[V1] Do not detokenize if sampling param detokenize is False (#14224)

Signed-off-by: Himanshu Jaju <hj@mistral.ai>
Signed-off-by: Nick Hill <nhill@redhat.com>
Co-authored-by: Nick Hill <nhill@redhat.com>

vllm/v1/engine/logprobs.py

@@ -1,6 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import itertools
+from collections.abc import Iterable
 from dataclasses import dataclass
 from typing import Optional
 
@@ -13,12 +14,15 @@ from vllm.v1.outputs import LogprobsLists, LogprobsTensors
 
 logger = init_logger(__name__)
 
+NONES = itertools.repeat(None)
+
 
 @dataclass
 class LogprobsProcessor:
 
-    # Tokenizer for this request
-    tokenizer: AnyTokenizer
+    # Tokenizer for this request,
+    # None if detokenization is disabled.
+    tokenizer: Optional[AnyTokenizer]
 
     # Logprobs for this request
     logprobs: Optional[SampleLogprobs]
@@ -30,7 +34,7 @@ class LogprobsProcessor:
     @classmethod
     def from_new_request(
         cls,
-        tokenizer: AnyTokenizer,
+        tokenizer: Optional[AnyTokenizer],
         request: EngineCoreRequest,
     ) -> "LogprobsProcessor":
         num_logprobs = request.sampling_params.logprobs
@@ -66,8 +70,8 @@ class LogprobsProcessor:
                                              token_ids_lst):
 
             # Detokenize (non-incrementally).
-            decoded_tokens = convert_ids_list_to_tokens(
-                self.tokenizer, token_ids)
+            decoded_tokens = NONES if self.tokenizer is None else (
+                convert_ids_list_to_tokens(self.tokenizer, token_ids))
 
             # Sampler puts the sampled logprob in first.
             sampled_token_logprob = logprobs[0]
@@ -103,9 +107,9 @@ class LogprobsProcessor:
 
         # Detokenize non-incrementally.
         # Output is flat: [num_tok, num_lps] -> [num_tok * num_lps]
-        decoded_tokens = convert_ids_list_to_tokens(
-            self.tokenizer,
-            token_ids.flatten().tolist())
+        decoded_tokens = None if self.tokenizer is None else (
+            convert_ids_list_to_tokens(self.tokenizer,
+                                       token_ids.flatten().tolist()))
 
         # Recover shapes.
         num_prompt_tokens, num_logprobs = logprobs.shape
@@ -121,7 +125,8 @@ class LogprobsProcessor:
             # Handle flattening.
             offset = pos * num_logprobs
             offset_end = offset + num_logprobs
-            decoded_tokens_for_pos = decoded_tokens[offset:offset_end]
+            decoded_tokens_for_pos = NONES \
+            if decoded_tokens is None else decoded_tokens[offset:offset_end]
 
             # Update with the Logprob dictionary for this pos.
             self.prompt_logprobs.append(
@@ -153,7 +158,7 @@ class LogprobsProcessor:
     def _make_logprob_dict(
         logprobs: list[float],
         logprob_token_ids: list[int],
-        decoded_tokens: list[str],
+        decoded_tokens: Iterable[Optional[str]],
         rank: int,
         num_logprobs: int,
     ) -> dict[int, Logprob]: