[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/test_quantization.py

@@ -19,6 +19,7 @@ from tests.e2e.conftest import VllmRunner
 from tests.e2e.model_utils import check_outputs_equal
 
 
+# fmt: off
 def test_qwen3_w8a8_quant():
     max_tokens = 5
     example_prompts = [
@@ -29,6 +30,7 @@ def test_qwen3_w8a8_quant():
         13480, 4712, 369, 444, 10994, 82, 13, 1084, 374, 6188, 311, 387
     ], 'vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. It is designed to be'
                             )]
+# fmt: on
 
     with VllmRunner(
             "vllm-ascend/Qwen3-0.6B-W8A8",
@@ -47,7 +49,7 @@ def test_qwen3_w8a8_quant():
         name_1="vllm_quant_w8a8_outputs",
     )
 
-
+# fmt: off
 def test_qwen3_dense_w8a16():
     max_tokens = 5
     example_prompts = [
@@ -58,6 +60,7 @@ def test_qwen3_dense_w8a16():
         13480, 4712, 369, 444, 10994, 82, 13, 1084, 374, 6188, 311, 387
     ], 'vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. It is designed to be'
                             )]
+# fmt: on
 
     with VllmRunner(
             "vllm-ascend/Qwen3-0.6B-W8A16",