[Model Runner V2] Minor simplification for BadWordsState (#34669)

Signed-off-by: Woosuk Kwon <woosuk@inferact.ai>

vllm/v1/worker/gpu/sample/bad_words.py

@@ -39,18 +39,11 @@ class BadWordsState:
         )
         # number of bad words per request
         self.num_bad_words = UvaBackedTensor(self.max_num_reqs, dtype=torch.int32)
-        # whether request uses bad words
-        self.use_bad_words = np.zeros(self.max_num_reqs, dtype=bool)
 
-    def add_request(
-        self,
-        req_idx: int,
-        sampling_params: SamplingParams,
-    ) -> None:
+    def add_request(self, req_idx: int, sampling_params: SamplingParams) -> None:
         bad_words_token_ids = sampling_params.bad_words_token_ids
         if not bad_words_token_ids:
             self.num_bad_words.np[req_idx] = 0
-            self.use_bad_words[req_idx] = False
             return
 
         num_bad_words = len(bad_words_token_ids)
@@ -77,7 +70,6 @@ class BadWordsState:
         self.bad_word_token_ids.stage_write(req_idx, 0, flattened_tokens)
         self.bad_word_offsets.stage_write(req_idx, 0, offsets)
         self.num_bad_words.np[req_idx] = num_bad_words
-        self.use_bad_words[req_idx] = True
 
     def apply_staged_writes(self) -> None:
         self.num_bad_words.copy_to_uva()
@@ -92,11 +84,11 @@ class BadWordsState:
         input_ids: torch.Tensor,
         expanded_local_pos: torch.Tensor,
     ) -> None:
-        if not np.any(self.use_bad_words[idx_mapping_np]):
+        max_num_bad_words = int(self.num_bad_words.np[idx_mapping_np].max())
+        if max_num_bad_words == 0:
             # No request uses bad words. Skip the kernel launch.
             return
 
-        actual_max_num_bad_words = int(np.max(self.num_bad_words.np[idx_mapping_np]))
         apply_bad_words(
             logits,
             idx_mapping,
@@ -108,7 +100,7 @@ class BadWordsState:
             self.total_len,
             input_ids,
             expanded_local_pos,
-            actual_max_num_bad_words,
+            max_num_bad_words,
         )