Add regex loading from tokenizer.json and code refinement

cgmanifest.json

@@ -62,7 +62,7 @@
       "component": {
         "type": "git",
         "git": {
-          "commitHash": "9406a60c7839052e4944ea4dbc8344762a89f9bd",
+          "commitHash": "e39786088138f2749d64e9e90e0f9902daa77c40",
           "repositoryUrl": "https://github.com/google/googletest.git"
         }
       }

cmake/externals/googletest.cmake

@@ -1,7 +1,7 @@
 FetchContent_Declare(
   googletest
-  URL             https://github.com/google/googletest/archive/9406a60c7839052e4944ea4dbc8344762a89f9bd.zip
-  URL_HASH        SHA1=06096d3900c356e468ba060a609642c635131106
+  URL             https://github.com/google/googletest/archive/refs/tags/v1.15.0.zip
+  URL_HASH        SHA1=9d2d0af8d77ac726ea55d44a8fa727ec98311349
   EXCLUDE_FROM_ALL
 )
 

onnxruntime_extensions/pp_api.py

@@ -49,10 +49,12 @@ def __init__(self, tokenizer_dir):
             self.tokenizer = create_tokenizer(tokenizer_dir)
 
     def tokenize(self, text):
+        if isinstance(text, (list, tuple)):
+            return batch_tokenize(self.tokenizer, text)
         return batch_tokenize(self.tokenizer, [text])[0]
 
     def detokenize(self, tokens):
-        return batch_detokenize(self.tokenizer, [tokens])[0]
+        return batch_detokenize(self.tokenizer, [tokens])
 
     def __del__(self):
         if delete_object and self.tokenizer:

operators/tokenizer/bpe_kernels.cc

@@ -262,7 +262,7 @@ std::vector<int64_t> KernelBpeTokenizer::Tokenize(ustring& input,
 
   // Parse input
   auto special_token_split_res = bbpe_tokenizer_->SplitByAddedAndSpecial(input);
-  bpe::TokenWithRegularExp regcmp;
+  bpe::PreTokenizerWithRegEx reg_splitter;
 
   for (auto& seg_id : special_token_split_res) {
     if (static_cast<int64_t>(res.size()) >= max_length) break;
@@ -274,7 +274,7 @@ std::vector<int64_t> KernelBpeTokenizer::Tokenize(ustring& input,
 
     // Note: keep ptr to make sure the string_view is valid in the following process
     std::u32string str(seg_id.first);
-    regcmp.Set(str.c_str());
+    reg_splitter.Set(str.c_str());
 
     size_t offset = 0;
     OffsetMappingType offset_mapping;
@@ -287,14 +287,8 @@ std::vector<int64_t> KernelBpeTokenizer::Tokenize(ustring& input,
     }
 
     while (static_cast<int64_t>(res.size()) < max_length) {
-      std::string regex_expr = "";
-      if (ModelName() == kModel_Llama){
-        regex_expr = regcmp.LLAMA_REGEX_PATTERN;
-      } else {
-        // default to GPT2 regex
-        regex_expr = regcmp.GPT2_REGEX_PATTERN;
-      }
-      auto [b, tok] = regcmp.GetNextToken(regex_expr);
+      std::string regex_expr =  bbpe_tokenizer_->GetPreTokenizerRegex(ModelName());
+      auto [b, tok] = reg_splitter.GetNextToken(regex_expr);
 
       if (!b) break;
 
@@ -742,9 +736,9 @@ OrtxStatus JsonFastTokenizer::Load(const ort_extensions::TokenJsonConfig& config
   }
 
   bbpe_tokenizer_ = std::make_unique<BpeModel>();
-  status = bbpe_tokenizer_->Load(*model_node,
-                                            bpe_conf_.get().GetSpecialTokens().c_str(),
-                                            bpe_conf_.get().spm_model_);
+  status = bbpe_tokenizer_->Load(*model_node, tok_json,
+                                 bpe_conf_.get().GetSpecialTokens().c_str(),
+                                 bpe_conf_.get().spm_model_);
   if (status.IsOk()) {
     UpdateTokenizer(config, tok_json);
   }

operators/tokenizer/bpe_tokenizer_model.hpp

@@ -20,8 +20,12 @@
 #include "trietree.hpp"
 #include "tokenizer_common.h"
 
-namespace ort_extensions {
+#define ORTX_JSON_RETURN_IF_NULL(node_iter, name, var) \
+  auto var = (node_iter)->find(name); \
+  if (var == (node_iter)->end() || var->is_null()) { return {}; }
+
 
+namespace ort_extensions {
 class BpeModel {
   using json = nlohmann::json;
 
@@ -44,6 +48,39 @@ class BpeModel {
     }
   }
 
+  OrtxStatus LoadPreTokenizer(const json& bpe_model) {
+    auto root_node = &bpe_model;
+    ORTX_JSON_RETURN_IF_NULL(root_node, "pre_tokenizer", node_pre_tokenizer);
+    ORTX_JSON_RETURN_IF_NULL(node_pre_tokenizer, "type", iter_type);
+
+    auto pre_token_type = iter_type->get<std::string>();
+    if (pre_token_type == "ByteLevel") {
+      // need to add more flag support here in the future
+      return {};
+    } else if (pre_token_type != "Sequence") {
+      return {kOrtxErrorNotImplemented, std::string("Unsupported pretokenizer type!") + pre_token_type};
+    }
+
+    ORTX_JSON_RETURN_IF_NULL(node_pre_tokenizer, "pretokenizers", iter_node_list);
+
+    for (const auto& node : *iter_node_list) {
+      ORTX_JSON_RETURN_IF_NULL(&node, "type", iter_type);
+      auto pre_type = iter_type->get<std::string>();
+      if (pre_type == "Split") {
+        ORTX_JSON_RETURN_IF_NULL(&node, "pattern", iter_pattern);
+        ORTX_JSON_RETURN_IF_NULL(iter_pattern, "Regex", regex_str);
+        pre_tokenizer_regex_ = regex_str->get<std::string>();
+      } else if (pre_type == "ByteLevel") {
+        ; // need to add more flag support here in the future
+      }
+      else {
+        return {kOrtxErrorNotImplemented, "Unsupported pretokenizer type!"};
+      }
+    }
+
+    return {};
+  }
+
   OrtxStatus Load(std::istream& vocab_stream, std::istream& merges_stream, const char* unk_token,
                   const char* special_tokens, bool spm_converted) {
     nlohmann::json tok_json;
@@ -120,7 +157,9 @@ class BpeModel {
     return {};
   }
 
-  OrtxStatus Load(const json& bpe_model, const char* /* special_tokens */, bool spm_converted) {
+  OrtxStatus Load(const json& bpe_model, const json& tok_json, const char* /* special_tokens */, bool spm_converted) {
+    ORTX_RETURN_IF_ERROR(LoadPreTokenizer(tok_json));
+
     const json& vocab_json = bpe_model["vocab"];
     const json& merges_json = bpe_model["merges"];
     vocab_json.get_to(vocab_map_);
@@ -358,6 +397,19 @@ class BpeModel {
 
   const std::string& GetEndOfWordSuffix() const { return end_of_word_suffix_; }
 
+  std::string GetPreTokenizerRegex(const std::string& model_name) const {
+    if (!pre_tokenizer_regex_.empty()) {
+      return pre_tokenizer_regex_;
+    }
+
+    if (model_name == "Llama") {
+      return bpe::PreTokenizerWithRegEx::LLAMA_REGEX_PATTERN;
+    }
+
+    // by default, use the GPT2 pretokenizer regex
+    return bpe::PreTokenizerWithRegEx::GPT2_REGEX_PATTERN;
+  }
+
  private:
   struct BpeNode {
     uint32_t id;
@@ -379,6 +431,7 @@ class BpeModel {
   uint32_t unk_id_ = (std::numeric_limits<uint32_t>::max)();
   bpe::SpecialTokenMap special_tokens_;
   TrieTree<char32_t> added_tokens_;
+  std::string pre_tokenizer_regex_;
 };
 
 }  // namespace ort_extensions

operators/tokenizer/bpe_utils.hpp

@@ -97,8 +97,12 @@ class SpecialTokenMap {
   std::unordered_map<ustring, int> token_map_;
 };
 
-class TokenWithRegularExp {
+class PreTokenizerWithRegEx {
  public:
+  static constexpr const char* GPT2_REGEX_PATTERN = "'s|'t|'re|'ve|'m|'ll|'d|?\\p{L}+|?\\p{N}+|?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)|\\s+";
+  static constexpr const char* LLAMA_REGEX_PATTERN = "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}|?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+";
+  static constexpr const char* LLAMA_REGEX_PATTERN_2 = "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+";
+
   void Set(std::u32string_view val) {
     m_text = val;
   }
@@ -115,10 +119,6 @@ class TokenWithRegularExp {
     return {false, {}};
   }
 
-  const std::string GPT2_REGEX_PATTERN = "'s|'t|'re|'ve|'m|'ll|'d|?\\p{L}+|?\\p{N}+|?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)|\\s+";
-  const std::string LLAMA_REGEX_PATTERN = "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}|?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+";
-  const std::string LLAMA_REGEX_PATTERN_2 = "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+";
-
  public:
 
   // Although we have RegexMatchGeneral which performs regex matching given any general regex string

operators/tokenizer/tokenizer_jsconfig.hpp

@@ -26,6 +26,7 @@ constexpr std::pair<const char*, TokenType> kTokenizerDict[] = {
   {"GPT2Tokenizer", TokenType::kBPE},
   {"Qwen2Tokenizer", TokenType::kBPE},
   {"BaichuanTokenizer", TokenType::kBPE},
+  {"GPTNeoXTokenizer", TokenType::kBPE},
 
   {"", TokenType::kUnigram},
   {"T5Tokenizer", TokenType::kUnigram},

operators/tokenizer/trietree.hpp

@@ -97,6 +97,7 @@ class TrieTree {
       tok_idx += 1;
       if (tok_id == invalid_id) {
         if (tok_idx < input.length()) {
+          tok_idx -= tok_len;  // backtrack to the last token
           continue;
         } else {
           tok_idx += 1;  // Assign tok_idx to input.length()

pyop/py_c_api.cc

@@ -121,7 +121,7 @@ void AddGlobalMethodsCApi(pybind11::module& m) {
         OrtxTokenizer* tokenizer = nullptr;
         auto err = OrtxCreateTokenizer(&tokenizer, tokenizer_def_json.c_str());
         if (err != kOrtxOK) {
-          throw std::runtime_error(std::string("Failed to create tokenizer") + OrtxGetLastErrorMessage());
+          throw std::runtime_error(std::string("Failed to create tokenizer\n") + OrtxGetLastErrorMessage());
         }
         return reinterpret_cast<std::uintptr_t>(tokenizer);
       },

pyop/pyfunc.cc

@@ -258,10 +258,9 @@ void PyCustomOpKernel::Compute(OrtKernelContext* context) {
     inputs.push_back(InputInformation{input_X, i_dtype, i_dimensions});
   }
 
