Unified tokenizer type onboarding

tokenizer/tokenizer_type.py

@@ -0,0 +1,16 @@
+from enum import Enum
+
+class TokenizerType(Enum):
+    NONE = 0
+    TIKTOKEN = 1
+    SENTENCEPIECE = 2
+    HF_TOKENIZER = 3
+
+    def is_tiktoken(self):
+        return self == TokenizerType.TIKTOKEN
+    def is_sentencepiece(self):
+        return self == TokenizerType.SENTENCEPIECE
+    def is_hf_tokenizer(self):
+        return self == TokenizerType.HF_TOKENIZER
+    def is_none(self):
+        return self == TokenizerType.NONE

torchchat/cli/builder.py

@@ -238,11 +238,7 @@ def from_speculative_args(cls, args: argparse.Namespace) -> "BuilderArgs":
         speculative_builder_args.pte_path = None
         return speculative_builder_args
 
-class TokenizerType(Enum):
-    NONE = 0
-    TIKTOKEN = 1
-    SENTENCEPIECE = 2
-    HF_TOKENIZER = 3
+from tokenizer.tokenizer_type import TokenizerType
 
 @dataclass
 class TokenizerArgs:
@@ -278,15 +274,6 @@ def __post_init__(self):
         except:
             pass
 
-    def is_tiktoken(self) -> bool:
-        return self.tokenizer_type == TokenizerType.TIKTOKEN
-
-    def is_sentencepiece(self) -> bool:
-        return self.tokenizer_type == TokenizerType.SENTENCEPIECE
-
-    def is_hf_tokenizer(self) -> bool:
-        return self.tokenizer_type == TokenizerType.HF_TOKENIZER
-
     def validate_model(
         self,
         model: Optional[Model],
@@ -295,12 +282,12 @@ def validate_model(
         if model is None:
             return
 
-        if self.tokenizer_type == TokenizerType.NONE:
+        if self.tokenizer_type.is_none():
             raise RuntimeError(f"no tokenizer was found at {self.tokenizer_path}")
 
-        is_tiktoken = self.is_tiktoken()
-        is_sentencepiece = self.is_sentencepiece()
-        is_hf_tokenizer = self.is_hf_tokenizer()
+        is_tiktoken = self.tokenizer_type.is_tiktoken()
+        is_sentencepiece = self.tokenizer_type.is_sentencepiece()
+        is_hf_tokenizer = self.tokenizer_type.is_hf_tokenizer()
 
         use_tiktoken = model.config.use_tiktoken
         use_hf_tokenizer = model.config.use_hf_tokenizer

torchchat/generate.py

@@ -365,14 +365,14 @@ def __init__(
         # must use tiktokenizer.
         # Piggy backing off of this flag then for now to identify llama3
         # without prompting user.
-        self.is_llama3_model = self.tokenizer_args.is_tiktoken()
+        self.is_llama3_model = self.tokenizer_args.tokenizer_type.is_tiktoken()
         if self.is_llama3_model:
             self.chat_formatter = Llama3ChatFormatter(self.tokenizer)
             if generator_args.chat_mode:
                 logger.debug(
                     "Llama3 model detected in chat mode. Using updated sentence schemas"
                 )
-        elif self.tokenizer_args.is_hf_tokenizer():
+        elif self.tokenizer_args.tokenizer_type.is_hf_tokenizer():
             if not self.tokenizer.has_chat_template():
                 raise ValueError("Tokenizer must have a chat template")
             self.chat_formatter = HFTokenizerChatFormatter(self.tokenizer)