[Lint]Style: Convert test/ to ruff format(Batch #5) (#6747)

### What this PR does / why we need it?
| File Path |
| :--- |
| `tests/e2e/singlecard/compile/backend.py` |
| `tests/e2e/singlecard/compile/test_graphex_norm_quant_fusion.py` |
| `tests/e2e/singlecard/compile/test_graphex_qknorm_rope_fusion.py` |
| `tests/e2e/singlecard/compile/test_norm_quant_fusion.py` |
| `tests/e2e/singlecard/model_runner_v2/test_basic.py` |
| `tests/e2e/singlecard/test_aclgraph_accuracy.py` |
| `tests/e2e/singlecard/test_aclgraph_batch_invariant.py` |
| `tests/e2e/singlecard/test_aclgraph_mem.py` |
| `tests/e2e/singlecard/test_async_scheduling.py` |
| `tests/e2e/singlecard/test_auto_fit_max_mode_len.py` |
| `tests/e2e/singlecard/test_batch_invariant.py` |
| `tests/e2e/singlecard/test_camem.py` |
| `tests/e2e/singlecard/test_completion_with_prompt_embeds.py` |
| `tests/e2e/singlecard/test_cpu_offloading.py` |
| `tests/e2e/singlecard/test_guided_decoding.py` |
| `tests/e2e/singlecard/test_ilama_lora.py` |
| `tests/e2e/singlecard/test_llama32_lora.py` |
| `tests/e2e/singlecard/test_models.py` |
| `tests/e2e/singlecard/test_multistream_overlap_shared_expert.py` |
| `tests/e2e/singlecard/test_quantization.py` |
| `tests/e2e/singlecard/test_qwen3_multi_loras.py` |
| `tests/e2e/singlecard/test_sampler.py` |
| `tests/e2e/singlecard/test_vlm.py` |
| `tests/e2e/singlecard/test_xlite.py` |
| `tests/e2e/singlecard/utils.py` |

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.15.0
- vLLM main:
9562912cea

---------

Signed-off-by: MrZ20 <2609716663@qq.com>

tests/e2e/singlecard/compile/backend.py

@@ -14,8 +14,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
+from collections.abc import Callable, Sequence
 from copy import deepcopy
-from typing import Any, Callable, List, Optional, Sequence
+from typing import Any
 
 import torch.fx as fx
 from torch._inductor.decomposition import select_decomp_table
@@ -37,7 +38,7 @@ class TestBackend:
     records the FX graph before and after the transformation.
     """
 
-    def __init__(self, custom_passes: Optional[List[Any]] = None):
+    def __init__(self, custom_passes: list[Any] | None = None):
         vllm_config = get_current_vllm_config()
         compile_config = vllm_config.compilation_config
         self.inductor_config = compile_config.inductor_compile_config
@@ -48,9 +49,7 @@ class TestBackend:
         self.graph_pre_pass = None
         self.graph_post_pass = None
 
-    def post_pass(self,
-                  graph: fx.Graph,
-                  runtime_shape: int | None = None) -> fx.Graph:
+    def post_pass(self, graph: fx.Graph, runtime_shape: int | None = None) -> fx.Graph:
         """
         Apply custom graph transformation passes.
         """
@@ -62,13 +61,13 @@ class TestBackend:
         return graph
 
     def compile(
-            self,
-            graph: fx.GraphModule,
-            example_inputs: list[Any],
-            compiler_config: dict[str, Any],
-            runtime_shape: Optional[int] = None,
-            key: Optional[str] = None
-    ) -> tuple[Optional[Callable], Optional[Any]]:
+        self,
+        graph: fx.GraphModule,
+        example_inputs: list[Any],
+        compiler_config: dict[str, Any],
+        runtime_shape: int | None = None,
+        key: str | None = None,
+    ) -> tuple[Callable | None, Any | None]:
         """
         Compile the FX graph using vLLM's Ascend compiler interface.
         Wraps the post-pass logic into the inner_compile callback.
@@ -87,8 +86,7 @@ class TestBackend:
         )
         return compiled_fn, None
 
-    def __call__(self, gm: fx.GraphModule,
-                 example_inputs: Optional[List[Any]]):
+    def __call__(self, gm: fx.GraphModule, example_inputs: list[Any] | None):
         """
         Make the backend callable by torch.compile().
         Returns a compiled executable function.
@@ -103,17 +101,11 @@ class TestBackend:
         )
         return compiled_fn
 
-    def find_nodes_by_target(self, graph: fx.GraphModule,
-                             target: OpOverload) -> List[fx.Node]:
+    def find_nodes_by_target(self, graph: fx.GraphModule, target: OpOverload) -> list[fx.Node]:
         """Helper to find all FX nodes that call a specific operator."""
-        return [
-            node for node in graph.graph.nodes
-            if hasattr(node, 'target') and node.target == target
-        ]
+        return [node for node in graph.graph.nodes if hasattr(node, "target") and node.target == target]
 
-    def check_before_ops(self,
-                         ops: Sequence[OpOverload],
-                         fully_replaced: bool = True):
+    def check_before_ops(self, ops: Sequence[OpOverload], fully_replaced: bool = True):
         """
         Verify that the original (unfused) operators exist before the pass
         and are fully removed afterward (if fully_replaced=True).