[feat] 支持 mRoPE 的 fused RMSNorm+RoPE 路径，并修正 torch.compile 动态维度标注

实现了用于优化张量计算的 rms_mrope_fuse 和 rms_mrope_fuse_fake 方法
更新了 forward：在满足条件时走新的 M-RoPE 融合路径
增强了 Qwen3MoeModel 对动态参数维度的支持，以适配该功能

vllm/model_executor/models/qwen3_moe.py

@@ -325,6 +325,67 @@ class Qwen3MoeAttention(nn.Module):
         fake_impl=rms_rotary_embedding_fuse_fake,
     )
 
+    def rms_mrope_fuse(
+        query: torch.Tensor,
+        key: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        head_size: int,
+        rotary_dim: int,
+        mrope_section_t: int,
+        mrope_section_h: int,
+        mrope_section_w: int,
+        mrope_interleaved: bool,
+        q_weight: torch.Tensor,
+        k_weight: torch.Tensor,
+        q_residual: Optional[torch.Tensor],
+        k_residual: Optional[torch.Tensor],
+        epsilon: float,
+    ) -> None:
+        from lightop import op as lightop_ops
+        lightop_ops.fuse_rms_mrope_cuda(
+            query,
+            key,
+            cos,
+            sin,
+            [mrope_section_t, mrope_section_h, mrope_section_w],
+            head_size,
+            rotary_dim,
+            mrope_interleaved,
+            q_weight,
+            k_weight,
+            q_residual,
+            k_residual,
+            epsilon,
+        )
+
+    def rms_mrope_fuse_fake(
+        query: torch.Tensor,
+        key: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        head_size: int,
+        rotary_dim: int,
+        mrope_section_t: int,
+        mrope_section_h: int,
+        mrope_section_w: int,
+        mrope_interleaved: bool,
+        q_weight: torch.Tensor,
+        k_weight: torch.Tensor,
+        q_residual: Optional[torch.Tensor],
+        k_residual: Optional[torch.Tensor],
+        epsilon: float,
+    ) -> None:
+        # Fake impl intentionally left as no-op for graph tracing modes.
+        pass
+
+    direct_register_custom_op(
+        op_name="rms_mrope_fuse",
+        op_func=rms_mrope_fuse,
+        mutates_args=["query", "key"],
+        fake_impl=rms_mrope_fuse_fake,
+    )
+
     def forward(
         self,
         positions: torch.Tensor,
@@ -333,7 +394,7 @@ class Qwen3MoeAttention(nn.Module):
         qkv, _ = self.qkv_proj(hidden_states)
         q, k, v = qkv.split([self.q_size, self.kv_size, self.kv_size], dim=-1)
         # Add qk-norm
-        if envs.VLLM_USE_FUSED_RMS_ROPE :
+        if envs.VLLM_USE_FUSED_RMS_ROPE and positions.ndim == 1:
             # Fused RMSNorm + RoPE path through custom op.
             cos_sin_cache = self.rotary_emb.cos_sin_cache
             if (cos_sin_cache.device != q.device
@@ -361,6 +422,44 @@ class Qwen3MoeAttention(nn.Module):
                 self.q_norm.variance_epsilon,
             )
 
+        elif envs.VLLM_USE_FUSED_RMS_ROPE and positions.ndim == 2 and getattr(
+                self.rotary_emb, "mrope_section", None) is not None:
+            # Fused RMSNorm + M-RoPE path through custom op.
+            cos_sin_cache = self.rotary_emb.cos_sin_cache
+            if (cos_sin_cache.device != q.device
+                    or cos_sin_cache.dtype != q.dtype):
+                cos_sin_cache = cos_sin_cache.to(q.device,
+                                                 dtype=q.dtype,
+                                                 non_blocking=True)
+                self.rotary_emb.cos_sin_cache = cos_sin_cache
+
+            cos_sin = cos_sin_cache[positions]
+            cos, sin = cos_sin.chunk(2, dim=-1)
+
+            q = q.contiguous()
+            k = k.contiguous()
+            cos = cos.contiguous()
+            sin = sin.contiguous()
+            mrope_section = self.rotary_emb.mrope_section
+            assert mrope_section is not None and len(mrope_section) == 3
+            torch.ops.vllm.rms_mrope_fuse(
+                q,
+                k,
+                cos,
+                sin,
+                self.head_dim,
+                self.rotary_emb.rotary_dim,
+                mrope_section[0],
+                mrope_section[1],
+                mrope_section[2],
+                self.rotary_emb.mrope_interleaved,
+                self.q_norm.weight,
+                self.k_norm.weight,
+                None,
+                None,
+                self.q_norm.variance_epsilon,
+            )
+
         else:
             # Add qk-norm then RoPE (original path).
             q_by_head = q.view(*q.shape[:-1], q.shape[-1] // self.head_dim,
@@ -462,7 +561,15 @@ class Qwen3MoeDecoderLayer(nn.Module):
         return hidden_states, residual
 
 
-@support_torch_compile
+@support_torch_compile(
+    dynamic_arg_dims={
+        "input_ids": 0,
+        # positions is of shape (3, seq_len) if mrope is enabled,
+        # otherwise (seq_len, ).
+        "positions": -1,
+        "intermediate_tensors": 0,
+        "inputs_embeds": 0,
+    })
 class Qwen3MoeModel(nn.Module):
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):