[LogitsProcs] Deduplicate built-in LP implementation logic (#23362)

Signed-off-by: Nick Hill <nhill@redhat.com>

tests/v1/logits_processors/utils.py

@@ -8,10 +8,9 @@ from typing import Optional
 import torch
 
 from vllm.config import VllmConfig
-from vllm.sampling_params import SamplingParams
 from vllm.v1.sample.logits_processor import (LOGITSPROCS_GROUP, BatchUpdate,
-                                             LogitsProcessor,
-                                             MoveDirectionality)
+                                             LogitsProcessor)
+from vllm.v1.sample.logits_processor.builtin import process_dict_updates
 
 MODEL_NAME = "facebook/opt-125m"
 POOLING_MODEL_NAME = "BAAI/bge-base-en-v1.5"
@@ -45,37 +44,19 @@ class DummyLogitsProcessor(LogitsProcessor):
 
     def __init__(self, vllm_config: "VllmConfig", device: torch.device,
                  is_pin_memory: bool):
-        self.req_info: dict[int, SamplingParams] = {}
+        self.req_info: dict[int, int] = {}
 
     def is_argmax_invariant(self) -> bool:
         """Never impacts greedy sampling"""
         return False
 
     def update_state(self, batch_update: Optional[BatchUpdate]):
-        if not batch_update:
-            return
-
-        # Process added requests.
-        for index, params, _, _ in batch_update.added:
-            assert params is not None
-            if params.extra_args and (target_token :=
-                                      params.extra_args.get("target_token")):
-                self.req_info[index] = target_token
-
-        if self.req_info:
-            # Process removed requests.
-            for index in batch_update.removed:
-                self.req_info.pop(index, None)
-
-            # Process moved requests, unidirectional move (a->b) and swap
-            # (a<->b)
-            for adx, bdx, direct in batch_update.moved:
-                a_val = self.req_info.pop(adx, None)
-                b_val = self.req_info.pop(bdx, None)
-                if a_val is not None:
-                    self.req_info[bdx] = a_val
-                if direct == MoveDirectionality.SWAP and b_val is not None:
-                    self.req_info[adx] = b_val
+        process_dict_updates(
+            self.req_info,
+            batch_update,
+            lambda params, _, __: params.extra_args and
+            (params.extra_args.get("target_token")),
+        )
 
     def apply(self, logits: torch.Tensor) -> torch.Tensor:
         if not self.req_info: