add qwen3

vllm-v0.6.2/vllm/transformers_utils/tokenizer_group/tokenizer_group.py

@@ -0,0 +1,99 @@
+from typing import List, Optional
+
+from vllm.config import TokenizerPoolConfig
+from vllm.lora.request import LoRARequest
+from vllm.transformers_utils.tokenizer import (AnyTokenizer,
+                                               get_lora_tokenizer,
+                                               get_lora_tokenizer_async,
+                                               get_tokenizer)
+from vllm.utils import LRUCache
+
+from .base_tokenizer_group import BaseTokenizerGroup
+
+
+class TokenizerGroup(BaseTokenizerGroup):
+    """A group of tokenizers that can be used for LoRA adapters."""
+
+    def __init__(self, tokenizer_id: str, enable_lora: bool, max_num_seqs: int,
+                 max_input_length: Optional[int], **tokenizer_config):
+        self.tokenizer_id = tokenizer_id
+        self.tokenizer_config = tokenizer_config
+        self.enable_lora = enable_lora
+        self.max_input_length = max_input_length
+        self.tokenizer = get_tokenizer(self.tokenizer_id, **tokenizer_config)
+        self.lora_tokenizers = LRUCache[AnyTokenizer](
+            capacity=max_num_seqs if enable_lora else 0)
+
+    @classmethod
+    def from_config(cls, tokenizer_pool_config: Optional[TokenizerPoolConfig],
+                    **init_kwargs) -> "TokenizerGroup":
+        return cls(**init_kwargs)
+
+    def ping(self) -> bool:
+        """Check if the tokenizer group is alive."""
+        return True
+
+    def get_max_input_len(self,
+                          lora_request: Optional[LoRARequest] = None
+                          ) -> Optional[int]:
+        """Get the maximum input length for the LoRA request."""
+        return self.max_input_length
+
+    def _raise_if_input_too_long(self,
+                                 encoded_tokens: List[int],
+                                 lora_request: Optional[LoRARequest] = None):
+        input_length = len(encoded_tokens)
+        if lora_request:
+            max_input_length = (lora_request.long_lora_max_len
+                                or self.max_input_length)
+        else:
+            max_input_length = self.max_input_length
+        if max_input_length is not None and input_length > max_input_length:
+            raise ValueError("Input too long.", input_length, max_input_length)
+
+    def encode(self,
+               prompt: str,
+               request_id: Optional[str] = None,
+               lora_request: Optional[LoRARequest] = None) -> List[int]:
+        tokenizer = self.get_lora_tokenizer(lora_request)
+        ret = tokenizer.encode(prompt)
+        self._raise_if_input_too_long(ret, lora_request)
+        return ret
+
+    async def encode_async(
+            self,
+            prompt: str,
+            request_id: Optional[str] = None,
+            lora_request: Optional[LoRARequest] = None) -> List[int]:
+        tokenizer = await self.get_lora_tokenizer_async(lora_request)
+        ret = tokenizer.encode(prompt)
+        self._raise_if_input_too_long(ret, lora_request)
+        return ret
+
+    def get_lora_tokenizer(
+        self,
+        lora_request: Optional[LoRARequest] = None,
+    ) -> AnyTokenizer:
+        if not lora_request or not self.enable_lora:
+            return self.tokenizer
+        if lora_request.lora_int_id not in self.lora_tokenizers:
+            tokenizer = (get_lora_tokenizer(
+                lora_request, **self.tokenizer_config) or self.tokenizer)
+            self.lora_tokenizers.put(lora_request.lora_int_id, tokenizer)
+            return tokenizer
+        else:
+            return self.lora_tokenizers[lora_request.lora_int_id]
+
+    async def get_lora_tokenizer_async(
+        self,
+        lora_request: Optional[LoRARequest] = None,
+    ) -> AnyTokenizer:
+        if not lora_request or not self.enable_lora:
+            return self.tokenizer
+        if lora_request.lora_int_id not in self.lora_tokenizers:
+            tokenizer = (await get_lora_tokenizer_async(
+                lora_request, **self.tokenizer_config) or self.tokenizer)
+            self.lora_tokenizers.put(lora_request.lora_int_id, tokenizer)
+            return tokenizer
+        else:
+            return self.lora_tokenizers[lora_request.lora_int_id]