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

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

examples/offline_inference/logits_processor.py

@@ -42,8 +42,8 @@ from vllm.config import VllmConfig
 from vllm.v1.sample.logits_processor import (
     BatchUpdate,
     LogitsProcessor,
-    MoveDirectionality,
 )
+from vllm.v1.sample.logits_processor.builtin import process_dict_updates
 
 
 # Hypothetical custom logits processor
@@ -53,38 +53,22 @@ 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,
+            # This function returns the LP's per-request state based on the
+            # request details, or None if this LP does not apply to the
+            # request.
+            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: