update for deepseek-llm
This commit is contained in:
Bingxuan Wang
parent
87fe183d4d
commit
cb33629441
8 changed files with 321 additions and 14 deletions
7
Makefile
7
Makefile
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@ -8,7 +8,7 @@ BUILD_TARGETS = \
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TEST_TARGETS = \
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tests/test-llama-grammar tests/test-grammar-parser tests/test-double-float tests/test-grad0 tests/test-opt \
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tests/test-quantize-fns tests/test-quantize-perf tests/test-sampling tests/test-tokenizer-0-llama \
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tests/test-tokenizer-0-falcon tests/test-tokenizer-0-deepseek_coder \
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tests/test-tokenizer-0-falcon tests/test-tokenizer-0-deepseek_coder tests/test-tokenizer-0-deepseek_llm \
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tests/test-tokenizer-1-llama tests/test-tokenizer-1-bpe
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# Code coverage output files
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@ -72,6 +72,8 @@ test: $(TEST_TARGETS)
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./$$test_target $(CURDIR)/models/ggml-vocab-falcon.gguf; \
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elif [ "$$test_target" = "tests/test-tokenizer-0-deepseek_coder" ]; then \
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./$$test_target $(CURDIR)/models/ggml-vocab-deepseek-coder.gguf; \
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elif [ "$$test_target" = "tests/test-tokenizer-0-deepseek_llm" ]; then \
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./$$test_target $(CURDIR)/models/ggml-vocab-deepseek-llm.gguf $(CURDIR)/README.md; \
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elif [ "$$test_target" = "tests/test-tokenizer-1-llama" ]; then \
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continue; \
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elif [ "$$test_target" = "tests/test-tokenizer-1-bpe" ]; then \
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@ -734,6 +736,9 @@ tests/test-tokenizer-0-llama: tests/test-tokenizer-0-llama.cpp ggml.o llama.o $(
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tests/test-tokenizer-0-deepseek_coder: tests/test-tokenizer-0-deepseek_coder.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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tests/test-tokenizer-0-deepseek_llm: tests/test-tokenizer-0-deepseek_llm.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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tests/test-tokenizer-1-bpe: tests/test-tokenizer-1-bpe.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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@ -195,6 +195,8 @@ class Model:
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return PersimmonModel
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if model_name_lower == "deepseekcoder":
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return DeepseekCoderModel
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if model_name_lower == "deepseekllm":
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return DeepseekLLMModel
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return Model
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def _is_model_safetensors(self) -> bool:
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@ -865,6 +867,9 @@ class DeepseekCoderModel(Model):
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def set_vocab(self):
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self._set_vocab_gpt2("deepseek_coder")
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class DeepseekLLMModel(DeepseekCoderModel):
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def set_vocab(self):
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self._set_vocab_gpt2("deepseek_llm")
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class StableLMModel(Model):
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def set_gguf_parameters(self):
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42
llama.cpp
42
llama.cpp
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@ -2385,14 +2385,19 @@ static void llm_load_vocab(
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vocab.special_unk_id = 0;
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vocab.special_sep_id = -1;
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vocab.special_pad_id = -1;
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} else if (tokenizer_name == "gpt2" || tokenizer_name == "deepseek_coder") {
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if(tokenizer_name == "gpt2") {
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} else {
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if (tokenizer_name == "gpt2") {
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vocab.type = LLAMA_VOCAB_TYPE_BPE;
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}
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else if (tokenizer_name == "deepseek_coder") {
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} else if (tokenizer_name == "deepseek_coder") {
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vocab.type = LLAMA_VOCAB_TYPE_DEEPSEEKCODER;
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} else if (tokenizer_name == "deepseek_llm") {
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vocab.type = LLAMA_VOCAB_TYPE_DEEPSEEKLLM;
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} else {
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LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_name.c_str());
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LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__);
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vocab.type = LLAMA_VOCAB_TYPE_SPM;
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return;
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}
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// read bpe merges and populate bpe ranks
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const int merges_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_MERGES).c_str());
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if (merges_keyidx == -1) {
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@ -2424,11 +2429,6 @@ static void llm_load_vocab(
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vocab.special_unk_id = -1;
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vocab.special_sep_id = -1;
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vocab.special_pad_id = -1;
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} else {
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LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_name.c_str());
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LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__);
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vocab.type = LLAMA_VOCAB_TYPE_SPM;
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}
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}
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@ -2605,7 +2605,7 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
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// hparams
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LLAMA_LOG_INFO("%s: format = %s\n", __func__, llama_file_version_name(ml.fver));
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LLAMA_LOG_INFO("%s: arch = %s\n", __func__, LLM_ARCH_NAMES.at(model.arch).c_str());
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LLAMA_LOG_INFO("%s: vocab type = %s\n", __func__, vocab.type == LLAMA_VOCAB_TYPE_SPM ? "SPM" : (vocab.type == LLAMA_VOCAB_TYPE_BPE ? "BPE" : "DEEPSEEKCODER")); // TODO: fix
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LLAMA_LOG_INFO("%s: vocab type = %s\n", __func__, vocab.type == LLAMA_VOCAB_TYPE_SPM ? "SPM" : "BPE"); // TODO: fix
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LLAMA_LOG_INFO("%s: n_vocab = %u\n", __func__, hparams.n_vocab);
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LLAMA_LOG_INFO("%s: n_merges = %u\n", __func__, (int) vocab.bpe_ranks.size());
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LLAMA_LOG_INFO("%s: n_ctx_train = %u\n", __func__, hparams.n_ctx_train);
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@ -5956,10 +5956,20 @@ struct llm_tokenizer_bpe {
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void tokenize(const std::string & text, std::vector<llama_vocab::id> & output) {
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int final_prev_index = -1;
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std::vector<std::string> word_collection;
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if(vocab.type == LLAMA_VOCAB_TYPE_BPE)
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switch (vocab.type)
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{
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case LLAMA_VOCAB_TYPE_BPE:
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word_collection = bpe_gpt2_preprocess(text);
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else if(vocab.type==LLAMA_VOCAB_TYPE_DEEPSEEKCODER)
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break;
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case LLAMA_VOCAB_TYPE_DEEPSEEKCODER:
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word_collection = bpe_deepseek_coder_preprocess(text);
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break;
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case LLAMA_VOCAB_TYPE_DEEPSEEKLLM:
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word_collection = bpe_deepseek_llm_preprocess(text);
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break;
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default:
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break;
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}
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symbols_final.clear();
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@ -6159,6 +6169,10 @@ private:
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return regex_bpe_preprocess(text, deepseek_coder_regex);
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}
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std::vector<std::string> bpe_deepseek_llm_preprocess(const std::string & text) {
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return regex_bpe_preprocess(text, deepseek_llm_regex);
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}
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const llama_vocab & vocab;
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std::vector<llm_symbol> symbols;
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@ -6350,6 +6364,7 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
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}
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} break;
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case LLAMA_VOCAB_TYPE_DEEPSEEKCODER:
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case LLAMA_VOCAB_TYPE_DEEPSEEKLLM:
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case LLAMA_VOCAB_TYPE_BPE:
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{
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for (const auto & fragment: fragment_buffer)
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@ -9467,6 +9482,7 @@ int llama_token_to_piece(const struct llama_model * model, llama_token token, ch
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break;
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}
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case LLAMA_VOCAB_TYPE_DEEPSEEKCODER:
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case LLAMA_VOCAB_TYPE_DEEPSEEKLLM:
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case LLAMA_VOCAB_TYPE_BPE: {
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if (llama_is_normal_token(model->vocab, token)) {
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std::string result = model->vocab.id_to_token[token].text;
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1
llama.h
1
llama.h
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@ -70,6 +70,7 @@ extern "C" {
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LLAMA_VOCAB_TYPE_SPM = 0, // SentencePiece
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LLAMA_VOCAB_TYPE_BPE = 1, // Byte Pair Encoding
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LLAMA_VOCAB_TYPE_DEEPSEEKCODER = 2, // deepseek coder
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LLAMA_VOCAB_TYPE_DEEPSEEKLLM = 3, // deepseek coder
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};
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enum llama_token_type {
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BIN
models/ggml-vocab-deepseek-llm.gguf
Normal file
BIN
models/ggml-vocab-deepseek-llm.gguf
Normal file
Binary file not shown.
188
tests/test-tokenizer-0-deepseek_llm.cpp
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188
tests/test-tokenizer-0-deepseek_llm.cpp
Normal file
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@ -0,0 +1,188 @@
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#include "llama.h"
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#include "common.h"
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#include "console.h"
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#include <cstdio>
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#include <string>
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#include <map>
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#include <vector>
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#include <fstream>
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// generate using test-tokenizer-0-falcon.py
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static const std::map<std::string, std::vector<llama_token>> & k_tests() {
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static std::map<std::string, std::vector<llama_token>> _k_tests = {
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{ "" , { }, },
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{ " " , { 207, }, },
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{ " " , { 243, }, },
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{ " " , { 300, }, },
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{ "\t" , { 184, }, },
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{ "\n" , { 185, }, },
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{ "\t\n" , { 184, 185, }, },
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{ "Hello world" , { 17464, 1843, }, },
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{ " Hello world" , { 37727, 1843, }, },
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{ "Hello World" , { 17464, 5427, }, },
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{ " Hello World" , { 37727, 5427, }, },
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{ " Hello World!" , { 37727, 5427, 0, }, },
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{ "Hello, world!" , { 17464, 11, 1843, 0, }, },
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{ " Hello, world!" , { 37727, 11, 1843, 0, }, },
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{ " this is 🦙.cpp" , { 437, 317, 12356, 99, 234, 13, 14743, }, },
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{ "w048 7tuijk dsdfhu" , { 86, 15, 19, 23, 207, 22, 83, 3970, 27519, 26016, 3944, 14025, }, },
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{ "нещо на Български" , { 1603, 6476, 620, 91754, }, },
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{ "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, }, },
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{ "🚀 (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, }, },
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{ "Hello" , { 17464, }, },
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{ " Hello" , { 37727, }, },
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{ " Hello" , { 207, 37727, }, },
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{ " Hello" , { 243, 37727, }, },
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{ " Hello" , { 300, 37727, }, },
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{ " Hello\n Hello" , { 300, 37727, 185, 300, 37727, }, },
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{ "\n =" , { 185, 403, }, },
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{ "' era" , { 6, 2906, }, },
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{ "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, }, },
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};
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return _k_tests;
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}
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int main(int argc, char **argv) {
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if (argc < 2) {
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fprintf(stderr, "Usage: %s vocab-file [text-file]\n", argv[0]);
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return 1;
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}
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const std::string fname = argv[1];
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std::string fname_text;
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if (argc > 2) {
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fname_text = argv[2];
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}
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fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str());
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llama_model * model;
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llama_context * ctx;
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llama_backend_init(false);
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// load the vocab
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{
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auto mparams = llama_model_default_params();
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mparams.vocab_only = true;
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model = llama_load_model_from_file(fname.c_str(), mparams);
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if (model == NULL) {
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fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
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return 1;
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}
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auto cparams = llama_context_default_params();
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ctx = llama_new_context_with_model(model, cparams);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
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llama_free_model(model);
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return 1;
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}
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}
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if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_DEEPSEEKLLM) {
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fprintf(stderr, "%s : error: vocab type is not DEEPSEEKLLM\n", __func__);
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llama_free_model(model);
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llama_free(ctx);
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return 2;
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}
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#ifdef _WIN32
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// We need this for unicode console support
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console::init(false, false);
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atexit([]() { console::cleanup(); });
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#endif
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bool success = true;
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for (const auto & test_kv : k_tests()) {
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const std::vector<llama_token> res = llama_tokenize(ctx, test_kv.first, false);
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printf("\n");
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printf("src: '%s'\n", test_kv.first.c_str());
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printf("res: '%s'\n", llama_detokenize_bpe(ctx, res).c_str());
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printf("tok: ");
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for (const auto & tok : res) {
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printf("%d ", tok);
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}
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printf("\n");
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bool correct = res.size() == test_kv.second.size();
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for (int i = 0; i < (int) res.size() && correct; ++i) {
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if (test_kv.second[i] != res[i]) {
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correct = false;
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}
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}
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if (!correct) {
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fprintf(stderr, "%s : failed test: '%s'\n", __func__, test_kv.first.c_str());
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fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__,
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llama_detokenize_bpe(ctx, res).c_str(),
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llama_detokenize_bpe(ctx, test_kv.second).c_str());
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fprintf(stderr, "%s : expected tokens: ", __func__);
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for (const auto & t : test_kv.second) {
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fprintf(stderr, "%6d, ", t);
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}
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fprintf(stderr, "\n");
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fprintf(stderr, "%s : got tokens: ", __func__);
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for (const auto & t : res) {
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fprintf(stderr, "%6d, ", t);
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}
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fprintf(stderr, "\n");
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success = false;
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}
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}
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if (!fname_text.empty()) {
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fprintf(stderr, "%s : tokenizing: '%s'\n", __func__, fname_text.c_str());
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std::string text;
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{
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std::ifstream ifs(fname_text);
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if (!ifs) {
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fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_text.c_str());
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return 1;
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}
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text = std::string(std::istreambuf_iterator<char>(ifs), std::istreambuf_iterator<char>());
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}
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fprintf(stderr, "%s : text size: %zu\n", __func__, text.size());
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const std::vector<llama_token> res = llama_tokenize(ctx, text, false);
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fprintf(stderr, "%s : tokens: %zu\n", __func__, res.size());
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{
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const std::string fname_out = fname_text + ".tokcpp";
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std::ofstream ofs(fname_out);
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if (!ofs) {
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fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str());
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return 1;
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}
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for (const auto & tok : res) {
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ofs << tok << " '" << llama_detokenize_bpe(ctx, std::vector<int>{tok}) << "'" << std::endl;
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}
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}
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fprintf(stderr, "%s : tokens written to '%s'\n", __func__, (fname_text + ".tokcpp").c_str());
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}
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llama_free_model(model);
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llama_free(ctx);
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llama_backend_free();
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return success ? 0 : 3;
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}
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83
tests/test-tokenizer-0-deepseek_llm.py
Normal file
83
tests/test-tokenizer-0-deepseek_llm.py
Normal file
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@ -0,0 +1,83 @@
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# tests with BPE tokenizer
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import argparse
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from transformers import AutoTokenizer
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parser = argparse.ArgumentParser()
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parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file")
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parser.add_argument("--fname-tok", help="path to a text file to tokenize")
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args = parser.parse_args()
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dir_tokenizer = args.dir_tokenizer
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tokenizer = AutoTokenizer.from_pretrained(dir_tokenizer)
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tests = [
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"",
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" ",
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" ",
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" ",
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"\t",
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"\n",
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"\t\n",
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"Hello world",
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" 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)
|
||||
|
|
@ -486,6 +486,15 @@ static const std::vector<std::wstring> deepseek_coder_regex = {
|
|||
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<std::wstring> 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<std::codecvt_utf8<wchar_t>> conv;
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue