[Lint]Style: Convert vllm-ascend/ to ruff format(Batch #10) (#6173)

### What this PR does / why we need it?
**Scope of Changes**:
| File Path |
| :--- |
|`vllm_ascend/ops/layer_shard_linear.py`|
|`vllm_ascend/ops/linear.py`|
|`vllm_ascend/ops/linear_op.py`|
|`vllm_ascend/worker/worker.py`|
| ` vllm_ascend/patch/worker/patch_bert.py` |
| ` vllm_ascend/patch/worker/patch_deepseek.py` |
| ` vllm_ascend/patch/worker/patch_distributed.py` |
| ` vllm_ascend/patch/worker/patch_module.py` |
| ` vllm_ascend/patch/worker/patch_multimodal_merge.py` |
| ` vllm_ascend/patch/worker/patch_qwen3_next.py` |
| ` vllm_ascend/patch/worker/patch_qwen3_next_mtp.py` |
| ` vllm_ascend/patch/worker/patch_rejection_sampler.py` |
| ` vllm_ascend/patch/worker/patch_rope.py` |
| ` vllm_ascend/patch/worker/patch_triton.py` |
| ` vllm_ascend/patch/worker/patch_unquantized_gemm.py` |
| ` vllm_ascend/patch/worker/patch_v2_egale.py` |
|` vllm_ascend/worker/npu_input_batch.py`|
|` vllm_ascend/worker/v2/aclgraph_utils.py`|
|` vllm_ascend/worker/v2/attn_utils.py`|
|` vllm_ascend/worker/v2/model_runner.py`|
|` vllm_ascend/worker/v2/sample/gumbel.py`|
|` vllm_ascend/worker/v2/sample/penalties.py`|
|` vllm_ascend/worker/v2/sample/sampler.py`|
|` vllm_ascend/worker/v2/spec_decode/__init__.py`|
|` vllm_ascend/worker/v2/spec_decode/eagle.py`|
|` vllm_ascend/worker/v2/states.py`|
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.14.0
- vLLM main:
d68209402d

Signed-off-by: MrZ20 <2609716663@qq.com>
Signed-off-by: SILONG ZENG <2609716663@qq.com>
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>

vllm_ascend/patch/worker/patch_qwen3_next_mtp.py

@@ -1,13 +1,15 @@
 import torch
 import vllm.v1.worker.utils as utils
 from vllm.v1.worker.utils import defaultdict, extract_layer_index
+
 from vllm_ascend.utils import vllm_version_is
 
 if vllm_version_is("v0.15.0"):
-    from vllm.attention.layer import Attention # type: ignore
+    from vllm.attention.layer import Attention  # type: ignore
 else:
     from vllm.model_executor.layers.attention import Attention
 
+
 # Without this patch, it will raise an exception when initialize kv_cache.
 # TODO To remove the patch, we need check why the original bind_kv_cache raises an NotImplementedError.
 def bind_kv_cache(
@@ -38,8 +40,7 @@ def bind_kv_cache(
     # Convert kv_caches dict to a list of tensors in the order of layer_index.
     index2name = defaultdict(list)
     for layer_name in kv_caches:
-        index2name[extract_layer_index(layer_name,
-                                       num_attn_module)].append(layer_name)
+        index2name[extract_layer_index(layer_name, num_attn_module)].append(layer_name)
 
     for layer_index in sorted(index2name.keys()):
         layer_names = index2name[layer_index]