[Kernel] Use fused rmsnorm for some models like qwen3 series (#17735)

Signed-off-by: evian <eviantai@u.nus.edu>
Co-authored-by: evian <eviantai@u.nus.edu>

vllm/model_executor/models/olmo2.py

@@ -139,8 +139,8 @@ class Olmo2Attention(nn.Module):
         if self.tp_size > 1:
             q = tensor_model_parallel_all_gather(q.contiguous())
             k = tensor_model_parallel_all_gather(k.contiguous())
-        q = self.q_norm.forward_native(q)
-        k = self.k_norm.forward_native(k)
+        q = self.q_norm(q)
+        k = self.k_norm(k)
         if self.tp_size > 1:
             splitter = partial(split_tensor_along_last_dim,
                                num_partitions=self.tp_size)