[Bugfix] Fix bad words for Mistral models (#17753)

Signed-off-by: Qiong Zhou Huang <qiong@phonic.co>

vllm/logits_process.py

@@ -4,11 +4,12 @@ from typing import Callable, Union
 
 import torch
 
-from vllm.transformers_utils.tokenizer import AnyTokenizer, MistralTokenizer
+from vllm.transformers_utils.tokenizer import AnyTokenizer
 
-LogitsProcessor = Union[Callable[[list[int], torch.Tensor], torch.Tensor],
-                        Callable[[list[int], list[int], torch.Tensor],
-                                 torch.Tensor]]
+LogitsProcessor = Union[
+    Callable[[list[int], torch.Tensor], torch.Tensor],
+    Callable[[list[int], list[int], torch.Tensor], torch.Tensor],
+]
 """LogitsProcessor is a function that takes a list
 of previously generated tokens, the logits tensor
 for the next token and, optionally, prompt tokens as a
@@ -29,10 +30,6 @@ def get_bad_words_logits_processors(
             prefix = " " if add_prefix_space else ""
             prompt = prefix + bad_word.lstrip()
 
-            if isinstance(tokenizer, MistralTokenizer):
-                # Mistral tokenizers should not add special tokens
-                prompt_token_ids = tokenizer.encode(text=prompt)
-            else:
             prompt_token_ids = tokenizer.encode(text=prompt,
                                                 add_special_tokens=False)
 

vllm/sampling_params.py

@@ -13,7 +13,6 @@ from typing_extensions import deprecated
 from vllm.logger import init_logger
 from vllm.logits_process import LogitsProcessor
 from vllm.transformers_utils.tokenizer import AnyTokenizer
-from vllm.transformers_utils.tokenizers.mistral import MistralTokenizer
 
 logger = init_logger(__name__)
 
@@ -491,13 +490,8 @@ class SamplingParams(
             for add_prefix_space in [False, True]:
                 prefix = " " if add_prefix_space else ""
                 prompt = prefix + bad_word.lstrip()
-
-                if isinstance(tokenizer, MistralTokenizer):
-                    # Mistral tokenizers should not add special tokens
-                    prompt_token_ids = tokenizer.encode(text=prompt)
-                else:
-                    prompt_token_ids = tokenizer.encode(
-                        text=prompt, add_special_tokens=False)
+                prompt_token_ids = tokenizer.encode(text=prompt,
+                                                    add_special_tokens=False)
 
                 # If no space at the beginning
                 # or if prefix space produces a new word token