Add restriction conditions to the ApplyTopPTopK operator (#3254)

### What this PR does / why we need it?
Add restriction conditions to the ApplyTopPTopK operator : 1 <= K <=1024
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?

- vLLM version: v0.10.2
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.0

---------

Signed-off-by: SunnyLee219 <3294305115@qq.com>

vllm_ascend/sample/sampler.py

@@ -29,7 +29,8 @@ class AscendTopKTopPSampler(TopKTopPSampler):
         p: torch.Tensor,
     ) -> torch.Tensor:
         # npu_top_k_top_p uses the operator aclnnApplyTopKTopP, but aclnnApplyTopKTopP currently does not support 310P
-        if not is_310p() and p is not None and k is not None:
+        if not is_310p() and p is not None and k is not None and 1 <= int(
+                k.max()) <= 1024:
             # npu_top_k_top_p's parameter order is (logits, p, k), not (logits, k, p)
             return torch_npu.npu_top_k_top_p(logits, p, k)