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

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

tests/v1/core/utils.py

@@ -4,18 +4,29 @@ from typing import Optional, Union
 
 import torch
 
-from vllm.config import (CacheConfig, KVTransferConfig, ModelConfig,
-                         SchedulerConfig, SpeculativeConfig, VllmConfig)
-from vllm.multimodal.inputs import (MultiModalFeatureSpec,
-                                    MultiModalKwargsItem, PlaceholderRange)
+from vllm.config import (
+    CacheConfig,
+    KVTransferConfig,
+    ModelConfig,
+    SchedulerConfig,
+    SpeculativeConfig,
+    VllmConfig,
+)
+from vllm.multimodal.inputs import (
+    MultiModalFeatureSpec,
+    MultiModalKwargsItem,
+    PlaceholderRange,
+)
 from vllm.sampling_params import SamplingParams
 from vllm.utils import sha256
-from vllm.v1.core.kv_cache_utils import (get_request_block_hasher,
-                                         init_none_hash)
+from vllm.v1.core.kv_cache_utils import get_request_block_hasher, init_none_hash
 from vllm.v1.core.sched.async_scheduler import AsyncScheduler
 from vllm.v1.core.sched.scheduler import Scheduler
-from vllm.v1.kv_cache_interface import (FullAttentionSpec, KVCacheConfig,
-                                        KVCacheGroupSpec)
+from vllm.v1.kv_cache_interface import (
+    FullAttentionSpec,
+    KVCacheConfig,
+    KVCacheGroupSpec,
+)
 from vllm.v1.request import Request
 from vllm.v1.structured_output import StructuredOutputManager
 
@@ -37,7 +48,7 @@ def create_scheduler(
     skip_tokenizer_init: bool = False,
     async_scheduling: bool = False,
 ) -> Union[Scheduler, AsyncScheduler]:
-    '''Create scheduler under test.
+    """Create scheduler under test.
 
     Args:
       model: model under test
@@ -49,7 +60,7 @@ def create_scheduler(
 
     Returns:
       {class}`Scheduler` instance
-    '''
+    """
     if max_model_len is None:
         max_model_len = max_num_batched_tokens
     scheduler_config = SchedulerConfig(
@@ -69,9 +80,11 @@ def create_scheduler(
         skip_tokenizer_init=skip_tokenizer_init,
     )
     # Cache config, optionally force APC
-    kwargs_cache = ({} if enable_prefix_caching is None else {
-        'enable_prefix_caching': enable_prefix_caching
-    })
+    kwargs_cache = (
+        {}
+        if enable_prefix_caching is None
+        else {"enable_prefix_caching": enable_prefix_caching}
+    )
     cache_config = CacheConfig(
         block_size=block_size,
         gpu_memory_utilization=0.9,
@@ -79,16 +92,21 @@ def create_scheduler(
         cache_dtype="auto",
         **kwargs_cache,
     )
-    kv_transfer_config = KVTransferConfig(
-        kv_connector="SharedStorageConnector",
-        kv_role="kv_both",
-        kv_connector_extra_config={"shared_storage_path": "local_storage"},
-    ) if use_kv_connector else None
+    kv_transfer_config = (
+        KVTransferConfig(
+            kv_connector="SharedStorageConnector",
+            kv_role="kv_both",
+            kv_connector_extra_config={"shared_storage_path": "local_storage"},
+        )
+        if use_kv_connector
+        else None
+    )
 
     speculative_config: Optional[SpeculativeConfig] = None
     if num_speculative_tokens is not None:
         speculative_config = SpeculativeConfig(
-            model="ngram", num_speculative_tokens=num_speculative_tokens)
+            model="ngram", num_speculative_tokens=num_speculative_tokens
+        )
 
     vllm_config = VllmConfig(
         scheduler_config=scheduler_config,
@@ -101,9 +119,9 @@ def create_scheduler(
         num_blocks=num_blocks,  # A large number of blocks to hold all requests
         kv_cache_tensors=[],
         kv_cache_groups=[
-            KVCacheGroupSpec(['layer'],
-                             FullAttentionSpec(block_size, 1, 1, torch.float32,
-                                               False))
+            KVCacheGroupSpec(
+                ["layer"], FullAttentionSpec(block_size, 1, 1, torch.float32, False)
+            )
         ],
     )
     cache_config.num_gpu_blocks = num_blocks
@@ -135,10 +153,12 @@ def create_requests(
         _none_hash_initialized = True
 
     block_hasher = get_request_block_hasher(block_size, sha256)
-    sampling_params = SamplingParams(ignore_eos=False,
-                                     max_tokens=max_tokens,
-                                     stop_token_ids=stop_token_ids,
-                                     prompt_logprobs=prompt_logprobs)
+    sampling_params = SamplingParams(
+        ignore_eos=False,
+        max_tokens=max_tokens,
+        stop_token_ids=stop_token_ids,
+        prompt_logprobs=prompt_logprobs,
+    )
     requests = []
     for i in range(num_requests):
         mm_features = []
@@ -152,11 +172,11 @@ def create_requests(
                     data=MultiModalKwargsItem.dummy("dummy_m"),
                     mm_position=position,
                     identifier=identifier,
-                    modality="image")
+                    modality="image",
+                )
                 mm_features.append(mm_feature)
 
-        prompt_token_ids = ([0] * num_tokens if same_prompt else [i] *
-                            num_tokens)
+        prompt_token_ids = [0] * num_tokens if same_prompt else [i] * num_tokens
         request = Request(
             request_id=f"{i}",
             prompt_token_ids=prompt_token_ids,