-  /* Acquire GIL before calling Python code, due to it was released in sess.run */
-  py::gil_scoped_acquire acquire;
-
   {
+    /* Acquire GIL before calling Python C API, due to it was released in sess.run */
+    py::gil_scoped_acquire acquire;
     py::list pyinputs;
     for (auto it = inputs.begin(); it != inputs.end(); ++it) {
       py::object input0 = PyCustomOpDefImpl::BuildPyArrayFromTensor(
@@ -349,8 +348,6 @@ void PyCustomOpKernel::Compute(OrtKernelContext* context) {
         memcpy(out, retval.data(), size * retval.size());
       }
     }
-
-    py::gil_scoped_release release;
   }
 }
 

shared/api/tokenizer_impl.cc

@@ -11,33 +11,15 @@
 
 namespace ort_extensions {
 
-std::set<std::string> TokenizerImpl::supported_bpe_models_ = {
-  "PreTrainedTokenizerFast", 
-  "CLIPTokenizer",
-  "WhisperTokenizer",
-  "GemmaTokenizer",
-  "LlamaTokenizer",
-  "Phi3Tokenizer",
-  "CodeLlamaTokenizer",
-  "CodeGenTokenizer",
-  "GPT2Tokenizer",
-  "Qwen2Tokenizer",
-  "BaichuanTokenizer"
-};
-
-std::set<std::string> TokenizerImpl::supported_ugm_models_ = {
-  "XLMRobertaTokenizer",
-  "T5Tokenizer",
-  "ChatGLMTokenizer"
-};
 
 TokenizerImpl::TokenizerImpl()
     : OrtxObjectImpl(extObjectKind_t::kOrtxKindTokenizer) {};
 TokenizerImpl::~TokenizerImpl() {};
 
 OrtxStatus TokenizerImpl::LoadTokenizer(const OrtxTokenizerBlob* blob) {
-  if (tok_config_->tokenizer_class_.empty() ||
-      supported_ugm_models_.count(tok_config_->tokenizer_class_)) {
+
+  auto type = TokenJsonConfig::GetTokenType(tok_config_->tokenizer_class_);
+  if (type == TokenType::kUnigram) {
     auto tokenizer = std::make_unique<SpmUgmTokenizer>();
     auto status = tokenizer->Load(*tok_config_);
     if (!status.IsOk()) {
@@ -53,42 +35,39 @@ OrtxStatus TokenizerImpl::LoadTokenizer(const OrtxTokenizerBlob* blob) {
       tokenizer_ = std::move(tokenizer);
       detokenizer_ = std::move(detok);
     }
-
     return status;
-  }
-
-  if (!supported_bpe_models_.count(tok_config_->tokenizer_class_)) {
-    return OrtxStatus(kOrtxErrorNotImplemented, "Unsupported tokenizer class");
-  }
-
-  auto tokenizer = std::make_unique<JsonFastTokenizer>();
-  auto fx_load = &JsonFastTokenizer::Load;
-  if (blob == nullptr) {
-    auto vocab_file_path = ortx::path(tok_config_->GetVocabDataFile());
-    // vocab file is checked in TokenJsonConfig::Load
-    if (vocab_file_path.extension() != ".json") {
-      fx_load = &JsonFastTokenizer::LoadTikTokenBase64;
+  } else if (type == TokenType::kBPE) {
+    auto tokenizer = std::make_unique<JsonFastTokenizer>();
+    auto fx_load = &JsonFastTokenizer::Load;
+    if (blob == nullptr) {
+      auto vocab_file_path = ortx::path(tok_config_->GetVocabDataFile());
+      // vocab file is checked in TokenJsonConfig::Load
+      if (vocab_file_path.extension() != ".json") {
+        fx_load = &JsonFastTokenizer::LoadTikTokenBase64;
+      }
+    } else {
+      if (blob->raw_model_blob_len > 0) {
+        fx_load = &JsonFastTokenizer::LoadTikTokenBase64;
+      }
     }
-  } else {
-    if (blob->raw_model_blob_len > 0) {
-      fx_load = &JsonFastTokenizer::LoadTikTokenBase64;
+
+    auto status = (tokenizer.get()->*fx_load)(*tok_config_);
+    if (!status.IsOk()) {
+      return status;
     }
-  }
 
-  auto status = (tokenizer.get()->*fx_load)(*tok_config_);
-  if (!status.IsOk()) {
-    return status;
-  }
+    auto detok = std::make_unique<BpeStreamingDecoder>();
+    status = detok->Load(tok_config_, *tokenizer);
 
-  auto detok = std::make_unique<BpeStreamingDecoder>();
-  status = detok->Load(tok_config_, *tokenizer);
+    if (status.IsOk()) {
+      tokenizer_ = std::move(tokenizer);
+      detokenizer_ = std::move(detok);
+    }
 
-  if (status.IsOk()) {
-    tokenizer_ = std::move(tokenizer);
-    detokenizer_ = std::move(detok);
+    return status;
   }
 
-  return status;
+  return OrtxStatus(kOrtxErrorNotImplemented, "Unsupported tokenizer class");
 }
 
 OrtxStatus TokenizerImpl::Load(const OrtxTokenizerBlob& blob) {

shared/api/tokenizer_impl.h

@@ -15,9 +15,6 @@ namespace ort_extensions {
 
 class TokenizerImpl : public OrtxObjectImpl {
  public:
-  static std::set<std::string> supported_bpe_models_;
-  static std::set<std::string> supported_ugm_models_;
-
   TokenizerImpl();
   virtual ~TokenizerImpl();
 

test/pp_api_test/test_tokenizer.cc

@@ -67,7 +67,7 @@ TEST(CApiTest, StreamApiTest) {
 
 TEST(OrtxTokenizerTest, RegexTest) {
   std::u32string str = U"CAN'T \r\n 2413m";
-  auto regcmp = std::make_unique<ort_extensions::bpe::TokenWithRegularExp>();
+  auto regcmp = std::make_unique<ort_extensions::bpe::PreTokenizerWithRegEx>();
 
   std::vector<std::u32string> res;
   std::vector<std::u32string> out_tokens = {U"CAN", U"'T", U" \r\n", U" ", U"241", U"3", U"m"};
@@ -91,7 +91,7 @@ TEST(OrtxTokenizerTest, RegexMatchSTDTest) {
   std::vector<std::u32string> input_strings = {U"not its, or IT'S, but it's",
                                                U"   ",
                                                U"AbCd"};                      
-  auto regcmp = std::make_unique<ort_extensions::bpe::TokenWithRegularExp>();
+  auto regcmp = std::make_unique<ort_extensions::bpe::PreTokenizerWithRegEx>();
 
   std::vector<std::vector<std::u32string>> res_vector;
   std::vector<std::vector<std::u32string>> out_tokens = {{U"'s"},
@@ -118,7 +118,7 @@ TEST(OrtxTokenizerTest, WrapStandaloneCategoriesTest) {
                                                 "\\p{rn}\\p{L}\\p{N}\\p{L}",
                                                 "\\p{Z}*[\\p{rn}]+",
                                                 "\\p{Z}+"};
-  auto regcmp = std::make_unique<ort_extensions::bpe::TokenWithRegularExp>();
+  auto regcmp = std::make_unique<ort_extensions::bpe::PreTokenizerWithRegEx>();
 
   std::vector<std::string> res;
   std::vector<std::string> out_regex = {"[^\\p{rn}\\p{L}\\p{N}]?[\\p{L}]+",
@@ -152,7 +152,7 @@ TEST(OrtxTokenizerTest, RegexMatchGeneralTest) {
                                                U"241356m",
                                                U"Ich liebe München <3 \r\n ",
                                                U"生活的真谛是"};                      
-  auto regcmp = std::make_unique<ort_extensions::bpe::TokenWithRegularExp>();
+  auto regcmp = std::make_unique<ort_extensions::bpe::PreTokenizerWithRegEx>();
 
   std::vector<std::vector<std::u32string>> res_vector;
   std::vector<std::vector<std::u32string>> out_tokens = {{U"CAN", U"'T", U"", U""},