ? text_utf[i + 1] : ""; - const std::string & utf_char_next_next = (i + 2 < (int)text_utf.size()) ? text_utf[i + 2] : ""; - - // handling contractions - if (!split_condition && bytes_remain >= 2) { - // 's|'t|'m|'d - if (utf_char == "\'" && (utf_char_next == "s" || utf_char_next == "t" || utf_char_next == "m" || utf_char_next == "d")) { - split_condition = true; - } - if (split_condition) { - if (token.size()) { - bpe_words.emplace_back(token); // push previous content as token + for(auto offset : offsets) { + const std::string text = unicode_wstring_to_utf8(std::wstring(wtext, start, offset)); + + std::string token = ""; + // GPT2 system regex: 's|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+ + bool collecting_numeric = false; + bool collecting_letter = false; + bool collecting_special = false; + bool collecting_whitespace_lookahead = false; + bool collecting = false; + + std::vector text_utf; + text_utf.reserve(text.size()); + + const auto cpts = unicode_cpts_from_utf8(text); + for (size_t i = 0; i < cpts.size(); ++i) + text_utf.emplace_back(unicode_cpt_to_utf8(cpts[i])); + + for (int i = 0; i < (int)text_utf.size(); i++) { + const std::string & utf_char = text_utf[i]; + bool split_condition = false; + int bytes_remain = text_utf.size() - i; + // forward backward lookups + const std::string & utf_char_next = (i + 1 < (int)text_utf.size()) ? text_utf[i + 1] : ""; + const std::string & utf_char_next_next = (i + 2 < (int)text_utf.size()) ? text_utf[i + 2] : ""; + + // handling contractions + if (!split_condition && bytes_remain >= 2) { + // 's|'t|'m|'d + if (utf_char == "\'" && (utf_char_next == "s" || utf_char_next == "t" || utf_char_next == "m" || utf_char_next == "d")) { + split_condition = true; + } + if (split_condition) { + if (token.size()) { + bpe_offsets.emplace_back(unicode_wstring_from_utf8(token).size()); + } + token = utf_char + utf_char_next; + bpe_offsets.emplace_back(unicode_wstring_from_utf8(token).size()); + token = ""; + i++; + continue; } - token = utf_char + utf_char_next; - bpe_words.emplace_back(token); - token = ""; - i++; - continue; - } - } - if (!split_condition && bytes_remain >= 3) { - // 're|'ve|'ll - if (utf_char == "\'" && ( - (utf_char_next == "r" && utf_char_next_next == "e") || - (utf_char_next == "v" && utf_char_next_next == "e") || - (utf_char_next == "l" && utf_char_next_next == "l")) - ) { - split_condition = true; } - if (split_condition) { - // current token + next token can be defined - if (token.size()) { - bpe_words.emplace_back(token); // push previous content as token + if (!split_condition && bytes_remain >= 3) { + // 're|'ve|'ll + if (utf_char == "\'" && ( + (utf_char_next == "r" && utf_char_next_next == "e") || + (utf_char_next == "v" && utf_char_next_next == "e") || + (utf_char_next == "l" && utf_char_next_next == "l")) + ) { + split_condition = true; + } + if (split_condition) { + // current token + next token can be defined + if (token.size()) { + bpe_offsets.emplace_back(unicode_wstring_from_utf8(token).size()); + } + token = utf_char + utf_char_next + utf_char_next_next; + bpe_offsets.emplace_back(unicode_wstring_from_utf8(token).size()); + token = ""; + i += 2; + continue; } - token = utf_char + utf_char_next + utf_char_next_next; - bpe_words.emplace_back(token); // the contraction - token = ""; - i += 2; - continue; } - } - if (!split_condition && !collecting) { - if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) { - collecting_letter = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) { - collecting_numeric = true; - collecting = true; - } - else if ( - ((unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) && (unicode_cpt_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) || - (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_DIGIT && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE) - ) { - collecting_special = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) { - collecting_whitespace_lookahead = true; - collecting = true; - } - else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) { - split_condition = true; - } - } - else if (!split_condition && collecting) { - if (collecting_letter && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER) { - split_condition = true; - } - else if (collecting_numeric && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) { - split_condition = true; - } - else if (collecting_special && (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) { - split_condition = true; + if (!split_condition && !collecting) { + if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) { + collecting_letter = true; + collecting = true; + } + else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) { + collecting_numeric = true; + collecting = true; + } + else if ( + ((unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) && (unicode_cpt_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) || + (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_DIGIT && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE) + ) { + collecting_special = true; + collecting = true; + } + else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) { + collecting_whitespace_lookahead = true; + collecting = true; + } + else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) { + split_condition = true; + } } - else if (collecting_whitespace_lookahead && (unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) { - split_condition = true; + else if (!split_condition && collecting) { + if (collecting_letter && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER) { + split_condition = true; + } + else if (collecting_numeric && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) { + split_condition = true; + } + else if (collecting_special && (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) { + split_condition = true; + } + else if (collecting_whitespace_lookahead && (unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) { + split_condition = true; + } } - } - if (utf_char_next == "") { - split_condition = true; // final - token += utf_char; - } + if (utf_char_next == "") { + split_condition = true; // final + token += utf_char; + } - if (split_condition) { - if (token.size()) { - bpe_words.emplace_back(token); + if (split_condition) { + if (token.size()) { + bpe_offsets.emplace_back(unicode_wstring_from_utf8(token).size()); + } + token = utf_char; + collecting = false; + collecting_letter = false; + collecting_numeric = false; + collecting_special = false; + collecting_whitespace_lookahead = false; + } + else { + token += utf_char; } - token = utf_char; - collecting = false; - collecting_letter = false; - collecting_numeric = false; - collecting_special = false; - collecting_whitespace_lookahead = false; - } - else { - token += utf_char; } } - return bpe_words; + return bpe_offsets; } static std::vector unicode_regex_preprocess(const std::wstring & text, const std::vector & offsets, const std::wstring & regex_expr) { @@ -386,16 +391,22 @@ static std::vector unicode_regex_preprocess(const std::wstring & text, c return bpe_offsets; } -static bool unicode_regex_matched(const std::wstring & text, const std::vector & regex_exprs) { +static bool unicode_regex_equivalent_wregex_exists(const std::string & regex) { + return unicode_regex_equivalent_wregex.find(regex) != unicode_regex_equivalent_wregex.end(); +} - for(auto & regex_expr: regex_exprs) { - std::wregex expr(regex_expr); - if(std::regex_match(text, expr)) { - return true; - } +static bool unicode_regex_with_custom_preprocessor_exists(const std::string & regex) { + return unicode_regex_with_custom_preprocessor.find(regex) != unicode_regex_with_custom_preprocessor.end(); +} + +static std::vector unicode_regex_custom_preprocess(const std::string & regex, const std::wstring & wtext, const std::vector & offsets) { + std::vector bpe_offsets; + + if(regex == "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)") { + bpe_offsets = unicode_gpt2_regex_preprocess(wtext, offsets); } - return false; + return bpe_offsets; } // @@ -479,33 +490,29 @@ char32_t unicode_tolower(char32_t cp) { auto it = unicode_map_lowercase.find(cp); return it == unicode_map_lowercase.end() ? cp : it->second; } - -bool unicode_wregex_exists(const std::string & regex) { - return unicode_regex_to_wregex.find(regex) != unicode_regex_to_wregex.end(); -} - -std::vector unicode_regex_split(const