[BugFix] Fix Qwen3-next break (#3428)

### What this PR does / why we need it?
Fix Qwen3NextGatedDeltaNet, caused by
https://github.com/vllm-project/vllm/pull/26437

### How was this patch tested?
```
def main():
    prompts = [
        "窗前明月光，",
        "The president of the United States is Mr.",
        "The capital of France is",
        "The future of AI is",
        "感时花溅泪，",
        "家书抵万金啥意思？",
        "plz tell me a story: ",
    ]

    # Create a sampling params object.
    sampling_params = SamplingParams(max_tokens=100, temperature=0.6, top_k=40, top_p=0.95)
    # Create an LLM.
    llm = LLM(
        model="/root/.cache/modelscope/hub/models/Qwen/Qwen3-Next-80B-A3B-Instruct",
              tensor_parallel_size=4,
              enforce_eager=True,
              trust_remote_code=True,
              max_model_len=256,
              gpu_memory_utilization=0.7,
              block_size=64
              )

    # Generate texts from the prompts.
    outputs = llm.generate(prompts, sampling_params)
    for output in outputs:
        prompt = output.prompt
        generated_text = output.outputs[0].text
        print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
```


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: Icey <1790571317@qq.com>

vllm_ascend/models/qwen3_next.py

@@ -51,6 +51,8 @@ from vllm.model_executor.utils import set_weight_attrs
 from vllm.transformers_utils.configs import Qwen3NextConfig
 from vllm.v1.attention.backends.gdn_attn import GDNAttentionMetadata
 
+from vllm_ascend.utils import vllm_version_is
+
 from vllm.model_executor.models.qwen3_next import (  # isort: skip
     Qwen3NextAttention, Qwen3NextDecoderLayer, Qwen3NextForCausalLM,
     Qwen3NextGatedDeltaNet, Qwen3NextModel, Qwen3NextSparseMoeBlock,
@@ -201,7 +203,11 @@ class CustomQwen3NextGatedDeltaNet(Qwen3NextGatedDeltaNet, MambaBase):
         spec_query_start_loc = attn_metadata.spec_query_start_loc
         non_spec_query_start_loc = attn_metadata.non_spec_query_start_loc
         spec_sequence_masks = attn_metadata.spec_sequence_masks
-        spec_token_masks = attn_metadata.spec_token_masks
+        if vllm_version_is("0.11.0"):
+            spec_token_masks = attn_metadata.spec_token_masks
+        else:
+            spec_token_indx = attn_metadata.spec_token_indx
+            non_spec_token_indx = attn_metadata.non_spec_token_indx
         spec_state_indices_tensor = attn_metadata.spec_state_indices_tensor  # noqa: E501
         non_spec_state_indices_tensor = attn_metadata.non_spec_state_indices_tensor  # noqa: E501
         self_kv_cache = self.kv_cache[forward_context.virtual_engine]
@@ -216,8 +222,9 @@ class CustomQwen3NextGatedDeltaNet(Qwen3NextGatedDeltaNet, MambaBase):
 
         # 1. Set up dimensions for reshapes later
         projected_states, _ = self.in_proj(hidden_states[:num_actual_tokens])
-        if spec_token_masks is not None:
+        if vllm_version_is("0.11.0"):
-            spec_token_masks = spec_token_masks[:num_actual_tokens]
+            if spec_token_masks is not None:
+                spec_token_masks = spec_token_masks[:num_actual_tokens]
         projected_states_qkvz, projected_states_ba = torch.split(
             projected_states,
             [
@@ -242,8 +249,13 @@ class CustomQwen3NextGatedDeltaNet(Qwen3NextGatedDeltaNet, MambaBase):
                 mixed_qkv_spec = mixed_qkv
                 mixed_qkv_non_spec = None
             else:
-                mixed_qkv_spec = mixed_qkv[spec_token_masks]
+                if vllm_version_is("0.11.0"):
-                mixed_qkv_non_spec = mixed_qkv[~spec_token_masks]
+                    mixed_qkv_spec = mixed_qkv[spec_token_masks]
+                    mixed_qkv_non_spec = mixed_qkv[~spec_token_masks]
+                else:
+                    mixed_qkv_spec = mixed_qkv.index_select(0, spec_token_indx)
+                    mixed_qkv_non_spec = mixed_qkv.index_select(
+                        0, non_spec_token_indx)
         else:
             mixed_qkv_spec = None
             mixed_qkv_non_spec = mixed_qkv
@@ -293,10 +305,16 @@ class CustomQwen3NextGatedDeltaNet(Qwen3NextGatedDeltaNet, MambaBase):
                 g_non_spec = None
                 beta_non_spec = None
             else:
-                g_spec = g[:, spec_token_masks]
+                if vllm_version_is("0.11.0"):
-                beta_spec = beta[:, spec_token_masks]
+                    g_spec = g[:, spec_token_masks]
-                g_non_spec = g[:, ~spec_token_masks]
+                    beta_spec = beta[:, spec_token_masks]
-                beta_non_spec = beta[:, ~spec_token_masks]
+                    g_non_spec = g[:, ~spec_token_masks]
+                    beta_non_spec = beta[:, ~spec_token_masks]
+                else:
+                    g_spec = g.index_select(1, spec_token_indx)
+                    beta_spec = beta.index_select(1, spec_token_indx)
+                    g_non_spec = g.index_select(1, non_spec_token_indx)
+                    beta_non_spec = beta.index_select(1, non_spec_token_indx)
         else:
             g_spec = None
             beta_spec = None
@@ -404,8 +422,14 @@ class CustomQwen3NextGatedDeltaNet(Qwen3NextGatedDeltaNet, MambaBase):
                 dtype=core_attn_out_non_spec.dtype,
                 device=core_attn_out_non_spec.device,
             )
-            core_attn_out[:, spec_token_masks] = core_attn_out_spec
+            if vllm_version_is("0.11.0"):
-            core_attn_out[:, ~spec_token_masks] = core_attn_out_non_spec
+                core_attn_out[:, spec_token_masks] = core_attn_out_spec
+                core_attn_out[:, ~spec_token_masks] = core_attn_out_non_spec
+            else:
+                core_attn_out.index_copy_(1, spec_token_indx,
+                                          core_attn_out_spec)
+                core_attn_out.index_copy_(1, non_spec_token_indx,
+                                          core_attn_out_non_spec)
         elif spec_sequence_masks is not None:
             core_attn_out = core_attn_out_spec
         else: