Convert formatting to use ruff instead of yapf + isort (#26247)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

tests/v1/logits_processors/utils.py

@@ -10,10 +10,13 @@ import torch
 from vllm.config import VllmConfig
 from vllm.logger import init_logger
 from vllm.sampling_params import SamplingParams
-from vllm.v1.sample.logits_processor import (LOGITSPROCS_GROUP,
-                                             AdapterLogitsProcessor,
-                                             BatchUpdate, LogitsProcessor,
-                                             RequestLogitsProcessor)
+from vllm.v1.sample.logits_processor import (
+    LOGITSPROCS_GROUP,
+    AdapterLogitsProcessor,
+    BatchUpdate,
+    LogitsProcessor,
+    RequestLogitsProcessor,
+)
 from vllm.v1.sample.logits_processor.builtin import process_dict_updates
 
 logger = init_logger(__name__)
@@ -30,6 +33,7 @@ DUMMY_LOGITPROC_FQCN = f"{DUMMY_LOGITPROC_MODULE}:DummyLogitsProcessor"
 
 class CustomLogitprocSource(Enum):
     """How to source a logitproc for testing purposes"""
+
     LOGITPROC_SOURCE_NONE = auto()  # No custom logitproc
     LOGITPROC_SOURCE_ENTRYPOINT = auto()  # Via entrypoint
     LOGITPROC_SOURCE_FQCN = auto()  # Via fully-qualified class name (FQCN)
@@ -48,8 +52,9 @@ prompts = [
 class DummyLogitsProcessor(LogitsProcessor):
     """Fake logit processor to support unit testing and examples"""
 
-    def __init__(self, vllm_config: "VllmConfig", device: torch.device,
-                 is_pin_memory: bool):
+    def __init__(
+        self, vllm_config: "VllmConfig", device: torch.device, is_pin_memory: bool
+    ):
         self.req_info: dict[int, int] = {}
 
     def is_argmax_invariant(self) -> bool:
@@ -60,8 +65,8 @@ class DummyLogitsProcessor(LogitsProcessor):
         process_dict_updates(
             self.req_info,
             batch_update,
-            lambda params, _, __: params.extra_args and
-            (params.extra_args.get("target_token")),
+            lambda params, _, __: params.extra_args
+            and (params.extra_args.get("target_token")),
         )
 
     def apply(self, logits: torch.Tensor) -> torch.Tensor:
@@ -69,16 +74,16 @@ class DummyLogitsProcessor(LogitsProcessor):
             return logits
 
         # Save target values before modification
-        cols = torch.tensor(list(self.req_info.values()),
-                            dtype=torch.long,
-                            device=logits.device)
-        rows = torch.tensor(list(self.req_info.keys()),
-                            dtype=torch.long,
-                            device=logits.device)
+        cols = torch.tensor(
+            list(self.req_info.values()), dtype=torch.long, device=logits.device
+        )
+        rows = torch.tensor(
+            list(self.req_info.keys()), dtype=torch.long, device=logits.device
+        )
         values_to_keep = logits[rows, cols].clone()
 
         # Mask all but target tokens
-        logits[rows] = float('-inf')
+        logits[rows] = float("-inf")
         logits[rows, cols] = values_to_keep
 
         return logits
@@ -154,14 +159,17 @@ class WrappedPerReqLogitsProcessor(AdapterLogitsProcessor):
         Returns:
           `Callable` request logits processor, or None
         """
-        target_token: Optional[
-            Any] = params.extra_args and params.extra_args.get("target_token")
+        target_token: Optional[Any] = params.extra_args and params.extra_args.get(
+            "target_token"
+        )
         if target_token is None:
             return None
         if not isinstance(target_token, int):
             logger.warning(
                 "target_token value %s is not int; not applying logits"
-                " processor to request.", target_token)
+                " processor to request.",
+                target_token,
+            )
             return None
         return DummyPerReqLogitsProcessor(target_token)