std::string & text, const std::vector & regex_exprs) { + +std::vector unicode_regex_split(const std::string & text, const std::vector & regex_exprs) { std::wstring wtext = unicode_wstring_from_utf8(text); std::vector bpe_offsets = {wtext.size()}; for(auto & regex_expr : regex_exprs) { - bpe_offsets = unicode_regex_preprocess(wtext, bpe_offsets, regex_expr); + + if (unicode_regex_equivalent_wregex_exists(regex_expr)) { + const std::wstring& wregex_expr = unicode_regex_equivalent_wregex.at(regex_expr); + bpe_offsets = unicode_regex_preprocess(wtext, bpe_offsets, wregex_expr); + } else if (unicode_regex_with_custom_preprocessor_exists(regex_expr)) { + bpe_offsets = unicode_regex_custom_preprocess(regex_expr, wtext, bpe_offsets); + } else { + throw std::runtime_error("Unicode regex is not found"); + } } std::vector bpe_words; bpe_words.reserve(bpe_offsets.size()); // Reserve memory for the approximate size size_t start = 0; - for(size_t & offset : bpe_offsets){ - const auto temp_word = std::wstring(wtext, start, offset); - - if(unicode_regex_matched(temp_word, regex_exprs)) { - bpe_words.emplace_back(unicode_wstring_to_utf8(temp_word)); - } else { - auto custom_bpe_words = unicode_custom_preprocess(unicode_wstring_to_utf8(temp_word)); - bpe_words.insert(bpe_words.end(), custom_bpe_words.begin(), custom_bpe_words.end()); - } - + for(size_t & offset : bpe_offsets) { + bpe_words.emplace_back(unicode_wstring_to_utf8(std::wstring(wtext, start, offset))); start += offset; } diff --git a/unicode.h b/unicode.h index dda0b5ba53dd7..3c9e6f8cf1536 100644 --- a/unicode.h +++ b/unicode.h @@ -28,5 +28,4 @@ uint8_t unicode_utf8_to_byte(const std::string & utf8); char32_t unicode_tolower(char32_t cp); -bool unicode_wregex_exists(const std::string & regex); -std::vector unicode_regex_split(const std::string & text, const std::vector & regex_exprs); +std::vector unicode_regex_split(const std::string & text, const std::vector & regex_exprs); From cc8d52921cd0d6f565250d95e348c3d3fe57851c Mon Sep 17 00:00:00 2001 From: Kazim Abrar Mahi Date: Tue, 16 Apr 2024 05:53:29 +0600 Subject: [PATCH 11/12] Fixed issues --- llama.cpp | 36 ++++++++++++++++++++---------------- unicode-data.cpp | 4 ++-- 2 files changed, 22 insertions(+), 18 deletions(-) diff --git a/llama.cpp b/llama.cpp index 1988e46f31973..719414ad230f1 100644 --- a/llama.cpp +++ b/llama.cpp @@ -4076,6 +4076,18 @@ static void llm_load_vocab( if (add_space_prefix_keyidx != -1) { vocab.add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx); } // The default value of add_space_prefix is true. + } else if (tokenizer_name == "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; + vocab.add_space_prefix = false; } else { if (tokenizer_name == "gpt2") { vocab.type = LLAMA_VOCAB_TYPE_BPE; @@ -4083,17 +4095,7 @@ static void llm_load_vocab( vocab.type = LLAMA_VOCAB_TYPE_DEEPSEEKCODER; } else if (tokenizer_name == "deepseek_llm") { vocab.type = LLAMA_VOCAB_TYPE_DEEPSEEKLLM; - } else if (tokenizer_name == "bert") { - vocab.type = LLAMA_VOCAB_TYPE_WPM; - - // default special tokens - vocab.special_bos_id = 101; - vocab.special_eos_id = 102; - vocab.special_unk_id = 100; - vocab.special_sep_id = -1; - vocab.special_pad_id = -1; - vocab.add_space_prefix = false; - } else { + } else { LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_name.c_str()); LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__); vocab.type = LLAMA_VOCAB_TYPE_SPM; @@ -4125,11 +4127,13 @@ static void llm_load_vocab( } // default special tokens - 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_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; } } diff --git a/unicode-data.cpp b/unicode-data.cpp index 17ba8f3d1e894..01a3aa1734b0c 100644 --- a/unicode-data.cpp +++ b/unicode-data.cpp @@ -1651,13 +1651,13 @@ const std::map unicode_map_lowercase = { }; const std::map unicode_regex_equivalent_wregex = { - {"\\p{P}+", 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+ {"\\p{P}+", 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a/unicode.cpp +++ b/unicode.cpp @@ -357,6 +357,7 @@ static std::vector unicode_gpt2_regex_preprocess(const std::wstring & wt token += utf_char; } } + start += offset; } return bpe_offsets;