[BugFix] Fix bad words with speculative decoding (#31908)

Signed-off-by: Nick Hill <nickhill123@gmail.com>

tests/v1/sample/test_rejection_sampler.py

@@ -691,9 +691,13 @@ def test_frequency_penalties(rejection_sampler):
 
 
 def test_bad_words(rejection_sampler):
-    """Test rejection sampling with bad words constraints"""
+    """Test rejection sampling with bad words constraints.
+
+    This test applies bad words to non-consecutive requests (0 and 2, but not 1)
+    to verify correct logit indexing when iterating over requests with bad words.
+    """
     spec_tokens = [[1, 2, 3], [1, 15, 3], [1, 2, 3]]
-    output_tokens = [[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]]
+    output_tokens = [[1, 2, 3, 4], [1, 15, 3, 4], [1, 2, 3, 4]]
 
     logits = create_logits_tensor(output_tokens, token_idx_to_override=15)
     metadata = create_sampling_metadata(
@@ -701,17 +705,9 @@ def test_bad_words(rejection_sampler):
         output_token_ids=[[2], [3], [4]],
         spec_token_ids=spec_tokens,
         bad_words_token_ids={
-            0: [
-                [
-                    2,
-                ]
-            ],
-            1: [
-                [
-                    2,
-                ]
-            ],
-            # Do not apply bad words to the last request
+            0: [[2]],
+            # Request 1 has no bad words (to test non-consecutive request handling)
+            2: [[2]],
         },
     )
     bonus_token_tensor = torch.tensor(
@@ -726,8 +722,11 @@ def test_bad_words(rejection_sampler):
         sampling_metadata=metadata,
     )
 
+    # Request 0: bad word [2] matches prefix, so token 2 is rejected -> 15
+    # Request 1: no bad words, all tokens match -> [1, 15, 3, 4]
+    # Request 2: bad word [2] matches prefix, so token 2 is rejected -> 15
     expected = torch.tensor(
-        [[1, 15, -1, -1], [1, 15, 3, 4], [1, 2, 3, 4]],
+        [[1, 15, -1, -1], [1, 15, 3, 4], [1, 15, -1, -1]],
         dtype=torch.int,
         device=logits.device,
     )

vllm/v1/sample/ops/bad_words.py

@@ -42,11 +42,16 @@ def apply_bad_words_with_drafts(
     num_draft_tokens: list[int],
 ) -> None:
     start_idx = 0
-    for i, bad_words_ids in bad_words_token_ids.items():
-        for draft_idx in range(num_draft_tokens[i]):
+    remaining = len(bad_words_token_ids)
+    for i, n in enumerate(num_draft_tokens):
+        if (bad_words_ids := bad_words_token_ids.get(i)) is not None:
+            for draft_idx in range(start_idx, start_idx + n):
                 _apply_bad_words_single_batch(
-                logits[start_idx + draft_idx],
+                    logits[draft_idx],
                     bad_words_ids,
-                past_tokens_ids[start_idx + draft_idx],
+                    past_tokens_ids[draft_idx],
                 )
-        start_idx += num_draft_tokens[i]
+            remaining -= 1
+            if not remaining:
+                break
+        start_idx += n