support qwen3-next full_decode_only mode. (#3949)

### What this PR does / why we need it?
support qwen3-next full_decode_only mode. 
bs=1, max_token=1024
| branch| tps| e2e time|
| --- | --- | --- |
|piecewise  |3.06  | 8.15 |
|fulldecodeonly | 7.2 | 3.47 |

- vLLM version: v0.11.0
- vLLM main:
83f478bb19

Signed-off-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
Co-authored-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>

vllm_ascend/torchair/torchair_model_runner.py

@@ -31,6 +31,7 @@ from vllm.distributed.parallel_state import get_dp_group
 from vllm.forward_context import get_forward_context
 from vllm.logger import logger
 
+import numpy as np
 import vllm_ascend.envs as envs_ascend
 from vllm_ascend.ascend_config import get_ascend_config
 from vllm_ascend.platform import NPUPlatform
@@ -178,6 +179,7 @@ class NPUTorchairModelRunner(NPUModelRunner):
         num_reqs: int,
         num_tokens: int,
         max_query_len: int,
+        num_scheduled_tokens: np.ndarray,
         aclgraph_runtime_mode: Optional[CUDAGraphMode] = None,
         force_attention: bool = False,
     ) -> Optional[dict[str, Any]]:
@@ -186,7 +188,7 @@ class NPUTorchairModelRunner(NPUModelRunner):
         if with_prefill or self.enable_shared_expert_dp:
             attn_metadata = super()._build_dummy_attn_metadata(
                 with_prefill, num_reqs, num_tokens, max_query_len,
-                aclgraph_runtime_mode, force_attention)
+                num_scheduled_tokens, aclgraph_runtime_mode, force_attention)
         else:
             common_attn_metadata = TorchairCommonAttentionMetadata(
                 num_reqs=num_reqs,