[v0.18.0][Feature] support qkv_rmsnorm_mrope for qwen3vl (#7852)

### What this PR does / why we need it?
Qwen3vl full attention supports enabling the split_qkv_rmsnorm_mrope
fusion operator.
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?
- [x] Run Qwen3-VL dense model with the fusion operator, verify correct
output
- [x] Run Qwen3-VL MoE model with the fusion operator, verify correct
output

---------

Signed-off-by: jiangmengyu18 <451528648@qq.com>
Signed-off-by: jiangmengyu18 <56633611+jiangmengyu18@users.noreply.github.com>
Signed-off-by: betta18 <jiangmengyu1@huawei.com>
Co-authored-by: betta18 <jiangmengyu1@huawei.com>

vllm_ascend/patch/worker/patch_qwen3vl.py

@@ -0,0 +1,44 @@
+import torch
+from vllm.model_executor.models.qwen3 import Qwen3Attention
+from vllm.model_executor.models.qwen3_moe import Qwen3MoeAttention
+
+from vllm_ascend.ops.rotary_embedding import AscendMRotaryEmbedding
+
+
+def forward_with_split_qkv_rmsnorm_mrope(self, positions: torch.Tensor, hidden_states: torch.Tensor):
+    qkv, _ = self.qkv_proj(hidden_states)
+    if isinstance(self.rotary_emb, AscendMRotaryEmbedding):
+        cos_sin = self.rotary_emb.cos_sin_cache[positions]
+        if cos_sin.device != qkv.device:
+            cos_sin = cos_sin.to(qkv.device)
+        if cos_sin.dtype != qkv.dtype:
+            cos_sin = cos_sin.to(qkv.dtype)
+        q, k, v, _ = torch.ops.vllm.triton_split_qkv_rmsnorm_mrope(
+            qkv=qkv,
+            q_weight=self.q_norm.weight,
+            k_weight=self.k_norm.weight,
+            cos_sin=cos_sin,
+            num_q_heads=self.num_heads,
+            num_kv_heads=self.num_kv_heads,
+            head_size=self.head_dim,
+            eps=self.q_norm.variance_epsilon,
+            mrope_section=self.rotary_emb.mrope_section,
+            is_interleaved=self.rotary_emb.mrope_interleaved,
+            rope_dim=self.rotary_emb.rotary_dim,
+        )
+    else:
+        q, k, v = qkv.split([self.q_size, self.kv_size, self.kv_size], dim=-1)
+        q_by_head = q.view(*q.shape[:-1], q.shape[-1] // self.head_dim, self.head_dim)
+        q_by_head = self.q_norm(q_by_head)
+        q = q_by_head.view(q.shape)
+        k_by_head = k.view(*k.shape[:-1], k.shape[-1] // self.head_dim, self.head_dim)
+        k_by_head = self.k_norm(k_by_head)
+        k = k_by_head.view(k.shape)
+        q, k = self.rotary_emb(positions, q, k)
+    attn_output = self.attn(q, k, v)
+    output, _ = self.o_proj(attn_output)
+    return output
+
+
+Qwen3Attention.forward = forward_with_split_qkv_rmsnorm_mrope
+Qwen3MoeAttention.forward = forward_with_split_qkv_rmsnorm_mrope