support triton of mrope (#5664)

### What this PR does / why we need it?
this pr support use triton mrope like cuda_forward, which performance is
equal to ascendc ops
this triton ops should use cann 8.5.0
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?
test in qwen3-vl-235b acc textvqa
native 81.82
npu triton 81.58
cuda triton 81.52
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef

Signed-off-by: shiyuan680 <917935075@qq.com>

vllm_ascend/ops/rotary_embedding.py

@@ -25,6 +25,10 @@ from vllm.model_executor.layers.rotary_embedding import (
     DeepseekScalingRotaryEmbedding, MRotaryEmbedding, RotaryEmbedding,
     YaRNScalingRotaryEmbedding)
 from vllm.model_executor.layers.rotary_embedding.common import ApplyRotaryEmb
+from vllm.triton_utils import HAS_TRITON
+
+if HAS_TRITON:
+    from vllm.model_executor.layers.rotary_embedding.mrope import triton_mrope
 
 from vllm_ascend.platform import NPUPlatform
 from vllm_ascend.utils import (AscendDeviceType, enable_custom_op,
@@ -527,12 +531,50 @@ class AscendDeepseekScalingRotaryEmbedding(DeepseekScalingRotaryEmbedding):
 
 class AscendMRotaryEmbedding(MRotaryEmbedding):
 
+    def forward_triton(self,
+                       positions: torch.Tensor,
+                       query: torch.Tensor,
+                       key: torch.Tensor | None = None,
+                       offsets: torch.Tensor | None = None):
+        assert positions.ndim == 2
+        assert key is not None
+
+        self._match_cos_sin_cache_dtype(query)
+        self.cos = None
+        self.sin = None
+        if self.cos is None and self.sin is None:
+            cos_sin = self.cos_sin_cache[positions]  # type: ignore
+            cos, sin = cos_sin.chunk(2, dim=-1)
+            self.cos = cos.contiguous()
+            self.sin = sin.contiguous()
+        query_shape = query.shape
+        key_shape = key.shape
+
+        assert self.mrope_section
+
+        q, k = triton_mrope(
+            query,
+            key,
+            self.cos,
+            self.sin,
+            self.mrope_section,
+            self.head_size,
+            self.rotary_dim,
+            self.mrope_interleaved,
+        )
+
+        return q.reshape(query_shape), k.reshape(key_shape)
+
     def forward_oot(
         self,
         positions: torch.Tensor,
         query: torch.Tensor,
         key: torch.Tensor,
     ):
+        if HAS_TRITON and positions.ndim == 2:
+            # todo: need cann update in 8.5.0
+            return self.forward_triton(positions, query, key)
+
         if self.mrope_section != [16, 24, 24] or \
             get_ascend_device_type() == AscendDeviceType.A5:
             return super().forward_oot(positions, query, key)