[BufFix]Fix the error when using Ascend custom operators with rank=128 (#5394)

### What this PR does / why we need it?
The customized ascend operator sgmv_expand and sgmv_shrink applies only
to the scenario where rank is 8,16,32,64. When rank >= 128, the operator
is out of range, causing the model to report an error.
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?
Depends on this commit https://github.com/vllm-project/vllm/pull/31408 
- vLLM version: release/v0.13.0
- vLLM main:
254f6b9867

---------

Signed-off-by: ZT-AIA <1028681969@qq.com>
Signed-off-by: ZT-AIA <63220130+ZT-AIA@users.noreply.github.com>

tests/e2e/multicard/2-cards/test_ilama_lora_tp2.py

@@ -18,6 +18,7 @@ def test_ilama_lora_tp2(distributed_executor_backend, ilama_lora_files):
             tensor_parallel_size=2,
             cudagraph_capture_sizes=[1, 2, 4, 8],
             distributed_executor_backend=distributed_executor_backend,
+            enforce_eager=True,
     ) as vllm_model:
         output = do_sample(vllm_model.model, ilama_lora_files, lora_id=2)
 

tests/e2e/singlecard/test_ilama_lora.py

@@ -53,6 +53,7 @@ def test_ilama_lora(ilama_lora_files):
             max_model_len=1024,
             cudagraph_capture_sizes=[1, 2, 4, 8],
             max_num_seqs=16,
+            enforce_eager=True,
     ) as vllm_model:
 
         output1 = do_sample(vllm_model.model, ilama_lora_files, lora_id=1)