[Lint]Style: Convert vllm-ascend/ to ruff format(Batch #12) (#6177)

### What this PR does / why we need it?
**Scope of Changes**:
| File Path |
| :--- |
| `vllm_ascend/ops/triton/activation/swiglu_quant.py` |
| `vllm_ascend/ops/triton/batch_invariant/matmul.py` |
| `vllm_ascend/ops/triton/batch_invariant/mean.py` |
| `vllm_ascend/ops/triton/batch_invariant/rmsnorm.py` |
| `vllm_ascend/ops/triton/fla/chunk.py` |
| `vllm_ascend/ops/triton/fla/chunk_delta_h.py` |
| `vllm_ascend/ops/triton/fla/chunk_o.py` |
| `vllm_ascend/ops/triton/fla/chunk_scaled_dot_kkt.py` |
| `vllm_ascend/ops/triton/fla/cumsum.py` |
| `vllm_ascend/ops/triton/fla/fused_qkvzba_split_reshape.py` |
| `vllm_ascend/ops/triton/fla/l2norm.py` |
| `vllm_ascend/ops/triton/fla/layernorm_guard.py` |
| `vllm_ascend/ops/triton/fla/sigmoid_gating.py` |
| `vllm_ascend/ops/triton/fla/solve_tril.py` |
| `vllm_ascend/ops/triton/fla/utils.py` |
| `vllm_ascend/ops/triton/fla/wy_fast.py` |
| `vllm_ascend/ops/triton/fused_gdn_gating.py` |
| `vllm_ascend/ops/triton/layernorm_gated.py` |
| `vllm_ascend/ops/triton/linearnorm/split_qkv_rmsnorm_rope.py` |
| `vllm_ascend/ops/triton/mamba/causal_conv1d.py` |
| `vllm_ascend/ops/triton/reject_sample.py` |
| `vllm_ascend/ops/triton/rope.py` |
| `vllm_ascend/ops/triton/spec_decode/utils.py` |
| `vllm_ascend/ops/triton/triton_utils.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>

vllm_ascend/ops/triton/batch_invariant/rmsnorm.py

@@ -100,8 +100,8 @@ def rms_norm(
     """
     assert weight.dim() == 1, "Weight must be 1-dimensional"
     assert input_.shape[-1] == weight.shape[0], (
-        f"Input last dimension ({input_.shape[-1]}) must match "
-        f"weight dimension ({weight.shape[0]})")
+        f"Input last dimension ({input_.shape[-1]}) must match weight dimension ({weight.shape[0]})"
+    )
 
     # Flatten all dimensions except the last one
     original_shape = input_.shape
@@ -113,10 +113,9 @@ def rms_norm(
 
     output = torch.empty_like(input_2d, dtype=input_.dtype)
     BLOCK_SIZE = 1024
-    max_grid_size = driver.active.utils.get_device_properties(
-        torch.npu.current_device())["num_vectorcore"]
+    max_grid_size = driver.active.utils.get_device_properties(torch.npu.current_device())["num_vectorcore"]
 
-    grid = (min(n_rows, max_grid_size), )
+    grid = (min(n_rows, max_grid_size),)
 
     _rms_norm_kernel[grid](
         input_2d,